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SQL | DuckDB's SQL Dialect | Trailing Commas | DuckDB allows [trailing commas](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Trailing_commas),
both when listing entities (e.g., column and table names) and when constructing [`LIST` items](#docs:sql:data_types:list::creating-lists).
For example, the following query works:
```sql
SELECT
42 AS x,
['a', 'b', 'c',] AS y,
'hello world' AS z,
;
``` | 101 | [
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|
SQL | DuckDB's SQL Dialect | "Top-N in Group" Queries | Computing the "top-N rows in a group" ordered by some criteria is a common task in SQL that unfortunately often requires a complex query involving window functions and/or subqueries.
To aid in this, DuckDB provides the aggregate functions [`max(arg, n)`](#docs:sql:functions:aggregates::maxarg-n), [`min(arg, n)`](#docs:sql:functions:aggregates::minarg-n), [`arg_max(arg, val, n)`](#docs:sql:functions:aggregates::arg_maxarg-val-n), [`arg_min(arg, val, n)`](#docs:sql:functions:aggregates::arg_minarg-val-n), [`max_by(arg, val, n)`](#docs:sql:functions:aggregates::max_byarg-val-n) and [`min_by(arg, val, n)`](#docs:sql:functions:aggregates::min_byarg-val-n) to efficiently return the "top" `n` rows in a group based on a specific column in either ascending or descending order.
For example, let's use the following table:
```sql
SELECT * FROM t1;
```
```text
βββββββββββ¬ββββββββ
β grp β val β
β varchar β int32 β
βββββββββββΌββββββββ€
β a β 2 β
β a β 1 β
β b β 5 β
β b β 4 β
β a β 3 β
β b β 6 β
βββββββββββ΄ββββββββ
```
We want to get a list of the top-3 `val` values in each group `grp`. The conventional way to do this is to use a window function in a subquery:
```sql
SELECT array_agg(rs.val), rs.grp
FROM
(SELECT val, grp, row_number() OVER (PARTITION BY grp ORDER BY val DESC) AS rid
FROM t1 ORDER BY val DESC) AS rs
WHERE rid < 4
GROUP BY rs.grp;
```
```text
βββββββββββββββββββββ¬ββββββββββ
β array_agg(rs.val) β grp β
β int32[] β varchar β
βββββββββββββββββββββΌββββββββββ€
β [3, 2, 1] β a β
β [6, 5, 4] β b β
βββββββββββββββββββββ΄ββββββββββ
```
But in DuckDB, we can do this much more concisely (and efficiently!):
```sql
SELECT max(val, 3) FROM t1 GROUP BY grp;
```
```text
βββββββββββββββ
β max(val, 3) β
β int32[] β
βββββββββββββββ€
β [3, 2, 1] β
β [6, 5, 4] β
βββββββββββββββ
``` | 669 | [
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|
SQL | DuckDB's SQL Dialect | Related Blog Posts | * [βFriendlier SQL with DuckDBβ](https://duckdb.org/2022/05/04/friendlier-sql) blog post
* [βEven Friendlier SQL with DuckDBβ](https://duckdb.org/2023/08/23/even-friendlier-sql) blog post
* [βSQL Gymnastics: Bending SQL into Flexible New Shapesβ](https://duckdb.org/2024/03/01/sql-gymnastics) blog post | 104 | [
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|
SQL | DuckDB's SQL Dialect | Identifiers | Similarly to other SQL dialects and programming languages, identifiers in DuckDB's SQL are subject to several rules.
* Unquoted identifiers need to conform to a number of rules:
* They must not be a reserved keyword (see [`duckdb_keywords()`](#docs:sql:meta:duckdb_table_functions::duckdb_keywords)), e.g., `SELECT 123 AS SELECT` will fail.
* They must not start with a number or special character, e.g., `SELECT 123 AS 1col` is invalid.
* They cannot contain whitespaces (including tabs and newline characters).
* Identifiers can be quoted using double-quote characters (` "`). Quoted identifiers can use any keyword, whitespace or special character, e.g., `"SELECT"` and `" Β§ π¦ ΒΆ "` are valid identifiers.
* Double quotes can be escaped by repeating the quote character, e.g., to create an identifier named `IDENTIFIER "X"`, use `"IDENTIFIER ""X"""`.
#### Deduplicating Identifiers {#docs:sql:dialect:keywords_and_identifiers::deduplicating-identifiers}
In some cases, duplicate identifiers can occur, e.g., column names may conflict when unnesting a nested data structure.
In these cases, DuckDB automatically deduplicates column names by renaming them according to the following rules:
* For a column named `β¨nameβ©`, the first instance is not renamed.
* Subsequent instances are renamed to `β¨nameβ©_β¨countβ©`, where `β¨countβ©` starts at 1.
For example:
```sql
SELECT *
FROM (SELECT UNNEST({'a': 42, 'b': {'a': 88, 'b': 99}}, recursive := true));
```
| a | a_1 | b |
|---:|----:|---:|
| 42 | 88 | 99 | | 397 | [
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|
SQL | DuckDB's SQL Dialect | Database Names | Database names are subject to the rules for [identifiers](#::identifiers).
Additionally, it is best practice to avoid DuckDB's two internal [database schema names](#docs:sql:meta:duckdb_table_functions::duckdb_databases), `system` and `temp`.
By default, persistent databases are named after their filename without the extension.
Therefore, the filenames `system.db` and `temp.db` (as well as `system.duckdb` and `temp.duckdb`) result in the database names `system` and `temp`, respectively.
If you need to attach to a database that has one of these names, use an alias, e.g.:
```sql
ATTACH 'temp.db' AS temp2;
USE temp2;
``` | 159 | [
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|
SQL | DuckDB's SQL Dialect | Rules for Case-Sensitivity | #### Keywords and Function Names {#docs:sql:dialect:keywords_and_identifiers::keywords-and-function-names}
SQL keywords and function names are case-insensitive in DuckDB.
For example, the following two queries are equivalent:
```matlab
select COS(Pi()) as CosineOfPi;
SELECT cos(pi()) AS CosineOfPi;
```
| CosineOfPi |
|-----------:|
| -1.0 |
#### Case-Sensitivity of Identifiers {#docs:sql:dialect:keywords_and_identifiers::case-sensitivity-of-identifiers}
Identifiers in DuckDB are always case-insensitive, similarly to PostgreSQL.
However, unlike PostgreSQL (and some other major SQL implementations), DuckDB also treats quoted identifiers as case-insensitive.
Despite treating identifiers in a case-insensitive manner, each character's case (uppercase/lowercase) is maintained as originally specified by the user even if a query uses different cases when referring to the identifier.
