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SQL | Functions | Interval Functions | `date_part(part, interval)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Extract [datepart component](#docs:sql:functions:datepart) (equivalent to `extract`). See [`INTERVAL`](#docs:sql:data_types:interval) for the sometimes surprising rules governing this extraction. |
| **Example** | `date_part('year', INTERVAL '14 months')` |
| **Result** | `1` | | 100 | [
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SQL | Functions | Interval Functions | `datepart(part, interval)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Alias of `date_part`. |
| **Example** | `datepart('year', INTERVAL '14 months')` |
| **Result** | `1` | | 61 | [
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] |
SQL | Functions | Interval Functions | `extract(part FROM interval)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Alias of `date_part`. |
| **Example** | `extract('month' FROM INTERVAL '14 months')` |
| **Result** | 2 | | 60 | [
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SQL | Functions | Interval Functions | `epoch(interval)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Get total number of seconds, as double precision floating point number, in interval. |
| **Example** | `epoch(INTERVAL 5 HOUR)` |
| **Result** | `18000.0` | | 71 | [
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SQL | Functions | Interval Functions | `to_centuries(integer)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Construct a century interval. |
| **Example** | `to_centuries(5)` |
| **Result** | `INTERVAL 500 YEAR` | | 59 | [
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] |
SQL | Functions | Interval Functions | `to_days(integer)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Construct a day interval. |
| **Example** | `to_days(5)` |
| **Result** | `INTERVAL 5 DAY` | | 58 | [
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SQL | Functions | Interval Functions | `to_decades(integer)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Construct a decade interval. |
| **Example** | `to_decades(5)` |
| **Result** | `INTERVAL 50 YEAR` | | 59 | [
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SQL | Functions | Interval Functions | `to_hours(integer)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Construct a hour interval. |
| **Example** | `to_hours(5)` |
| **Result** | `INTERVAL 5 HOUR` | | 58 | [
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SQL | Functions | Interval Functions | `to_microseconds(integer)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Construct a microsecond interval. |
| **Example** | `to_microseconds(5)` |
| **Result** | `INTERVAL 5 MICROSECOND` | | 61 | [
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SQL | Functions | Interval Functions | `to_millennia(integer)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Construct a millennium interval. |
| **Example** | `to_millennia(5)` |
| **Result** | `INTERVAL 5000 YEAR` | | 62 | [
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SQL | Functions | Interval Functions | `to_milliseconds(integer)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Construct a millisecond interval. |
| **Example** | `to_milliseconds(5)` |
| **Result** | `INTERVAL 5 MILLISECOND` | | 62 | [
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SQL | Functions | Interval Functions | `to_minutes(integer)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Construct a minute interval. |
| **Example** | `to_minutes(5)` |
| **Result** | `INTERVAL 5 MINUTE` | | 59 | [
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SQL | Functions | Interval Functions | `to_months(integer)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Construct a month interval. |
| **Example** | `to_months(5)` |
| **Result** | `INTERVAL 5 MONTH` | | 58 | [
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] |
SQL | Functions | Interval Functions | `to_seconds(integer)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Construct a second interval. |
| **Example** | `to_seconds(5)` |
| **Result** | `INTERVAL 5 SECOND` | | 58 | [
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SQL | Functions | Interval Functions | `to_weeks(integer)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Construct a week interval. |
| **Example** | `to_weeks(5)` |
| **Result** | `INTERVAL 35 DAY` | | 59 | [
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SQL | Functions | Interval Functions | `to_years(integer)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Construct a year interval. |
| **Example** | `to_years(5)` |
| **Result** | `INTERVAL 5 YEAR` | | 58 | [
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SQL | Functions | Lambda Functions | Lambda functions enable the use of more complex and flexible expressions in queries.
DuckDB supports several scalar functions that operate on [`LIST`s](#docs:sql:data_types:list) and
accept lambda functions as parameters
in the form `(parameter1, parameter2, ...) -> expression`.
If the lambda function has only one parameter, then the parentheses can be omitted.
The parameters can have any names.
For example, the following are all valid lambda functions:
* `param -> param > 1`
* `s -> contains(concat(s, 'DB'), 'duck')`
* `(x, y) -> x + y` | 128 | [
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|
SQL | Functions | Scalar Functions That Accept Lambda Functions | | Name | Description |
|:--|:-------|
| [`list_transform(list, lambda)`](#::list_transformlist-lambda) | Returns a list that is the result of applying the lambda function to each element of the input list. |
| [`list_filter(list, lambda)`](#::list_filterlist-lambda) | Constructs a list from those elements of the input list for which the lambda function returns `true`. |
| [`list_reduce(list, lambda)`](#::list_reducelist-lambda) | Reduces all elements of the input list into a single value by executing the lambda function on a running result and the next list element. The list must have at least one element – the use of an initial accumulator value is currently not supported. |
#### `list_transform(list, lambda)` {#docs:sql:functions:lambda::list_transformlist-lambda}
<div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Returns a list that is the result of applying the lambda function to each element of the input list. For more information, see [Transform](#::transform). |
| **Example** | `list_transform([4, 5, 6], x -> x + 1)` |
| **Result** | `[5, 6, 7]` |
| **Aliases** | `array_transform`, `apply`, `list_apply`, `array_apply` |
#### `list_filter(list, lambda)` {#docs:sql:functions:lambda::list_filterlist-lambda}
<div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Constructs a list from those elements of the input list for which the lambda function returns `true`. For more information, see [Filter](#::filter). |
| **Example** | `list_filter([4, 5, 6], x -> x > 4)` |
| **Result** | `[5, 6]` |
| **Aliases** | `array_filter`, `filter` |
#### `list_reduce(list, lambda)` {#docs:sql:functions:lambda::list_reducelist-lambda}
<div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Reduces all elements of the input list into a single value by executing the lambda function on a running result and the next list element. The list must have at least one element – the use of an initial accumulator value is currently not supported. For more information, see [Reduce](#::reduce). |
| **Example** | `list_reduce([4, 5, 6], (x, y) -> x + y)` |
| **Result** | `15` |
| **Aliases** | `array_reduce`, `reduce` | | 609 | [
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|
SQL | Functions | Nesting | All scalar functions can be arbitrarily nested.
_Nested lambda functions to get all squares of even list elements:_
```sql
SELECT list_transform(
list_filter([0, 1, 2, 3, 4, 5], x -> x % 2 = 0),
y -> y * y
);
```
```text
[0, 4, 16]
```
_Nested lambda function to add each element of the first list to the sum of the second list:_
```sql
SELECT list_transform(
[1, 2, 3],
x -> list_reduce([4, 5, 6], (a, b) -> a + b) + x
);
```
```text
[16, 17, 18]
``` | 162 | [
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|
SQL | Functions | Scoping | Lambda functions confirm to scoping rules in the following order:
* inner lambda parameters
* outer lambda parameters
* column names
* macro parameters
```sql
CREATE TABLE tbl (x INTEGER);
INSERT INTO tbl VALUES (10);
SELECT apply([1, 2], x -> apply([4], x -> x + tbl.x)[1] + x) FROM tbl;
```
```text
[15, 16]
``` | 89 | [
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|
SQL | Functions | Indexes as Parameters | All lambda functions accept an optional extra parameter that represents the index of the current element.
This is always the last parameter of the lambda function, and is 1-based (i.e., the first element has index 1).
_Get all elements that are larger than their index:_
```sql
SELECT list_filter([1, 3, 1, 5], (x, i) -> x > i);
```
```text
[3, 5]
``` | 97 | [
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|
SQL | Functions | Transform | **Signature:** `list_transform(list, lambda)`
**Description:** `list_transform` returns a list that is the result of applying the lambda function to each element of the input list.
**Aliases:**
* `array_transform`
* `apply`
* `list_apply`
* `array_apply`
**Number of parameters excluding indexes:** 1
**Return type:** Defined by the return type of the lambda function
#### Examples {#docs:sql:functions:lambda::examples}
Incrementing each list element by one:
```sql
SELECT list_transform([1, 2, NULL, 3], x -> x + 1);
```
```text
[2, 3, NULL, 4]
```
Transforming strings:
```sql
SELECT list_transform(['Duck', 'Goose', 'Sparrow'], s -> concat(s, 'DB'));
```
```text
[DuckDB, GooseDB, SparrowDB]
```
Combining lambda functions with other functions:
```sql
SELECT list_transform([5, NULL, 6], x -> coalesce(x, 0) + 1);
```
```text
[6, 1, 7]
``` | 254 | [
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|
SQL | Functions | Filter | **Signature:** `list_filter(list, lambda)`
**Description:**
Constructs a list from those elements of the input list for which the lambda function returns `true`.
DuckDB must be able to cast the lambda function's return type to `BOOL`.
**Aliases:**
* `array_filter`
* `filter`
**Number of parameters excluding indexes:** 1
**Return type:** The same type as the input list
#### Examples {#docs:sql:functions:lambda::examples}
Filter out negative values:
```sql
SELECT list_filter([5, -6, NULL, 7], x -> x > 0);
```
```text
[5, 7]
```
Divisible by 2 and 5:
```sql
SELECT list_filter(
list_filter([2, 4, 3, 1, 20, 10, 3, 30], x -> x % 2 = 0),
y -> y % 5 = 0
);
```
```text
[20, 10, 30]
```
In combination with `range(...)` to construct lists:
```sql
SELECT list_filter([1, 2, 3, 4], x -> x > #1) FROM range(4);
```
```text
[1, 2, 3, 4]
[2, 3, 4]
[3, 4]
[4]
[]
``` | 307 | [
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|
SQL | Functions | Reduce | **Signature:** `list_reduce(list, lambda)`
**Description:**
The scalar function returns a single value
that is the result of applying the lambda function to each element of the input list.
Starting with the first element
and then repeatedly applying the lambda function to the result of the previous application and the next element of the list.
The list must have at least one element.
**Aliases:**
* `array_reduce`
* `reduce`
**Number of parameters excluding indexes:** 2
**Return type:** The type of the input list's elements
#### Examples {#docs:sql:functions:lambda::examples}
Sum of all list elements:
```sql
SELECT list_reduce([1, 2, 3, 4], (x, y) -> x + y);
```
```text
10
```
Only add up list elements if they are greater than 2:
```sql
SELECT list_reduce(list_filter([1, 2, 3, 4], x -> x > 2), (x, y) -> x + y);
```
```text
7
```
Concat all list elements:
```sql
SELECT list_reduce(['DuckDB', 'is', 'awesome'], (x, y) -> concat(x, ' ', y));
```
```text
DuckDB is awesome
``` | 282 | [
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|
SQL | Functions | List Functions | <!-- markdownlint-disable MD001 MD056 -->
| Name | Description |
|:--|:-------|
| [`list[index]`](#listindex) | Bracket notation serves as an alias for `list_extract`. |
| [`list[begin:end]`](#listbeginend) | Bracket notation with colon is an alias for `list_slice`. |
| [`list[begin:end:step]`](#listbeginendstep) | `list_slice` in bracket notation with an added `step` feature. |
| [`array_pop_back(list)`](#::array_pop_backlist) | Returns the list without the last element. |
| [`array_pop_front(list)`](#::array_pop_frontlist) | Returns the list without the first element. |
| [`flatten(list_of_lists)`](#::flattenlist_of_lists) | Concatenate a list of lists into a single list. This only flattens one level of the list (see [examples](#::flattening)). |
| [`len(list)`](#::lenlist) | Return the length of the list. |
| [`list_aggregate(list, name)`](#::list_aggregatelist-name) | Executes the aggregate function `name` on the elements of `list`. See the [List Aggregates](#docs:sql:functions:list::list-aggregates) section for more details. |
| [`list_any_value(list)`](#::list_any_valuelist) | Returns the first non-null value in the list. |
| [`list_append(list, element)`](#::list_appendlist-element) | Appends `element` to `list`. |
| [`list_concat(list1, list2)`](#::list_concatlist1-list2) | Concatenate two lists. NULL inputs are skipped. See also `||` |
| [`list_contains(list, element)`](#::list_containslist-element) | Returns true if the list contains the element. |
| [`list_cosine_similarity(list1, list2)`](#::list_cosine_similaritylist1-list2) | Compute the cosine similarity between two lists. |
| [`list_cosine_distance(list1, list2)`](#::list_cosine_distancelist1-list2) | Compute the cosine distance between two lists. Equivalent to `1.0 - list_cosine_similarity`. |
| [`list_distance(list1, list2)`](#::list_distancelist1-list2) | Calculates the Euclidean distance between two points with coordinates given in two inputs lists of equal length. |
| [`list_distinct(list)`](#::list_distinctlist) | Removes all duplicates and `NULL` values from a list. Does not preserve the original order. |
| [`list_dot_product(list1, list2)`](#::list_dot_productlist1-list2) | Computes the dot product of two same-sized lists of numbers. |
| [`list_negative_dot_product(list1, list2)`](#::list_negative_dot_productlist1-list2) | Computes the negative dot product of two same-sized lists of numbers. Equivalent to `- list_dot_product`. |
| [`list_extract(list, index)`](#::list_extractlist-index) | Extract the `index`th (1-based) value from the list. |
| [`list_filter(list, lambda)`](#::list_filterlist-lambda) | Constructs a list from those elements of the input list for which the lambda function returns true. See the [Lambda Functions](#docs:sql:functions:lambda::filter) page for more details. |