For example:
```sql
CREATE TABLE tbl AS SELECT cos(pi()) AS CosineOfPi;
SELECT cosineofpi FROM tbl;
```
| CosineOfPi |
|-----------:|
| -1.0 |
To change this behavior, set the `preserve_identifier_case` [configuration option](#docs:configuration:overview::configuration-reference) to `false`. | 283 | [
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|
SQL | DuckDB's SQL Dialect | Rules for Case-Sensitivity | Handling Conflicts | In case of a conflict, when the same identifier is spelt with different cases, one will be selected randomly. For example:
```sql
CREATE TABLE t1 (idfield INTEGER, x INTEGER);
CREATE TABLE t2 (IdField INTEGER, y INTEGER);
INSERT INTO t1 VALUES (1, 123);
INSERT INTO t2 VALUES (1, 456);
SELECT * FROM t1 NATURAL JOIN t2;
```
| idfield | x | y |
|--------:|----:|----:|
| 1 | 123 | 456 | | 122 | [
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SQL | DuckDB's SQL Dialect | Rules for Case-Sensitivity | Disabling Preserving Cases | With the `preserve_identifier_case` [configuration option](#docs:configuration:overview::configuration-reference) set to `false`, all identifiers are turned into lowercase:
```sql
SET preserve_identifier_case = false;
CREATE TABLE tbl AS SELECT cos(pi()) AS CosineOfPi;
SELECT CosineOfPi FROM tbl;
```
| cosineofpi |
|-----------:|
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SQL | DuckDB's SQL Dialect | Order Preservation | For many operations, DuckDB preserves the insertion order of rows, similarly to data frame libraries such as Pandas.
The following operations and components respect insertion order:
* [The CSV reader](#docs:data:csv:overview::order-preservation)
Preservation of insertion order is controlled by the `preserve_insertion_order` [configuration option](#docs:configuration:overview).
This setting is `true` by default, indicating that the order should be preserved.
To change this setting, use:
```sql
SET preserve_insertion_order = false;
``` | 116 | [
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SQL | DuckDB's SQL Dialect | PostgreSQL Compatibility | DuckDB's SQL dialect closely follows the conventions of the PostgreSQL dialect.
The few exceptions to this are listed on this page. | 26 | [
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|
SQL | DuckDB's SQL Dialect | Floating-Point Arithmetic | DuckDB and PostgreSQL handle floating-point arithmetic differently for division by zero. DuckDB conforms to the [IEEE Standard for Floating-Point Arithmetic (IEEE 754)](https://en.wikipedia.org/wiki/IEEE_754) for both division by zero and operations involving infinity values. PostgreSQL returns an error for division by zero but aligns with IEEE 754 for handling infinity values. To show the differences, run the following SQL queries:
```sql
SELECT 1.0 / 0.0 AS x;
SELECT 0.0 / 0.0 AS x;
SELECT -1.0 / 0.0 AS x;
SELECT 'Infinity'::FLOAT / 'Infinity'::FLOAT AS x;
SELECT 1.0 / 'Infinity'::FLOAT AS x;
SELECT 'Infinity'::FLOAT - 'Infinity'::FLOAT AS x;
SELECT 'Infinity'::FLOAT - 1.0 AS x;
```
<div class="narrow_table monospace_table"></div>
| Expression | PostgreSQL | DuckDB | IEEE 754 |
| :---------------------- | ---------: | --------: | --------: |
| 1.0 / 0.0 | error | Infinity | Infinity |
| 0.0 / 0.0 | error | NaN | NaN |
| -1.0 / 0.0 | error | -Infinity | -Infinity |
| 'Infinity' / 'Infinity' | NaN | NaN | NaN |
| 1.0 / 'Infinity' | 0.0 | 0.0 | 0.0 |
| 'Infinity' - 'Infinity' | NaN | NaN | NaN |
| 'Infinity' - 1.0 | Infinity | Infinity | Infinity | | 380 | [
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|
SQL | DuckDB's SQL Dialect | Division on Integers | When computing division on integers, PostgreSQL performs integer division, while DuckDB performs float division:
```sql
SELECT 1 / 2 AS x;
```
PostgreSQL returns:
```text
x
0
(1 row)
```
DuckDB returns:
| x |
| ---: |
| 0.5 |
To perform integer division in DuckDB, use the `//` operator:
```sql
SELECT 1 // 2 AS x;
```
| x |
| ---: |
| 0 | | 116 | [
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] |
|
SQL | DuckDB's SQL Dialect | `UNION` of Boolean and Integer Values | The following query fails in PostgreSQL but successfully completes in DuckDB:
```sql
SELECT true AS x
UNION
SELECT 2;
```
PostgreSQL returns an error:
```console
ERROR: UNION types boolean and integer cannot be matched
```
DuckDB performs an enforced cast, therefore, it completes the query and returns the following:
| x |
| ---: |
| 1 |
| 2 | | 93 | [
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|
SQL | DuckDB's SQL Dialect | Case Sensitivity for Quoted Identifiers | PostgreSQL is case-insensitive. The way PostgreSQL achieves case insensitivity is by lowercasing unquoted identifiers within SQL, whereas quoting preserves case, e.g., the following command creates a table named `mytable` but tries to query for `MyTaBLe` because quotes preserve the case.
```sql
CREATE TABLE MyTaBLe(x INT);
SELECT * FROM "MyTaBLe";
```
```console
ERROR: relation "MyTaBLe" does not exist
```
PostgreSQL does not only treat quoted identifiers as case-sensitive, PostgreSQL treats all identifiers as case-sensitive, e.g., this also does not work:
```sql
CREATE TABLE "PreservedCase"(x INT);
SELECT * FROM PreservedCase;
```
```console
ERROR: relation "preservedcase" does not exist
```
Therefore, case-insensitivity in PostgreSQL only works if you never use quoted identifiers with different cases.
For DuckDB, this behavior was problematic when interfacing with other tools (e.g., Parquet, Pandas) that are case-sensitive by default - since all identifiers would be lowercased all the time.
Therefore, DuckDB achieves case insensitivity by making identifiers fully case insensitive throughout the system but [_preserving their case_](#docs:sql:dialect:keywords_and_identifiers::rules-for-case-sensitivity).
In DuckDB, the scripts above complete successfully:
```sql
CREATE TABLE MyTaBLe(x INT);
SELECT * FROM "MyTaBLe";
CREATE TABLE "PreservedCase"(x INT);
SELECT * FROM PreservedCase;
SELECT table_name FROM duckdb_tables();
```
<div class="narrow_table monospace_table"></div>
| table_name |
| ------------- |
| MyTaBLe |
| PreservedCase |
PostgreSQL's behavior of lowercasing identifiers is accessible using the [`preserve_identifier_case` option](#docs:configuration:overview::local-configuration-options):
```sql
SET preserve_identifier_case = false;
CREATE TABLE MyTaBLe(x INT);
SELECT table_name FROM duckdb_tables();
```
<div class="narrow_table monospace_table"></div>
| table_name |
| ---------- |
| mytable |
However, the case insensitive matching in the system for identifiers cannot be turned off. | 478 | [
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|
SQL | DuckDB's SQL Dialect | Using Double Equality Sign for Comparison | DuckDB supports both `=` and `==` for quality comparison, while Postgres only supports `=`.
```sql
SELECT 1 == 1 AS t;
```
DuckDB returns:
```text
βββββββββββ
β t β
β boolean β
βββββββββββ€
β true β
βββββββββββ
```
Postgres returns:
```console
postgres=# SELECT 1 == 1 AS t;
ERROR: operator does not exist: integer == integer
LINE 1: SELECT 1 == 1 AS t;
```
Note that the use of `==` is not encouraged due to its limited portability. | 149 | [
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|
SQL | DuckDB's SQL Dialect | Vacuuming tables | In PostgreSQL, the `VACUUM` statement garbage collects tables and analyzes tables.
In DuckDB, the [`VACUUM` statement](#docs:sql:statements:vacuum) is only used to rebuild statistics.