| [`list_grade_up(list)`](#::list_grade_uplist) | Works like sort, but the results are the indexes that correspond to the position in the original `list` instead of the actual values. |
| [`list_has_all(list, sub-list)`](#::list_has_alllist-sub-list) | Returns true if all elements of sub-list exist in list. |
| [`list_has_any(list1, list2)`](#::list_has_anylist1-list2) | Returns true if any elements exist is both lists. |
| [`list_intersect(list1, list2)`](#::list_intersectlist1-list2) | Returns a list of all the elements that exist in both `l1` and `l2`, without duplicates. |
| [`list_position(list, element)`](#::list_positionlist-element) | Returns the index of the element if the list contains the element. If the element is not found, it returns `NULL`. |
| [`list_prepend(element, list)`](#::list_prependelement-list) | Prepends `element` to `list`. |
| [`list_reduce(list, lambda)`](#::list_reducelist-lambda) | Returns a single value that is the result of applying the lambda function to each element of the input list. See the [Lambda Functions](#docs:sql:functions:lambda::reduce) page for more details. |
| [`list_resize(list, size[, value])`](#list_resizelist-size-value) | Resizes the list to contain `size` elements. Initializes new elements with `value` or `NULL` if `value` is not set. |
| [`list_reverse_sort(list)`](#::list_reverse_sortlist) | Sorts the elements of the list in reverse order. See the [Sorting Lists](#docs:sql:functions:list::sorting-lists) section for more details about the `NULL` sorting order. |
| [`list_reverse(list)`](#::list_reverselist) | Reverses the list. |
| [`list_select(value_list, index_list)`](#::list_selectvalue_list-index_list) | Returns a list based on the elements selected by the `index_list`. |
| [`list_slice(list, begin, end, step)`](#::list_slicelist-begin-end-step) | `list_slice` with added `step` feature. |
| [`list_slice(list, begin, end)`](#::list_slicelist-begin-end) | Extract a sublist using slice conventions. Negative values are accepted. See [slicing](#docs:sql:functions:list::slicing). |
| [`list_sort(list)`](#::list_sortlist) | Sorts the elements of the list. See the [Sorting Lists](#docs:sql:functions:list::sorting-lists) section for more details about the sorting order and the `NULL` sorting order. |
| [`list_transform(list, lambda)`](#::list_transformlist-lambda) | Returns a list that is the result of applying the lambda function to each element of the input list. See the [Lambda Functions](#docs:sql:functions:lambda::transform) page for more details. |
| [`list_unique(list)`](#::list_uniquelist) | Counts the unique elements of a list. |
| [`list_value(any, ...)`](#::list_valueany-) | Create a `LIST` containing the argument values. |
| [`list_where(value_list, mask_list)`](#::list_wherevalue_list-mask_list) | Returns a list with the `BOOLEAN`s in `mask_list` applied as a mask to the `value_list`. |
| [`list_zip(list_1, list_2, ...[, truncate])`](#list_ziplist1-list2-) | Zips _k_ `LIST`s to a new `LIST` whose length will be that of the longest list. Its elements are structs of _k_ elements from each list `list_1`, ..., `list_k`, missing elements are replaced with `NULL`. If `truncate` is set, all lists are truncated to the smallest list length. |
| [`unnest(list)`](#::unnestlist) | Unnests a list by one level. Note that this is a special function that alters the cardinality of the result. See the [`unnest` page](#docs:sql:query_syntax:unnest) for more details. | | 1,658 | [
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|
SQL | Functions | List Functions | `list[index]` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Bracket notation serves as an alias for `list_extract`. |
| **Example** | `[4, 5, 6][3]` |
| **Result** | `6` |
| **Alias** | `list_extract` | | 76 | [
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SQL | Functions | List Functions | `list[begin:end]` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Bracket notation with colon is an alias for `list_slice`. |
| **Example** | `[4, 5, 6][2:3]` |
| **Result** | `[5, 6]` |
| **Alias** | `list_slice` | | 83 | [
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SQL | Functions | List Functions | `list[begin:end:step]` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |`list_slice` in bracket notation with an added `step` feature. |
| **Example** | `[4, 5, 6][:-:2]` |
| **Result** | `[4, 6]` |
| **Alias** | `list_slice` | | 86 | [
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SQL | Functions | List Functions | `array_pop_back(list)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Returns the list without the last element. |
| **Example** | `array_pop_back([4, 5, 6])` |
| **Result** | `[4, 5]` | | 69 | [
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SQL | Functions | List Functions | `array_pop_front(list)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Returns the list without the first element. |
| **Example** | `array_pop_front([4, 5, 6])` |
| **Result** | `[5, 6]` | | 69 | [
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SQL | Functions | List Functions | `flatten(list_of_lists)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Concatenate a list of lists into a single list. This only flattens one level of the list (see [examples](#::flattening)). |
| **Example** | `flatten([[1, 2], [3, 4]])` |
| **Result** | `[1, 2, 3, 4]` | | 99 | [
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SQL | Functions | List Functions | `len(list)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Return the length of the list. |
| **Example** | `len([1, 2, 3])` |
| **Result** | `3` |
| **Alias** | `array_length` | | 72 | [
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SQL | Functions | List Functions | `list_aggregate(list, name)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Executes the aggregate function `name` on the elements of `list`. See the [List Aggregates](#docs:sql:functions:list::list-aggregates) section for more details. |
| **Example** | `list_aggregate([1, 2, NULL], 'min')` |
| **Result** | `1` |
| **Aliases** | `list_aggr`, `aggregate`, `array_aggregate`, `array_aggr` | | 124 | [
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SQL | Functions | List Functions | `list_any_value(list)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Returns the first non-null value in the list. |
| **Example** | `list_any_value([NULL, -3])` |
| **Result** | `-3` | | 64 | [
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] |
SQL | Functions | List Functions | `list_append(list, element)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Appends `element` to `list`. |
| **Example** | `list_append([2, 3], 4)` |
| **Result** | `[2, 3, 4]` |
| **Aliases** | `array_append`, `array_push_back` | | 86 | [
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SQL | Functions | List Functions | `list_concat(list1, list2)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Concatenate two lists. `NULL` inputs are skipped. See also `||` |
| **Example** | `list_concat([2, 3], [4, 5, 6])` |
| **Result** | `[2, 3, 4, 5, 6]` |
| **Aliases** | `list_cat`, `array_concat`, `array_cat` | | 111 | [
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SQL | Functions | List Functions | `list_contains(list, element)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Returns true if the list contains the element. |
| **Example** | `list_contains([1, 2, NULL], 1)` |
| **Result** | `true` |
| **Aliases** | `list_has`, `array_contains`, `array_has` | | 84 | [
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] |
SQL | Functions | List Functions | `list_cosine_similarity(list1, list2)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Compute the cosine similarity between two lists. |
| **Example** | `list_cosine_similarity([1, 2, 3], [1, 2, 5])` |
| **Result** | `0.9759000729485332` | | 82 | [
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] |
SQL | Functions | List Functions | `list_cosine_distance(list1, list2)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Compute the cosine distance between two lists. Equivalent to `1.0 - list_cosine_similarity` |
| **Example** | `list_cosine_distance([1, 2, 3], [1, 2, 5])` |
| **Result** | `0.007416606` | | 91 | [
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SQL | Functions | List Functions | `list_distance(list1, list2)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Calculates the Euclidean distance between two points with coordinates given in two inputs lists of equal length. |
| **Example** | `list_distance([1, 2, 3], [1, 2, 5])` |
| **Result** | `2.0` | | 87 | [
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SQL | Functions | List Functions | `list_distinct(list)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Removes all duplicates and `NULL` values from a list. Does not preserve the original order. |
| **Example** | `list_distinct([1, 1, NULL, -3, 1, 5])` |
| **Result** | `[1, 5, -3]` |
| **Alias** | `array_distinct` | | 103 | [
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SQL | Functions | List Functions | `list_dot_product(list1, list2)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Computes the dot product of two same-sized lists of numbers. |
| **Example** | `list_dot_product([1, 2, 3], [1, 2, 5])` |
| **Result** | `20.0` |
| **Alias** | `list_inner_product` | | 92 | [
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SQL | Functions | List Functions | `list_negative_dot_product(list1, list2)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Computes the negative dot product of two same-sized lists of numbers. Equivalent to `- list_dot_product` |
| **Example** | `list_negative_dot_product([1, 2, 3], [1, 2, 5])` |
| **Result** | `-20.0` |
| **Alias** | `list_negative_inner_product` | | 102 | [
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SQL | Functions | List Functions | `list_extract(list, index)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Extract the `index`th (1-based) value from the list. |
| **Example** | `list_extract([4, 5, 6], 3)` |
| **Result** | `6` |
| **Aliases** | `list_element`, `array_extract` | | 87 | [
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SQL | Functions | List Functions | `list_filter(list, lambda)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Constructs a list from those elements of the input list for which the lambda function returns true. See the [Lambda Functions](#docs:sql:functions:lambda::filter) page for more details. |
| **Example** | `list_filter([4, 5, 6], x -> x > 4)` |
| **Result** | `[5, 6]` |
| **Aliases** | `array_filter`, `filter` | | 120 | [
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SQL | Functions | List Functions | `list_grade_up(list)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Works like sort, but the results are the indexes that correspond to the position in the original `list` instead of the actual values. |
| **Example** | `list_grade_up([30, 10, 40, 20])` |
| **Result** | `[2, 4, 1, 3]` |
| **Alias** | `array_grade_up` | | 108 | [
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SQL | Functions | List Functions | `list_has_all(list, sub-list)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Returns true if all elements of sub-list exist in list. |
| **Example** | `list_has_all([4, 5, 6], [4, 6])` |
| **Result** | `true` |
| **Alias** | `array_has_all` | | 86 | [
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SQL | Functions | List Functions | `list_has_any(list1, list2)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Returns true if any elements exist is both lists. |
| **Example** | `list_has_any([1, 2, 3], [2, 3, 4])` |
| **Result** | `true` |
| **Alias** | `array_has_any` | | 87 | [
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SQL | Functions | List Functions | `list_intersect(list1, list2)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Returns a list of all the elements that exist in both `l1` and `l2`, without duplicates. |
| **Example** | `list_intersect([1, 2, 3], [2, 3, 4])` |
| **Result** | `[2, 3]` |
| **Alias** | `array_intersect` | | 102 | [
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SQL | Functions | List Functions | `list_position(list, element)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Returns the index of the element if the list contains the element. If the element is not found, it returns `NULL`. |
| **Example** | `list_position([1, 2, NULL], 2)` |
| **Result** | `2` |
| **Aliases** | `list_indexof`, `array_position`, `array_indexof` | | 102 | [
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SQL | Functions | List Functions | `list_prepend(element, list)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Prepends `element` to `list`. |
| **Example** | `list_prepend(3, [4, 5, 6])` |
| **Result** | `[3, 4, 5, 6]` |
| **Aliases** | `array_prepend`, `array_push_front` | | 96 | [
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SQL | Functions | List Functions | `list_reduce(list, lambda)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Returns a single value that is the result of applying the lambda function to each element of the input list. See the [Lambda Functions](#docs:sql:functions:lambda::reduce) page for more details. |
| **Example** | `list_reduce([4, 5, 6], (x, y) -> x + y)` |
| **Result** | `15` |
| **Aliases** | `array_reduce`, `reduce` | | 121 | [
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SQL | Functions | List Functions | `list_resize(list, size[, value])` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Resizes the list to contain `size` elements. Initializes new elements with `value` or `NULL` if `value` is not set. |
| **Example** | `list_resize([1, 2, 3], 5, 0)` |
| **Result** | `[1, 2, 3, 0, 0]` |
| **Alias** | `array_resize` | | 114 | [
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SQL | Functions | List Functions | `list_reverse_sort(list)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Sorts the elements of the list in reverse order. See the [Sorting Lists](#docs:sql:functions:list::sorting-lists) section for more details about the `NULL` sorting order. |
| **Example** | `list_reverse_sort([3, 6, 1, 2])` |