For instruction on reclaiming space, refer to the [βReclaiming spaceβ page](#docs:operations_manual:footprint_of_duckdb:reclaiming_space). | 85 | [
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|
SQL | DuckDB's SQL Dialect | Functions | #### `to_date` Function {#docs:sql:dialect:postgresql_compatibility::to_date-function}
DuckDB does not support the [`to_date` PostgreSQL date formatting function](https://www.postgresql.org/docs/17/functions-formatting.html).
Instead, please use the [`strptime` function](#docs:sql:functions:dateformat::strptime-examples). | 79 | [
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|
SQL | DuckDB's SQL Dialect | Resolution of Type Names in the Schema | For [`CREATE TABLE` statements](#docs:sql:statements:create_table), DuckDB attempts to resolve type names in the schema where a table is created. For example:
```sql
CREATE SCHEMA myschema;
CREATE TYPE myschema.mytype AS ENUM ('as', 'df');
CREATE TABLE myschema.mytable (v mytype);
```
PostgreSQL returns an error on the last statement:
```console
ERROR: type "mytype" does not exist
LINE 1: CREATE TABLE myschema.mytable (v mytype);
^
```
DuckDB runs the statement and creates the table successfully, confirmed by the following query:
```sql
DESCRIBE myschema.mytable;
```
```text
βββββββββββββββ¬βββββββββββββββββββ¬ββββββββββ¬ββββββββββ¬ββββββββββ¬ββββββββββ
β column_name β column_type β null β key β default β extra β
β varchar β varchar β varchar β varchar β varchar β varchar β
βββββββββββββββΌβββββββββββββββββββΌββββββββββΌββββββββββΌββββββββββΌββββββββββ€
β v β ENUM('as', 'df') β YES β NULL β NULL β NULL β
βββββββββββββββ΄βββββββββββββββββββ΄ββββββββββ΄ββββββββββ΄ββββββββββ΄ββββββββββ
``` | 307 | [
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|
SQL | Samples | Samples are used to randomly select a subset of a dataset.
#### Examples {#docs:sql:samples::examples}
Select a sample of 5 rows from `tbl` using reservoir sampling:
```sql
SELECT *
FROM tbl
USING SAMPLE 5;
```
Select a sample of 10% of the table using system sampling (cluster sampling):
```sql
SELECT *
FROM tbl
USING SAMPLE 10%;
```
Select a sample of 10% of the table using bernoulli sampling:
```sql
SELECT *
FROM tbl
USING SAMPLE 10 PERCENT (bernoulli);
```
Select a sample of 50 rows of the table using reservoir sampling with a fixed seed (100):
```sql
SELECT *
FROM tbl
USING SAMPLE reservoir(50 ROWS)
REPEATABLE (100);
```
Select a sample of 20% of the table using system sampling with a fixed seed (377):
```sql
SELECT *
FROM tbl
USING SAMPLE 20% (system, 377);
```
Select a sample of 20% of `tbl` **before** the join with `tbl2`:
```sql
SELECT *
FROM tbl TABLESAMPLE reservoir(20%), tbl2
WHERE tbl.i = tbl2.i;
```
Select a sample of 20% of `tbl` **after** the join with `tbl2`:
```sql
SELECT *
FROM tbl, tbl2
WHERE tbl.i = tbl2.i
USING SAMPLE reservoir(20%);
```
#### Syntax {#docs:sql:samples::syntax}
<div id="rrdiagram"></div>
Samples allow you to randomly extract a subset of a dataset. Samples are useful for exploring a dataset faster, as often you might not be interested in the exact answers to queries, but only in rough indications of what the data looks like and what is in the data. Samples allow you to get approximate answers to queries faster, as they reduce the amount of data that needs to pass through the query engine.
DuckDB supports three different types of sampling methods: `reservoir`, `bernoulli` and `system`. By default, DuckDB uses `reservoir` sampling when an exact number of rows is sampled, and `system` sampling when a percentage is specified. The sampling methods are described in detail below.
Samples require a *sample size*, which is an indication of how many elements will be sampled from the total population. Samples can either be given as a percentage (` 10%`) or as a fixed number of rows (` 10 rows`). All three sampling methods support sampling over a percentage, but **only** reservoir sampling supports sampling a fixed number of rows.
Samples are probablistic, that is to say, samples can be different between runs *unless* the seed is specifically specified. Specifying the seed *only* guarantees that the sample is the same if multi-threading is not enabled (i.e., `SET threads = 1`). In the case of multiple threads running over a sample, samples are not necessarily consistent even with a fixed seed.
#### `reservoir` {#docs:sql:samples::reservoir}
Reservoir sampling is a stream sampling technique that selects a random sample by keeping a *reservoir* of size equal to the sample size, and randomly replacing elements as more elements come in. Reservoir sampling allows us to specify *exactly* how many elements we want in the resulting sample (by selecting the size of the reservoir). As a result, reservoir sampling *always* outputs the same amount of elements, unlike system and bernoulli sampling.
Reservoir sampling is only recommended for small sample sizes, and is not recommended for use with percentages. That is because reservoir sampling needs to materialize the entire sample and randomly replace tuples within the materialized sample. The larger the sample size, the higher the performance hit incurred by this process.
Reservoir sampling also incurs an additional performance penalty when multi-processing is used, since the reservoir is to be shared amongst the different threads to ensure unbiased sampling. This is not a big problem when the reservoir is very small, but becomes costly when the sample is large.
> **Best practice. ** Avoid using reservoir sampling with large sample sizes if possible.
> Reservoir sampling requires the entire sample to be materialized in memory.
#### `bernoulli` {#docs:sql:samples::bernoulli}
Bernoulli sampling can only be used when a sampling percentage is specified. It is rather straightforward: every tuple in the underlying table is included with a chance equal to the specified percentage. As a result, bernoulli sampling can return a different number of tuples even if the same percentage is specified. The amount of rows will generally be more or less equal to the specified percentage of the table, but there will be some variance.
Because bernoulli sampling is completely independent (there is no shared state), there is no penalty for using bernoulli sampling together with multiple threads.
#### `system` {#docs:sql:samples::system}
System sampling is a variant of bernoulli sampling with one crucial difference: every *vector* is included with a chance equal to the sampling percentage. This is a form of cluster sampling. System sampling is more efficient than bernoulli sampling, as no per-tuple selections have to be performed. There is almost no extra overhead for using system sampling, whereas bernoulli sampling can add additional cost as it has to perform random number generation for every single tuple.
System sampling is not suitable for smaller data sets as the granularity of the sampling is on the order of ~1000 tuples. That means that if system sampling is used for small data sets (e.g., 100 rows) either all the data will be filtered out, or all the data will be included. | 1,207 | [
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||
SQL | Samples | Table Samples | The `TABLESAMPLE` and `USING SAMPLE` clauses are identical in terms of syntax and effect, with one important difference: tablesamples sample directly from the table for which they are specified, whereas the sample clause samples after the entire from clause has been resolved. This is relevant when there are joins present in the query plan.
The `TABLESAMPLE` clause is essentially equivalent to creating a subquery with the `USING SAMPLE` clause, i.e., the following two queries are identical:
Sample 20% of `tbl` **before** the join:
```sql
SELECT * FROM tbl TABLESAMPLE reservoir(20%), tbl2 WHERE tbl.i = tbl2.i;
```
Sample 20% of `tbl` **before** the join:
```sql
SELECT *
FROM (SELECT * FROM tbl USING SAMPLE reservoir(20%)) tbl, tbl2
WHERE tbl.i = tbl2.i;
```
Sample 20% **after** the join (i.e., sample 20% of the join result):
```sql
SELECT *
FROM tbl, tbl2
WHERE tbl.i = tbl2.i
USING SAMPLE reservoir(20%);
``` | 239 | [
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|
Configuration | Configuration | DuckDB has a number of configuration options that can be used to change the behavior of the system.
The configuration options can be set using either the [`SET` statement](#docs:sql:statements:set) or the [`PRAGMA` statement](#docs:configuration:pragmas).
They can be reset to their original values using the [`RESET` statement](#docs:sql:statements:set::reset).
The values of configuration options can be queried via the [`current_setting()` scalar function](#docs:sql:functions:utility) or using the [`duckdb_settings()` table function](#docs:sql:meta:duckdb_table_functions::duckdb_settings). For example:
```sql
SELECT current_setting('memory_limit') AS memlimit;
SELECT value AS memlimit FROM duckdb_settings() WHERE name = 'memory_limit';
``` | 176 | [
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||
Configuration | Configuration | Examples | Set the memory limit of the system to 10 GB.
```sql
SET memory_limit = '10GB';
```
Configure the system to use 1 thread.
```sql
SET threads TO 1;
```
Enable printing of a progress bar during long-running queries.
```sql
SET enable_progress_bar = true;
```
Set the default null order to `NULLS LAST`.
```sql
SET default_null_order = 'nulls_last';
```
Return the current value of a specific setting.
```sql
SELECT current_setting('threads') AS threads;
```
| threads |
|--------:|
| 10 |
Query a specific setting.
```sql
SELECT *
FROM duckdb_settings()
WHERE name = 'threads';
```
| name | value | description | input_type | scope |
|---------|-------|-------------------------------------------------|------------|--------|
| threads | 1 | The number of total threads used by the system. | BIGINT | GLOBAL |
Show a list of all available settings.
```sql
SELECT *
FROM duckdb_settings();
```
Reset the memory limit of the system back to the default.
```sql
RESET memory_limit;
``` | 255 | [
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Configuration | Configuration | Secrets Manager | DuckDB has a [Secrets manager](#docs:sql:statements:create_secret), which provides a unified user interface for secrets across all backends (e.g., AWS S3) that use them. | 43 | [
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|
Configuration | Configuration | Configuration Reference | <!-- This section is generated by scripts/generate_config_docs.py -->
Configuration options come with different default [scopes](#docs:sql:statements:set::scopes): `GLOBAL` and `LOCAL`. Below is a list of all available configuration options by scope.
#### Global Configuration Options {#docs:configuration:overview::global-configuration-options}
| Name | Description | Type | Default value |
|----|--------|--|---|
| `Calendar` | The current calendar | `VARCHAR` | System (locale) calendar |
| `TimeZone` | The current time zone | `VARCHAR` | System (locale) timezone |
| `access_mode` | Access mode of the database (` AUTOMATIC`, `READ_ONLY` or `READ_WRITE`) | `VARCHAR` | `automatic` |
| `allocator_background_threads` | Whether to enable the allocator background thread. | `BOOLEAN` | `false` |
| `allocator_bulk_deallocation_flush_threshold` | If a bulk deallocation larger than this occurs, flush outstanding allocations. | `VARCHAR` | `512.0 MiB` |
| `allocator_flush_threshold` | Peak allocation threshold at which to flush the allocator after completing a task. | `VARCHAR` | `128.0 MiB` |
| `allow_community_extensions` | Allow to load community built extensions | `BOOLEAN` | `true` |
| `allow_extensions_metadata_mismatch` | Allow to load extensions with not compatible metadata | `BOOLEAN` | `false` |
| `allow_persistent_secrets` | Allow the creation of persistent secrets, that are stored and loaded on restarts | `BOOLEAN` | `true` |
| `allow_unredacted_secrets` | Allow printing unredacted secrets | `BOOLEAN` | `false` |
| `allow_unsigned_extensions` | Allow to load extensions with invalid or missing signatures | `BOOLEAN` | `false` |
| `arrow_large_buffer_size` | If arrow buffers for strings, blobs, uuids and bits should be exported using large buffers | `BOOLEAN` | `false` |
| `arrow_lossless_conversion` | Whenever a DuckDB type does not have a clear native or canonical extension match in Arrow, export the types with a duckdb.type_name extension name. | `BOOLEAN` | `false` |
| `arrow_output_list_view` | If export to arrow format should use ListView as the physical layout for LIST columns | `BOOLEAN` | `false` |
| `autoinstall_extension_repository` | Overrides the custom endpoint for extension installation on autoloading | `VARCHAR` | |
| `autoinstall_known_extensions` | Whether known extensions are allowed to be automatically installed when a query depends on them | `BOOLEAN` | `true` |
| `autoload_known_extensions` | Whether known extensions are allowed to be automatically loaded when a query depends on them | `BOOLEAN` | `true` |
| `binary_as_string` | In Parquet files, interpret binary data as a string. | `BOOLEAN` | |
| `ca_cert_file` | Path to a custom certificate file for self-signed certificates. | `VARCHAR` | |
| `catalog_error_max_schemas` | The maximum number of schemas the system will scan for "did you mean..." style errors in the catalog | `UBIGINT` | `100` |
| `checkpoint_threshold`, `wal_autocheckpoint` | The WAL size threshold at which to automatically trigger a checkpoint (e.g., 1GB) | `VARCHAR` | `16.0 MiB` |
| `custom_extension_repository` | Overrides the custom endpoint for remote extension installation | `VARCHAR` | |
| `custom_user_agent` | Metadata from DuckDB callers | `VARCHAR` | |
| `default_block_size` | The default block size for new duckdb database files (new as-in, they do not yet exist). | `UBIGINT` | `262144` |
| `default_collation` | The collation setting used when none is specified | `VARCHAR` | |
| `default_null_order`, `null_order` | Null ordering used when none is specified (` NULLS_FIRST`, `NULLS_LAST`, `NULLS_FIRST_ON_ASC_LAST_ON_DESC` or `NULLS_LAST_ON_ASC_FIRST_ON_DESC`) | `VARCHAR` | `NULLS_LAST` |
| `default_order` | The order type used when none is specified (` ASC` or `DESC`) | `VARCHAR` | `ASC` |
| `default_secret_storage` | Allows switching the default storage for secrets | `VARCHAR` | `local_file` |
| `disabled_filesystems` | Disable specific file systems preventing access (e.g., LocalFileSystem) | `VARCHAR` | |
| `duckdb_api` | DuckDB API surface | `VARCHAR` | `cli` |
| `enable_external_access` | Allow the database to access external state (through e.g., loading/installing modules, COPY TO/FROM, CSV readers, pandas replacement scans, etc) | `BOOLEAN` | `true` |
| `enable_fsst_vectors` | Allow scans on FSST compressed segments to emit compressed vectors to utilize late decompression | `BOOLEAN` | `false` |
| `enable_http_metadata_cache` | Whether or not the global http metadata is used to cache HTTP metadata | `BOOLEAN` | `false` |
| `enable_macro_dependencies` | Enable created MACROs to create dependencies on the referenced objects (such as tables) | `BOOLEAN` | `false` |
| `enable_object_cache` | Whether or not object cache is used to cache e.g., Parquet metadata | `BOOLEAN` | `false` |