| **Result** | `[6, 3, 2, 1]` |
| **Alias** | `array_reverse_sort` | | 122 | [
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] |
SQL | Functions | List Functions | `list_reverse(list)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Reverses the list. |
| **Example** | `list_reverse([3, 6, 1, 2])` |
| **Result** | `[2, 1, 6, 3]` |
| **Alias** | `array_reverse` | | 85 | [
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SQL | Functions | List Functions | `list_select(value_list, index_list)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Returns a list based on the elements selected by the `index_list`. |
| **Example** | `list_select([10, 20, 30, 40], [1, 4])` |
| **Result** | `[10, 40]` |
| **Alias** | `array_select` | | 93 | [
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SQL | Functions | List Functions | `list_slice(list, begin, end, step)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |`list_slice` with added `step` feature. |
| **Example** | `list_slice([4, 5, 6], 1, 3, 2)` |
| **Result** | `[4, 6]` |
| **Alias** | `array_slice` | | 89 | [
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SQL | Functions | List Functions | `list_slice(list, begin, end)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Extract a sublist using slice conventions. Negative values are accepted. See [slicing](#docs:sql:functions:list::slicing). |
| **Example** | `list_slice([4, 5, 6], 2, 3)` |
| **Result** | `[5, 6]` |
| **Alias** | `array_slice` | | 103 | [
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SQL | Functions | List Functions | `list_sort(list)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Sorts the elements of the list. See the [Sorting Lists](#docs:sql:functions:list::sorting-lists) section for more details about the sorting order and the `NULL` sorting order. |
| **Example** | `list_sort([3, 6, 1, 2])` |
| **Result** | `[1, 2, 3, 6]` |
| **Alias** | `array_sort` | | 121 | [
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SQL | Functions | List Functions | `list_transform(list, lambda)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Returns a list that is the result of applying the lambda function to each element of the input list. See the [Lambda Functions](#docs:sql:functions:lambda::transform) page for more details. |
| **Example** | `list_transform([4, 5, 6], x -> x + 1)` |
| **Result** | `[5, 6, 7]` |
| **Aliases** | `array_transform`, `apply`, `list_apply`, `array_apply` | | 132 | [
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SQL | Functions | List Functions | `list_unique(list)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Counts the unique elements of a list. |
| **Example** | `list_unique([1, 1, NULL, -3, 1, 5])` |
| **Result** | `3` |
| **Alias** | `array_unique` | | 82 | [
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SQL | Functions | List Functions | `list_value(any, ...)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Create a `LIST` containing the argument values. |
| **Example** | `list_value(4, 5, 6)` |
| **Result** | `[4, 5, 6]` |
| **Alias** | `list_pack` | | 82 | [
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SQL | Functions | List Functions | `list_where(value_list, mask_list)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Returns a list with the `BOOLEAN`s in `mask_list` applied as a mask to the `value_list`. |
| **Example** | `list_where([10, 20, 30, 40], [true, false, false, true])` |
| **Result** | `[10, 40]` |
| **Alias** | `array_where` | | 105 | [
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SQL | Functions | List Functions | `list_zip(list1, list2, ...)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Zips _k_ `LIST`s to a new `LIST` whose length will be that of the longest list. Its elements are structs of _k_ elements from each list `list_1`, ..., `list_k`, missing elements are replaced with `NULL`. If `truncate` is set, all lists are truncated to the smallest list length. |
| **Example** | `list_zip([1, 2], [3, 4], [5, 6])` |
| **Result** | `[(1, 3, 5), (2, 4, 6)]` |
| **Alias** | `array_zip` | | 163 | [
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SQL | Functions | List Functions | `unnest(list)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Unnests a list by one level. Note that this is a special function that alters the cardinality of the result. See the [`unnest` page](#docs:sql:query_syntax:unnest) for more details. |
| **Example** | `unnest([1, 2, 3])` |
| **Result** | `1`, `2`, `3` | | 110 | [
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SQL | Functions | List Operators | The following operators are supported for lists:
<!-- markdownlint-disable MD056 -->
| Operator | Description | Example | Result |
|-|--|---|-|
| `&&` | Alias for [`list_has_any`](#::list_has_anylist1-list2). | `[1, 2, 3, 4, 5] && [2, 5, 5, 6]` | `true` |
| `@>` | Alias for [`list_has_all`](#::list_has_alllist-sub-list), where the list on the **right** of the operator is the sublist. | `[1, 2, 3, 4] @> [3, 4, 3]` | `true` |
| `<@` | Alias for [`list_has_all`](#::list_has_alllist-sub-list), where the list on the **left** of the operator is the sublist. | `[1, 4] <@ [1, 2, 3, 4]` | `true` |
| `||` | Similar to [`list_concat`](#::list_concatlist1-list2), except any `NULL` input results in `NULL`. | `[1, 2, 3] || [4, 5, 6]` | `[1, 2, 3, 4, 5, 6]` |
| `<=>` | Alias for [`list_cosine_distance`](#::list_cosine_distancelist1-list2). | `[1, 2, 3] <=> [1, 2, 5]` | `0.007416606` |
| `<->` | Alias for [`list_distance`](#::list_distancelist1-list2). | `[1, 2, 3] <-> [1, 2, 5]` | `2.0` |
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|
SQL | Functions | List Comprehension | Python-style list comprehension can be used to compute expressions over elements in a list. For example:
```sql
SELECT [lower(x) FOR x IN strings] AS strings
FROM (VALUES (['Hello', '', 'World'])) t(strings);
```
<div class="narrow_table monospace_table"></div>
| strings |
|------------------|
| [hello, , world] |
```sql
SELECT [upper(x) FOR x IN strings IF len(x) > 0] AS strings
FROM (VALUES (['Hello', '', 'World'])) t(strings);
```
<div class="narrow_table monospace_table"></div>
| strings |
|----------------|
| [HELLO, WORLD] |
List comprehensions can also use the position of the list elements by adding a second variable.
In the following example, we use `x, i`, where `x` is the value and `i` is the position:
```sql
SELECT [4, 5, 6] AS l, [x FOR x, i IN l IF i != 2] filtered;
```
<div class="narrow_table monospace_table"></div>
| l | filtered |
|-----------|----------|
| [4, 5, 6] | [4, 6] | | 276 | [
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|
SQL | Functions | Range Functions | DuckDB offers two range functions, [`range(start, stop, step)`](#::range) and [`generate_series(start, stop, step)`](#::generate_series), and their variants with default arguments for `stop` and `step`. The two functions' behavior is different regarding their `stop` argument. This is documented below.
#### `range` {#docs:sql:functions:list::range}
The `range` function creates a list of values in the range between `start` and `stop`.
The `start` parameter is inclusive, while the `stop` parameter is exclusive.
The default value of `start` is 0 and the default value of `step` is 1.
Based on the number of arguments, the following variants of `range` exist. | 164 | [
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] |
|
SQL | Functions | Range Functions | `range(stop)` | ```sql
SELECT range(5);
```
```text
[0, 1, 2, 3, 4]
``` | 29 | [
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] |
SQL | Functions | Range Functions | `range(start, stop)` | ```sql
SELECT range(2, 5);
```
```text
[2, 3, 4]
``` | 26 | [
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SQL | Functions | Range Functions | `range(start, stop, step)` | ```sql
SELECT range(2, 5, 3);
```
```text
[2]
```
#### `generate_series` {#docs:sql:functions:list::generate_series}
The `generate_series` function creates a list of values in the range between `start` and `stop`.
Both the `start` and the `stop` parameters are inclusive.
The default value of `start` is 0 and the default value of `step` is 1.
Based on the number of arguments, the following variants of `generate_series` exist. | 117 | [
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] |
SQL | Functions | Range Functions | `generate_series(stop)` | ```sql
SELECT generate_series(5);
```
```text
[0, 1, 2, 3, 4, 5]
``` | 33 | [
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] |
SQL | Functions | Range Functions | `generate_series(start, stop)` | ```sql
SELECT generate_series(2, 5);
```
```text
[2, 3, 4, 5]
``` | 30 | [
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] |
SQL | Functions | Range Functions | `generate_series(start, stop, step)` | ```sql
SELECT generate_series(2, 5, 3);
```
```text
[2, 5]
``` | 27 | [
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SQL | Functions | Range Functions | `generate_subscripts(arr, dim)` | The `generate_subscripts(arr, dim)` function generates indexes along the `dim`th dimension of array `arr`.
```sql
SELECT generate_subscripts([4, 5, 6], 1) AS i;
```
| i |
|--:|
| 1 |
| 2 |
| 3 |
#### Date Ranges {#docs:sql:functions:list::date-ranges}
Date ranges are also supported for `TIMESTAMP` and `TIMESTAMP WITH TIME ZONE` values.
Note that for these types, the `stop` and `step` arguments have to be specified explicitly (a default value is not provided). | 135 | [
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] |
SQL | Functions | Range Functions | `range` for Date Ranges | ```sql
SELECT *
FROM range(DATE '1992-01-01', DATE '1992-03-01', INTERVAL '1' MONTH);
```
| range |
|---------------------|
| 1992-01-01 00:00:00 |
| 1992-02-01 00:00:00 | | 73 | [
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] |
SQL | Functions | Range Functions | `generate_series` for Date Ranges | ```sql
SELECT *
FROM generate_series(DATE '1992-01-01', DATE '1992-03-01', INTERVAL '1' MONTH);
```
| generate_series |
|---------------------|
| 1992-01-01 00:00:00 |
| 1992-02-01 00:00:00 |
| 1992-03-01 00:00:00 | | 90 | [
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SQL | Functions | Slicing | The function [`list_slice`](#::list_slicelist-begin-end) can be used to extract a sublist from a list. The following variants exist:
* `list_slice(list, begin, end)`
* `list_slice(list, begin, end, step)`
* `array_slice(list, begin, end)`
* `array_slice(list, begin, end, step)`
* `list[begin:end]`
* `list[begin:end:step]`
The arguments are as follows:
* `list`
* Is the list to be sliced
* `begin`
* Is the index of the first element to be included in the slice
* When `begin < 0` the index is counted from the end of the list
* When `begin < 0` and `-begin > length`, `begin` is clamped to the beginning of the list
* When `begin > length`, the result is an empty list
* **Bracket Notation:** When `begin` is omitted, it defaults to the beginning of the list
* `end`
* Is the index of the last element to be included in the slice
* When `end < 0` the index is counted from the end of the list
* When `end > length`, end is clamped to `length`
* When `end < begin`, the result is an empty list
* **Bracket Notation:** When `end` is omitted, it defaults to the end of the list. When `end` is omitted and a `step` is provided, `end` must be replaced with a `-`
* `step` *(optional)*
* Is the step size between elements in the slice
* When `step < 0` the slice is reversed, and `begin` and `end` are swapped
* Must be non-zero
Examples:
```sql
SELECT list_slice([1, 2, 3, 4, 5], 2, 4);
```
```text
[2, 3, 4]
```
```sql
SELECT ([1, 2, 3, 4, 5])[2:4:2];
```
```text
[2, 4]
```
```sql
SELECT([1, 2, 3, 4, 5])[4:2:-2];
```
```text
[4, 2]
```
```sql
SELECT ([1, 2, 3, 4, 5])[:];
```
```text
[1, 2, 3, 4, 5]
```
```sql
SELECT ([1, 2, 3, 4, 5])[:-:2];
```
```text
[1, 3, 5]
```
```sql
SELECT ([1, 2, 3, 4, 5])[:-:-2];
```
```text
[5, 3, 1]
``` | 620 | [
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|
SQL | Functions | List Aggregates | The function [`list_aggregate`](#::list_aggregatelist-name) allows the execution of arbitrary existing aggregate functions on the elements of a list. Its first argument is the list (column), its second argument is the aggregate function name, e.g., `min`, `histogram` or `sum`.
`list_aggregate` accepts additional arguments after the aggregate function name. These extra arguments are passed directly to the aggregate function, which serves as the second argument of `list_aggregate`.
```sql
SELECT list_aggregate([1, 2, -4, NULL], 'min');
```
```text
-4
```
```sql
SELECT list_aggregate([2, 4, 8, 42], 'sum');
```
```text
56
```
```sql
SELECT list_aggregate([[1, 2], [NULL], [2, 10, 3]], 'last');
```
```text
[2, 10, 3]
```
```sql
SELECT list_aggregate([2, 4, 8, 42], 'string_agg', '|');
```
```text
2|4|8|42
```
#### `list_*` Rewrite Functions {#docs:sql:functions:list::list_-rewrite-functions}
The following is a list of existing rewrites. Rewrites simplify the use of the list aggregate function by only taking the list (column) as their argument. `list_avg`, `list_var_samp`, `list_var_pop`, `list_stddev_pop`, `list_stddev_samp`, `list_sem`, `list_approx_count_distinct`, `list_bit_xor`, `list_bit_or`, `list_bit_and`, `list_bool_and`, `list_bool_or`, `list_count`, `list_entropy`, `list_last`, `list_first`, `list_kurtosis`, `list_kurtosis_pop`, `list_min`, `list_max`, `list_product`, `list_skewness`, `list_sum`, `list_string_agg`, `list_mode`, `list_median`, `list_mad` and `list_histogram`.