| `enable_server_cert_verification` | Enable server side certificate verification. | `BOOLEAN` | `false` |
| `enable_view_dependencies` | Enable created VIEWs to create dependencies on the referenced objects (such as tables) | `BOOLEAN` | `false` |
| `extension_directory` | Set the directory to store extensions in | `VARCHAR` | |
| `external_threads` | The number of external threads that work on DuckDB tasks. | `BIGINT` | `1` |
| `force_download` | Forces upfront download of file | `BOOLEAN` | `false` |
| `http_keep_alive` | Keep alive connections. Setting this to false can help when running into connection failures | `BOOLEAN` | `true` |
| `http_proxy_password` | Password for HTTP proxy | `VARCHAR` | |
| `http_proxy_username` | Username for HTTP proxy | `VARCHAR` | |
| `http_proxy` | HTTP proxy host | `VARCHAR` | |
| `http_retries` | HTTP retries on I/O error | `UBIGINT` | `3` |
| `http_retry_backoff` | Backoff factor for exponentially increasing retry wait time | `FLOAT` | `4` |
| `http_retry_wait_ms` | Time between retries | `UBIGINT` | `100` |
| `http_timeout` | HTTP timeout read/write/connection/retry | `UBIGINT` | `30000` |
| `immediate_transaction_mode` | Whether transactions should be started lazily when needed, or immediately when BEGIN TRANSACTION is called | `BOOLEAN` | `false` |
| `index_scan_max_count` | The maximum index scan count sets a threshold for index scans. If fewer than MAX(index_scan_max_count, index_scan_percentage * total_row_count) rows match, we perform an index scan instead of a table scan. | `UBIGINT` | `2048` |
| `index_scan_percentage` | The index scan percentage sets a threshold for index scans. If fewer than MAX(index_scan_max_count, index_scan_percentage * total_row_count) rows match, we perform an index scan instead of a table scan. | `DOUBLE` | `0.001` |
| `lock_configuration` | Whether or not the configuration can be altered | `BOOLEAN` | `false` |
| `max_memory`, `memory_limit` | The maximum memory of the system (e.g., 1GB) | `VARCHAR` | 80% of RAM |
| `max_temp_directory_size` | The maximum amount of data stored inside the 'temp_directory' (when set). If the `temp_directory` is set to an existing directory, this option defaults to the available disk space on that drive. Otherwise, it defaults to 0 (implying that the temporary directory is not used). | `VARCHAR` | `0 bytes` |
| `max_vacuum_tasks` | The maximum vacuum tasks to schedule during a checkpoint | `UBIGINT` | `100` |
| `old_implicit_casting` | Allow implicit casting to/from VARCHAR | `BOOLEAN` | `false` |
| `password` | The password to use. Ignored for legacy compatibility. | `VARCHAR` | `NULL` |
| `preserve_insertion_order` | Whether or not to preserve insertion order. If set to false the system is allowed to re-order any results that do not contain ORDER BY clauses. | `BOOLEAN` | `true` |
| `produce_arrow_string_view` | If strings should be produced by DuckDB in Utf8View format instead of Utf8 | `BOOLEAN` | `false` |
| `s3_access_key_id` | S3 Access Key ID | `VARCHAR` | |
| `s3_endpoint` | S3 Endpoint | `VARCHAR` | |
| `s3_region` | S3 Region | `VARCHAR` | `us-east-1` |
| `s3_secret_access_key` | S3 Access Key | `VARCHAR` | |
| `s3_session_token` | S3 Session Token | `VARCHAR` | |
| `s3_uploader_max_filesize` | S3 Uploader max filesize (between 50GB and 5TB) | `VARCHAR` | `800GB` |
| `s3_uploader_max_parts_per_file` | S3 Uploader max parts per file (between 1 and 10000) | `UBIGINT` | `10000` |
| `s3_uploader_thread_limit` | S3 Uploader global thread limit | `UBIGINT` | `50` |
| `s3_url_compatibility_mode` | Disable Globs and Query Parameters on S3 URLs | `BOOLEAN` | `false` |
| `s3_url_style` | S3 URL style | `VARCHAR` | `vhost` |
| `s3_use_ssl` | S3 use SSL | `BOOLEAN` | `true` |
| `secret_directory` | Set the directory to which persistent secrets are stored | `VARCHAR` | `~/.duckdb/stored_secrets` |
| `storage_compatibility_version` | Serialize on checkpoint with compatibility for a given duckdb version | `VARCHAR` | `v0.10.2` |
| `temp_directory` | Set the directory to which to write temp files | `VARCHAR` | `β¨database_nameβ©.tmp` or `.tmp` (in in-memory mode) |
| `threads`, `worker_threads` | The number of total threads used by the system. | `BIGINT` | # CPU cores |
| `username`, `user` | The username to use. Ignored for legacy compatibility. | `VARCHAR` | `NULL` |
#### Local Configuration Options {#docs:configuration:overview::local-configuration-options}
| Name | Description | Type | Default value |
|----|--------|--|---|
| `custom_profiling_settings` | Accepts a `JSON` enabling custom metrics | `VARCHAR` | `{"RESULT_SET_SIZE": "true", "OPERATOR_TIMING": "true", "OPERATOR_ROWS_SCANNED": "true", "CUMULATIVE_ROWS_SCANNED": "true", "OPERATOR_CARDINALITY": "true", "OPERATOR_TYPE": "true", "CUMULATIVE_CARDINALITY": "true", "EXTRA_INFO": "true", "CPU_TIME": "true", "BLOCKED_THREAD_TIME": "true", "QUERY_NAME": "true"}` |
| `enable_http_logging` | Enables HTTP logging | `BOOLEAN` | `false` |
| `enable_profiling` | Enables profiling, and sets the output format (` JSON`, `QUERY_TREE`, `QUERY_TREE_OPTIMIZER`) | `VARCHAR` | `NULL` |
| `enable_progress_bar_print` | Controls the printing of the progress bar, when 'enable_progress_bar' is true | `BOOLEAN` | `true` |
| `enable_progress_bar` | Enables the progress bar, printing progress to the terminal for long queries | `BOOLEAN` | `true` |
| `errors_as_json` | Output error messages as structured `JSON` instead of as a raw string | `BOOLEAN` | `false` |
| `explain_output` | Output of EXPLAIN statements (` ALL`, `OPTIMIZED_ONLY`, `PHYSICAL_ONLY`) | `VARCHAR` | `physical_only` |
| `file_search_path` | A comma separated list of directories to search for input files | `VARCHAR` | |
| `home_directory` | Sets the home directory used by the system | `VARCHAR` | |
| `http_logging_output` | The file to which HTTP logging output should be saved, or empty to print to the terminal | `VARCHAR` | |
| `ieee_floating_point_ops` | Use IEE754-compliant floating point operations (returning NAN instead of errors/NULL) | `BOOLEAN` | `true` |
| `integer_division` | Whether or not the / operator defaults to integer division, or to floating point division | `BOOLEAN` | `false` |
| `log_query_path` | Specifies the path to which queries should be logged (default: NULL, queries are not logged) | `VARCHAR` | `NULL` |
| `max_expression_depth` | The maximum expression depth limit in the parser. WARNING: increasing this setting and using very deep expressions might lead to stack overflow errors. | `UBIGINT` | `1000` |
| `merge_join_threshold` | The number of rows we need on either table to choose a merge join | `UBIGINT` | `1000` |
| `nested_loop_join_threshold` | The number of rows we need on either table to choose a nested loop join | `UBIGINT` | `5` |
| `order_by_non_integer_literal` | Allow ordering by non-integer literals - ordering by such literals has no effect | `BOOLEAN` | `false` |
| `ordered_aggregate_threshold` | The number of rows to accumulate before sorting, used for tuning | `UBIGINT` | `262144` |
| `partitioned_write_flush_threshold` | The threshold in number of rows after which we flush a thread state when writing using `PARTITION_BY` | `UBIGINT` | `524288` |
| `partitioned_write_max_open_files` | The maximum amount of files the system can keep open before flushing to disk when writing using `PARTITION_BY` | `UBIGINT` | `100` |
| `perfect_ht_threshold` | Threshold in bytes for when to use a perfect hash table | `BIGINT` | `12` |
| `pivot_filter_threshold` | The threshold to switch from using filtered aggregates to LIST with a dedicated pivot operator | `BIGINT` | `20` |
| `pivot_limit` | The maximum number of pivot columns in a pivot statement | `BIGINT` | `100000` |
| `prefer_range_joins` | Force use of range joins with mixed predicates | `BOOLEAN` | `false` |
| `preserve_identifier_case` | Whether or not to preserve the identifier case, instead of always lowercasing all non-quoted identifiers | `BOOLEAN` | `true` |
| `profile_output`, `profiling_output` | The file to which profile output should be saved, or empty to print to the terminal | `VARCHAR` | |
| `profiling_mode` | The profiling mode (` STANDARD` or `DETAILED`) | `VARCHAR` | `NULL` |
| `progress_bar_time` | Sets the time (in milliseconds) how long a query needs to take before we start printing a progress bar | `BIGINT` | `2000` |
| `scalar_subquery_error_on_multiple_rows` | When a scalar subquery returns multiple rows - return a random row instead of returning an error | `BOOLEAN` | `true` |
| `schema` | Sets the default search schema. Equivalent to setting search_path to a single value. | `VARCHAR` | `main` |
| `search_path` | Sets the default catalog search path as a comma-separated list of values | `VARCHAR` | |
| `streaming_buffer_size` | The maximum memory to buffer between fetching from a streaming result (e.g., 1GB) | `VARCHAR` | `976.5 KiB` | | 4,038 | [
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|
Configuration | Pragmas | <!-- markdownlint-disable MD001 -->
The `PRAGMA` statement is a SQL extension adopted by DuckDB from SQLite. `PRAGMA` statements can be issued in a similar manner to regular SQL statements. `PRAGMA` commands may alter the internal state of the database engine, and can influence the subsequent execution or behavior of the engine.
`PRAGMA` statements that assign a value to an option can also be issued using the [`SET` statement](#docs:sql:statements:set) and the value of an option can be retrieved using `SELECT current_setting(option_name)`.
For DuckDB's built in configuration options, see the [Configuration Reference](#docs:configuration:overview::configuration-reference).
DuckDB [extensions](#docs:extensions:overview) may register additional configuration options.
These are documented in the respective extensions' documentation pages.
This page contains the supported `PRAGMA` settings. | 187 | [
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||
Configuration | Pragmas | Metadata | Schema Information | List all databases:
```sql
PRAGMA database_list;
```
List all tables:
```sql
PRAGMA show_tables;
```
List all tables, with extra information, similarly to [`DESCRIBE`](#docs:guides:meta:describe):
```sql
PRAGMA show_tables_expanded;
```
To list all functions:
```sql
PRAGMA functions;
``` | 82 | [
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Configuration | Pragmas | Metadata | Table Information | Get info for a specific table:
```sql
PRAGMA table_info('table_name');
CALL pragma_table_info('table_name');
```
`table_info` returns information about the columns of the table with name `table_name`. The exact format of the table returned is given below:
```sql
cid INTEGER, -- cid of the column
name VARCHAR, -- name of the column
type VARCHAR, -- type of the column
notnull BOOLEAN, -- if the column is marked as NOT NULL
dflt_value VARCHAR, -- default value of the column, or NULL if not specified
pk BOOLEAN -- part of the primary key or not
``` | 138 | [
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Configuration | Pragmas | Metadata | Database Size | Get the file and memory size of each database:
```sql
SET database_size;
CALL pragma_database_size();
```
`database_size` returns information about the file and memory size of each database. The column types of the returned results are given below:
```sql
database_name VARCHAR, -- database name
database_size VARCHAR, -- total block count times the block size
block_size BIGINT, -- database block size
total_blocks BIGINT, -- total blocks in the database
used_blocks BIGINT, -- used blocks in the database
free_blocks BIGINT, -- free blocks in the database
wal_size VARCHAR, -- write ahead log size
memory_usage VARCHAR, -- memory used by the database buffer manager
memory_limit VARCHAR -- maximum memory allowed for the database
``` | 165 | [
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Configuration | Pragmas | Metadata | Storage Information | To get storage information:
```sql
PRAGMA storage_info('table_name');
CALL pragma_storage_info('table_name');
```
This call returns the following information for the given table:
<div class="narrow_table"></div>
| Name | Type | Description |
|----------------|-----------|-------------------------------------------------------|
| `row_group_id` | `BIGINT` ||
| `column_name` | `VARCHAR` ||
| `column_id` | `BIGINT` ||
| `column_path` | `VARCHAR` ||
| `segment_id` | `BIGINT` ||
| `segment_type` | `VARCHAR` ||
| `start` | `BIGINT` | The start row id of this chunk |
| `count` | `BIGINT` | The amount of entries in this storage chunk |
| `compression` | `VARCHAR` | Compression type used for this column β see the [βLightweight Compression in DuckDBβ blog post](https://duckdb.org/2022/10/28/lightweight-compression) |
| `stats` | `VARCHAR` ||
| `has_updates` | `BOOLEAN` ||
| `persistent` | `BOOLEAN` | `false` if temporary table |
| `block_id` | `BIGINT` | empty unless persistent |
| `block_offset` | `BIGINT` | empty unless persistent |
See [Storage](#docs:internals:storage) for more information. | 320 | [
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Configuration | Pragmas | Metadata | Show Databases | The following statement is equivalent to the [`SHOW DATABASES` statement](#docs:sql:statements:attach):
```sql
PRAGMA show_databases;
``` | 34 | [
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Configuration | Pragmas | Resource Management | Memory Limit | Set the memory limit for the buffer manager:
```sql
SET memory_limit = '1GB';
SET max_memory = '1GB';
```
> **Warning. ** The specified memory limit is only applied to the buffer manager.
> For most queries, the buffer manager handles the majority of the data processed.
> However, certain in-memory data structures such as [vectors](#docs:internals:vector) and query results are allocated outside of the buffer manager.
> Additionally, [aggregate functions](#docs:sql:functions:aggregates) with complex state (e.g., `list`, `mode`, `quantile`, `string_agg`, and `approx` functions) use memory outside of the buffer manager.