```sql
SELECT list_min([1, 2, -4, NULL]);
```
```text
-4
```
```sql
SELECT list_sum([2, 4, 8, 42]);
```
```text
56
```
```sql
SELECT list_last([[1, 2], [NULL], [2, 10, 3]]);
```
```text
[2, 10, 3]
``` | 534 | [
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|
SQL | Functions | List Aggregates | `array_to_string` | Concatenates list/array elements using an optional delimiter.
```sql
SELECT array_to_string([1, 2, 3], '-') AS str;
```
```text
1-2-3
```
This is equivalent to the following SQL:
```sql
SELECT list_aggr([1, 2, 3], 'string_agg', '-') AS str;
```
```text
1-2-3
``` | 90 | [
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SQL | Functions | Sorting Lists | The function `list_sort` sorts the elements of a list either in ascending or descending order.
In addition, it allows to provide whether `NULL` values should be moved to the beginning or to the end of the list.
It has the same sorting behavior as DuckDB's `ORDER BY` clause.
Therefore, (nested) values compare the same in `list_sort` as in `ORDER BY`.
By default, if no modifiers are provided, DuckDB sorts `ASC NULLS FIRST`.
I.e., the values are sorted in ascending order and `NULL` values are placed first.
This is identical to the default sort order of SQLite.
The default sort order can be changed using [`PRAGMA` statements.](#..:query_syntax:orderby).
`list_sort` leaves it open to the user whether they want to use the default sort order or a custom order.
`list_sort` takes up to two additional optional parameters.
The second parameter provides the sort order and can be either `ASC` or `DESC`.
The third parameter provides the `NULL` order and can be either `NULLS FIRST` or `NULLS LAST`.
This query uses the default sort order and the default `NULL` order.
```sql
SELECT list_sort([1, 3, NULL, 5, NULL, -5]);
```
```sql
[NULL, NULL, -5, 1, 3, 5]
```
This query provides the sort order.
The `NULL` order uses the configurable default value.
```sql
SELECT list_sort([1, 3, NULL, 2], 'ASC');
```
```sql
[NULL, 1, 2, 3]
```
This query provides both the sort order and the `NULL` order.
```sql
SELECT list_sort([1, 3, NULL, 2], 'DESC', 'NULLS FIRST');
```
```sql
[NULL, 3, 2, 1]
```
`list_reverse_sort` has an optional second parameter providing the `NULL` sort order.
It can be either `NULLS FIRST` or `NULLS LAST`.
This query uses the default `NULL` sort order.
```sql
SELECT list_sort([1, 3, NULL, 5, NULL, -5]);
```
```sql
[NULL, NULL, -5, 1, 3, 5]
```
This query provides the `NULL` sort order.
```sql
SELECT list_reverse_sort([1, 3, NULL, 2], 'NULLS LAST');
```
```sql
[3, 2, 1, NULL]
``` | 554 | [
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|
SQL | Functions | Flattening | The flatten function is a scalar function that converts a list of lists into a single list by concatenating each sub-list together.
Note that this only flattens one level at a time, not all levels of sub-lists.
Convert a list of lists into a single list:
```sql
SELECT
flatten([
[1, 2],
[3, 4]
]);
```
```text
[1, 2, 3, 4]
```
If the list has multiple levels of lists, only the first level of sub-lists is concatenated into a single list:
```sql
SELECT
flatten([
[
[1, 2],
[3, 4],
],
[
[5, 6],
[7, 8],
]
]);
```
```text
[[1, 2], [3, 4], [5, 6], [7, 8]]
```
In general, the input to the flatten function should be a list of lists (not a single level list).
However, the behavior of the flatten function has specific behavior when handling empty lists and `NULL` values.
If the input list is empty, return an empty list:
```sql
SELECT flatten([]);
```
```text
[]
```
If the entire input to flatten is `NULL`, return `NULL`:
```sql
SELECT flatten(NULL);
```
```text
NULL
```
If a list whose only entry is `NULL` is flattened, return an empty list:
```sql
SELECT flatten([NULL]);
```
```text
[]
```
If the sub-list in a list of lists only contains `NULL`, do not modify the sub-list:
```sql
-- (Note the extra set of parentheses vs. the prior example)
SELECT flatten([[NULL]]);
```
```text
[NULL]
```
Even if the only contents of each sub-list is `NULL`, still concatenate them together. Note that no de-duplication occurs when flattening. See `list_distinct` function for de-duplication:
```sql
SELECT flatten([[NULL],[NULL]]);
```
```text
[NULL, NULL]
``` | 444 | [
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|
SQL | Functions | Lambda Functions | DuckDB supports lambda functions in the form `(parameter1, parameter2, ...) -> expression`.
For details, see the [lambda functions page](#docs:sql:functions:lambda). | 39 | [
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|
SQL | Functions | Related Functions | There are also [aggregate functions](#docs:sql:functions:aggregates) `list` and `histogram` that produces lists and lists of structs.