> Therefore, the actual memory consumption can be higher than the specified memory limit. | 166 | [
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Configuration | Pragmas | Resource Management | Threads | Set the amount of threads for parallel query execution:
```sql
SET threads = 4;
``` | 21 | [
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Configuration | Pragmas | Collations | List all available collations:
```sql
PRAGMA collations;
```
Set the default collation to one of the available ones:
```sql
SET default_collation = 'nocase';
``` | 43 | [
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|
Configuration | Pragmas | Default Ordering for NULLs | Set the default ordering for NULLs to be either `NULLS_FIRST`, `NULLS_LAST`, `NULLS_FIRST_ON_ASC_LAST_ON_DESC` or `NULLS_LAST_ON_ASC_FIRST_ON_DESC`:
```sql
SET default_null_order = 'NULLS_FIRST';
SET default_null_order = 'NULLS_LAST_ON_ASC_FIRST_ON_DESC';
```
Set the default result set ordering direction to `ASCENDING` or `DESCENDING`:
```sql
SET default_order = 'ASCENDING';
SET default_order = 'DESCENDING';
``` | 110 | [
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|
Configuration | Pragmas | Ordering by Non-Integer Literals | By default, ordering by non-integer literals is not allowed:
```sql
SELECT 42 ORDER BY 'hello world';
```
```console
-- Binder Error: ORDER BY non-integer literal has no effect.
```
To allow this behavior, use the `order_by_non_integer_literal` option:
```sql
SET order_by_non_integer_literal = true;
``` | 77 | [
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|
Configuration | Pragmas | Implicit Casting to `VARCHAR` | Prior to version 0.10.0, DuckDB would automatically allow any type to be implicitly cast to `VARCHAR` during function binding. As a result it was possible to e.g., compute the substring of an integer without using an explicit cast. For version v0.10.0 and later an explicit cast is needed instead. To revert to the old behavior that performs implicit casting, set the `old_implicit_casting` variable to `true`:
```sql
SET old_implicit_casting = true;
``` | 107 | [
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|
Configuration | Pragmas | Python: Scan All Dataframes | Prior to version 1.1.0, DuckDB's [replacement scan mechanism](#docs:api:c:replacement_scans) in Python scanned the global Python namespace. To revert to this old behavior, use the following setting:
```sql
SET python_scan_all_frames = true;
``` | 61 | [
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|
Configuration | Pragmas | Information on DuckDB | Version | Show DuckDB version:
```sql
PRAGMA version;
CALL pragma_version();
``` | 18 | [
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Configuration | Pragmas | Information on DuckDB | Platform | `platform` returns an identifier for the platform the current DuckDB executable has been compiled for, e.g., `osx_arm64`.
The format of this identifier matches the platform name as described in the [extension loading explainer](#docs:extensions:working_with_extensions::platforms):
```sql
PRAGMA platform;
CALL pragma_platform();
``` | 72 | [
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] |
Configuration | Pragmas | Information on DuckDB | User Agent | The following statement returns the user agent information, e.g., `duckdb/v0.10.0(osx_arm64)`:
```sql
PRAGMA user_agent;
``` | 37 | [
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] |
Configuration | Pragmas | Information on DuckDB | Metadata Information | The following statement returns information on the metadata store (` block_id`, `total_blocks`, `free_blocks`, and `free_list`):
```sql
PRAGMA metadata_info;
``` | 37 | [
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Configuration | Pragmas | Progress Bar | Show progress bar when running queries:
```sql
PRAGMA enable_progress_bar;
```
Or:
```sql
PRAGMA enable_print_progress_bar;
```
Don't show a progress bar for running queries:
```sql
PRAGMA disable_progress_bar;
```
Or:
```sql
PRAGMA disable_print_progress_bar;
``` | 70 | [
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|
Configuration | Pragmas | EXPLAIN Output | The output of [`EXPLAIN`](#docs:sql:statements:profiling) can be configured to show only the physical plan.
The default configuration of `EXPLAIN`:
```sql
SET explain_output = 'physical_only';
```
To only show the optimized query plan:
```sql
SET explain_output = 'optimized_only';
```
To show all query plans:
```sql
SET explain_output = 'all';
``` | 90 | [
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|
Configuration | Pragmas | Profiling | #### Enable Profiling {#docs:configuration:pragmas::enable-profiling}
The following query enables profiling with the default format, `query_tree`.
Independent of the format, `enable_profiling` is **mandatory** to enable profiling.
```sql
PRAGMA enable_profiling;
PRAGMA enable_profile;
```
###### Profiling Format {#docs:configuration:pragmas::profiling-format}
The format of `enable_profiling` can be specified as `query_tree`, `json`, `query_tree_optimizer`, or `no_output`.
Each format prints its output to the configured output, except `no_output`.
The default format is `query_tree`.
It prints the physical query plan and the metrics of each operator in the tree.
```sql
SET enable_profiling = 'query_tree';
```
Alternatively, `json` returns the physical query plan as JSON:
```sql
SET enable_profiling = 'json';
```
To return the physical query plan, including optimizer and planner metrics:
```sql
SET enable_profiling = 'query_tree_optimizer';
```
Database drivers and other applications can also access profiling information through API calls, in which case users can disable any other output.
Even though the parameter reads `no_output`, it is essential to note that this **only** affects printing to the configurable output.
When accessing profiling information through API calls, it is still crucial to enable profiling:
```sql
SET enable_profiling = 'no_output';
```
#### Profiling Output {#docs:configuration:pragmas::profiling-output}
By default, DuckDB prints profiling information to the standard output.
However, if you prefer to write the profiling information to a file, you can use `PRAGMA` `profiling_output` to specify a filepath.
> **Warning. ** The file contents will be overwritten for every newly issued query.
> Hence, the file will only contain the profiling information of the last run query:
```sql
SET profiling_output = '/path/to/file.json';
SET profile_output = '/path/to/file.json';
```
#### Profiling Mode {#docs:configuration:pragmas::profiling-mode}
By default, a limited amount of profiling information is provided (` standard`).
```sql
SET profiling_mode = 'standard';
```
For more details, use the detailed profiling mode by setting `profiling_mode` to `detailed`.
The output of this mode includes profiling of the planner and optimizer stages.
```sql
SET profiling_mode = 'detailed';
```
#### Custom Metrics {#docs:configuration:pragmas::custom-metrics}
By default, profiling enables all metrics except those activated by detailed profiling.
Using the `custom_profiling_settings` `PRAGMA`, each metric, including those from detailed profiling, can be individually enabled or disabled.
This `PRAGMA` accepts a JSON object with metric names as keys and Boolean values to toggle them on or off.
Settings specified by this `PRAGMA` override the default behavior.
> **Note. ** This only affects the metrics when the `enable_profiling` is set to `json` or `no_output`.
> The `query_tree` and `query_tree_optimizer` always use a default set of metrics.
In the following example, the `CPU_TIME` metric is disabled.
The `EXTRA_INFO`, `OPERATOR_CARDINALITY`, and `OPERATOR_TIMING` metrics are enabled.
```sql
SET custom_profiling_settings = '{"CPU_TIME": "false", "EXTRA_INFO": "true", "OPERATOR_CARDINALITY": "true", "OPERATOR_TIMING": "true"}';
```
The profiling documentation contains an overview of the available [metrics](#docs:dev:profiling::metrics).
#### Disable Profiling {#docs:configuration:pragmas::disable-profiling}
To disable profiling:
```sql
PRAGMA disable_profiling;
PRAGMA disable_profile;
``` | 824 | [
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|
Configuration | Pragmas | Query Optimization | Optimizer | To disable the query optimizer:
```sql
PRAGMA disable_optimizer;
```
To enable the query optimizer:
```sql
PRAGMA enable_optimizer;
``` | 33 | [
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Configuration | Pragmas | Query Optimization | Selectively Disabling Optimizers | The `disabled_optimizers` option allows selectively disabling optimization steps.