The [`unnest`](#docs:sql:query_syntax:unnest) function is used to unnest a list by one level. | 62 | [
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|
SQL | Functions | Map Functions | <!-- markdownlint-disable MD001 -->
| Name | Description |
|:--|:-------|
| [`cardinality(map)`](#::cardinalitymap) | Return the size of the map (or the number of entries in the map). |
| [`element_at(map, key)`](#::element_atmap-key) | Return a list containing the value for a given key or an empty list if the key is not contained in the map. The type of the key provided in the second parameter must match the type of the map's keys else an error is returned. |
| [`map_contains(map, key)`](#::map_containsmap-key) | Checks if a map contains a given key. |
| [`map_contains_entry(map, key, value)`](#::map_contains_entrymap-key-value) | Check if a map contains a given key-value pair. |
| [`map_contains_value(map, value)`](#::map_contains_valuemap-value) | Checks if a map contains a given value. |
| [`map_entries(map)`](#::map_entriesmap) | Return a list of struct(k, v) for each key-value pair in the map. |
| [`map_extract(map, key)`](#::map_extractmap-key) | Alias of `element_at`. Return a list containing the value for a given key or an empty list if the key is not contained in the map. The type of the key provided in the second parameter must match the type of the map's keys else an error is returned. |
| [`map_from_entries(STRUCT(k, v)[])`](#map_from_entriesstructk-v) | Returns a map created from the entries of the array. |
| [`map_keys(map)`](#::map_keysmap) | Return a list of all keys in the map. |
| [`map_values(map)`](#::map_valuesmap) | Return a list of all values in the map. |
| [`map()`](#::map) | Returns an empty map. |
| [`map[entry]`](#mapentry) | Alias for `element_at`. | | 434 | [
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|
SQL | Functions | Map Functions | `cardinality(map)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Return the size of the map (or the number of entries in the map). |
| **Example** | `cardinality(map([4, 2], ['a', 'b']))` |
| **Result** | `2` | | 76 | [
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SQL | Functions | Map Functions | `element_at(map, key)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Return a list containing the value for a given key or an empty list if the key is not contained in the map. The type of the key provided in the second parameter must match the type of the map's keys else an error is returned. |
| **Example** | `element_at(map([100, 5], [42, 43]), 100)` |
| **Result** | `[42]` | | 112 | [
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SQL | Functions | Map Functions | `map_contains(map, key)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Checks if a map contains a given key. |
| **Example** | `map_contains(MAP {'key1': 10, 'key2': 20, 'key3': 30}, 'key2')` |
| **Result** | `true` | | 83 | [
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SQL | Functions | Map Functions | `map_contains_entry(map, key, value)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Check if a map contains a given key-value pair. |
| **Example** | `map_contains_entry(MAP {'key1': 10, 'key2': 20, 'key3': 30}, 'key2', 20)` |
| **Result** | `true` | | 88 | [
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SQL | Functions | Map Functions | `map_contains_value(map, value)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Checks if a map contains a given value. |
| **Example** | `map_contains_value(MAP {'key1': 10, 'key2': 20, 'key3': 30}, 20)` |
| **Result** | `true` | | 82 | [
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SQL | Functions | Map Functions | `map_entries(map)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Return a list of struct(k, v) for each key-value pair in the map. |
| **Example** | `map_entries(map([100, 5], [42, 43]))` |
| **Result** | `[{'key': 100, 'value': 42}, {'key': 5, 'value': 43}]` | | 101 | [
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] |
SQL | Functions | Map Functions | `map_extract(map, key)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Alias of `element_at`. Return a list containing the value for a given key or an empty list if the key is not contained in the map. The type of the key provided in the second parameter must match the type of the map's keys else an error is returned. |
| **Example** | `map_extract(map([100, 5], [42, 43]), 100)` |
| **Result** | `[42]` | | 118 | [
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SQL | Functions | Map Functions | `map_from_entries(STRUCT(k, v)[])` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Returns a map created from the entries of the array. |
| **Example** | `map_from_entries([{k: 5, v: 'val1'}, {k: 3, v: 'val2'}])` |
| **Result** | `{5=val1, 3=val2}` | | 91 | [
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SQL | Functions | Map Functions | `map_keys(map)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Return a list of all keys in the map. |
| **Example** | `map_keys(map([100, 5], [42,43]))` |
| **Result** | `[100, 5]` | | 73 | [
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SQL | Functions | Map Functions | `map_values(map)` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Return a list of all values in the map. |
| **Example** | `map_values(map([100, 5], [42, 43]))` |
| **Result** | `[42, 43]` | | 74 | [
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SQL | Functions | Map Functions | `map()` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Returns an empty map. |
| **Example** | `map()` |
| **Result** | `{}` | | 50 | [
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] |
SQL | Functions | Map Functions | `map[entry]` | <div class="nostroke_table"></div>
| | |
|:--|:--------|
| **Description** |Alias for `element_at`. |
| **Example** | `map([100, 5], ['a', 'b'])[100]` |
| **Result** | `[a]` | | 67 | [
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SQL | Functions | Nested Functions | There are five [nested data types](#docs:sql:data_types:overview::nested--composite-types):
| Name | Type page | Functions page |
|--|---|---|
| `ARRAY` | [`ARRAY` type](#docs:sql:data_types:array) | [`ARRAY` functions](#docs:sql:functions:array) |
| `LIST` | [`LIST` type](#docs:sql:data_types:list) | [`LIST` functions](#docs:sql:functions:list) |
| `MAP` | [`MAP` type](#docs:sql:data_types:map) | [`MAP` functions](#docs:sql:functions:map) |
| `STRUCT` | [`STRUCT` type](#docs:sql:data_types:struct) | [`STRUCT` functions](#docs:sql:functions:struct) |
| `UNION` | [`UNION` type](#docs:sql:data_types:union) | [`UNION` functions](#docs:sql:functions:union) | | 226 | [
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|
SQL | Functions | Numeric Functions | <!-- markdownlint-disable MD001 --> | 7 | [
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|
SQL | Functions | Numeric Operators | The table below shows the available mathematical operators for [numeric types](#docs:sql:data_types:numeric).
<div class="narrow_table"></div>
<!-- markdownlint-disable MD056 -->
| Operator | Description | Example | Result |
|-|-----|--|-|
| `+` | addition | `2 + 3` | `5` |
| `-` | subtraction | `2 - 3` | `-1` |
| `*` | multiplication | `2 * 3` | `6` |
| `/` | float division | `5 / 2` | `2.5` |
| `//` | division | `5 // 2` | `2` |
| `%` | modulo (remainder) | `5 % 4` | `1` |
| `**` | exponent | `3 ** 4` | `81` |
| `^` | exponent (alias for `**`) | `3 ^ 4` | `81` |
| `&` | bitwise AND | `91 & 15` | `11` |
| `|` | bitwise OR | `32 | 3` | `35` |
| `<<` | bitwise shift left | `1 << 4` | `16` |
| `>>` | bitwise shift right | `8 >> 2` | `2` |
| `~` | bitwise negation | `~15` | `-16` |
| `!` | factorial of `x` | `4!` | `24` |
<!-- markdownlint-enable MD056 -->
#### Division and Modulo Operators {#docs:sql:functions:numeric::division-and-modulo-operators}
There are two division operators: `/` and `//`.
They are equivalent when at least one of the operands is a `FLOAT` or a `DOUBLE`.
When both operands are integers, `/` performs floating points division (` 5 / 2 = 2.5`) while `//` performs integer division (` 5 // 2 = 2`).
#### Supported Types {#docs:sql:functions:numeric::supported-types}
The modulo, bitwise, and negation and factorial operators work only on integral data types,
whereas the others are available for all numeric data types. | 531 | [
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Subsets and Splits