For example, to disable `filter_pushdown` and `statistics_propagation`, run:
```sql
SET disabled_optimizers = 'filter_pushdown,statistics_propagation';
```
The available optimizations can be queried using the [`duckdb_optimizers()` table function](#docs:sql:meta:duckdb_table_functions::duckdb_optimizers).
To re-enable the optimizers, run:
```sql
SET disabled_optimizers = '';
```
> **Warning. ** The `disabled_optimizers` option should only be used for debugging performance issues and should be avoided in production. | 141 | [
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] |
Configuration | Pragmas | Logging | Set a path for query logging:
```sql
SET log_query_path = '/tmp/duckdb_log/';
```
Disable query logging:
```sql
SET log_query_path = '';
``` | 40 | [
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|
Configuration | Pragmas | Full-Text Search Indexes | The `create_fts_index` and `drop_fts_index` options are only available when the [`fts` extension](#docs:extensions:full_text_search) is loaded. Their usage is documented on the [Full-Text Search extension page](#docs:extensions:full_text_search). | 60 | [
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|
Configuration | Pragmas | Verification | Verification of External Operators | Enable verification of external operators:
```sql
PRAGMA verify_external;
```
Disable verification of external operators:
```sql
PRAGMA disable_verify_external;
``` | 34 | [
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Configuration | Pragmas | Verification | Verification of Round-Trip Capabilities | Enable verification of round-trip capabilities for supported logical plans:
```sql
PRAGMA verify_serializer;
```
Disable verification of round-trip capabilities:
```sql
PRAGMA disable_verify_serializer;
``` | 42 | [
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Configuration | Pragmas | Object Cache | Enable caching of objects for e.g., Parquet metadata:
```sql
PRAGMA enable_object_cache;
```
Disable caching of objects:
```sql
PRAGMA disable_object_cache;
``` | 40 | [
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|
Configuration | Pragmas | Checkpointing | Force Checkpoint | When [`CHECKPOINT`](#docs:sql:statements:checkpoint) is called when no changes are made, force a checkpoint regardless:
```sql
PRAGMA force_checkpoint;
``` | 37 | [
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Configuration | Pragmas | Checkpointing | Checkpoint on Shutdown | Run a `CHECKPOINT` on successful shutdown and delete the WAL, to leave only a single database file behind:
```sql
PRAGMA enable_checkpoint_on_shutdown;
```
Don't run a `CHECKPOINT` on shutdown:
```sql
PRAGMA disable_checkpoint_on_shutdown;
``` | 59 | [
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Configuration | Pragmas | Temp Directory for Spilling Data to Disk | By default, DuckDB uses a temporary directory named `β¨database_file_nameβ©.tmp` to spill to disk, located in the same directory as the database file. To change this, use:
```sql
SET temp_directory = '/path/to/temp_dir.tmp/';
``` | 57 | [
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|
Configuration | Pragmas | Returning Errors as JSON | The `errors_as_json` option can be set to obtain error information in raw JSON format. For certain errors, extra information or decomposed information is provided for easier machine processing. For example:
```sql
SET errors_as_json = true;
```
Then, running a query that results in an error produces a JSON output:
```sql
SELECT * FROM nonexistent_tbl;
```
```json
{
"exception_type":"Catalog",
"exception_message":"Table with name nonexistent_tbl does not exist!\nDid you mean \"temp.information_schema.tables\"?",
"name":"nonexistent_tbl",
"candidates":"temp.information_schema.tables",
"position":"14",
"type":"Table",
"error_subtype":"MISSING_ENTRY"
}
``` | 148 | [
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|
Configuration | Pragmas | IEEE Floating-Point Operation Semantics | DuckDB follows IEEE floating-point operation semantics. If you would like to turn this off, run:
```sql
SET ieee_floating_point_ops = false;
```
In this case, floating point division by zero (e.g., `1.0 / 0.0`, `0.0 / 0.0` and `-1.0 / 0.0`) will all return `NULL`. | 86 | [
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|
Configuration | Pragmas | Query Verification (for Development) | The following `PRAGMA`s are mostly used for development and internal testing.
Enable query verification:
```sql
PRAGMA enable_verification;
```
Disable query verification:
```sql
PRAGMA disable_verification;
```
Enable force parallel query processing:
```sql
PRAGMA verify_parallelism;
```
Disable force parallel query processing:
```sql
PRAGMA disable_verify_parallelism;
``` | 82 | [
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|
Configuration | Pragmas | Block Sizes | When persisting a database to disk, DuckDB writes to a dedicated file containing a list of blocks holding the data.
In the case of a file that only holds very little data, e.g., a small table, the default block size of 256KB might not be ideal.
Therefore, DuckDB's storage format supports different block sizes.
There are a few constraints on possible block size values.
* Must be a power of two.
* Must be greater or equal to 16384 (16 KB).
* Must be lesser or equal to 262144 (256 KB).
You can set the default block size for all new DuckDB files created by an instance like so:
```sql
SET default_block_size = '16384';
```
It is also possible to set the block size on a per-file basis, see [`ATTACH`](#docs:sql:statements:attach) for details. | 186 | [
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|
Configuration | Secrets Manager | The **Secrets manager** provides a unified user interface for secrets across all backends that use them. Secrets can be scoped, so different storage prefixes can have different secrets, allowing for example to join data across organizations in a single query. Secrets can also be persisted, so that they do not need to be specified every time DuckDB is launched.
> **Warning. ** Persistent secrets are stored in unencrypted binary format on the disk. | 90 | [
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||
Configuration | Secrets Manager | Secrets | #### Types of Secrets {#docs:configuration:secrets_manager::types-of-secrets}
Secrets are typed, their type identifies which service they are for. Currently, the following cloud services are available:
* AWS S3 (` S3`), through the [`httpfs` extension](#docs:extensions:httpfs:s3api)
* Azure Blob Storage (` AZURE`), through the [`azure` extension](#docs:extensions:azure)
* Cloudflare R2 (` R2`), through the [`httpfs` extension](#docs:extensions:httpfs:s3api)
* Google Cloud Storage (` GCS`), through the [`httpfs` extension](#docs:extensions:httpfs:s3api)
* Hugging Face (` HUGGINGFACE`), through the [`httpfs` extension](#docs:extensions:httpfs:hugging_face)
* MySQL (` MYSQL`), through the [`mysql` extension](#docs:extensions:mysql)
* PostgreSQL (` POSTGRES`), through the [`postgres` extension](#docs:extensions:postgres)
For each type, there are one or more βsecret providersβ that specify how the secret is created. Secrets can also have an optional scope, which is a file path prefix that the secret applies to. When fetching a secret for a path, the secret scopes are compared to the path, returning the matching secret for the path. In the case of multiple matching secrets, the longest prefix is chosen.
#### Creating a Secret {#docs:configuration:secrets_manager::creating-a-secret}
Secrets can be created using the [`CREATE SECRET` SQL statement](#docs:sql:statements:create_secret).
Secrets can be **temporary** or **persistent**. Temporary secrets are used by default β and are stored in-memory for the life span of the DuckDB instance similar to how settings worked previously. Persistent secrets are stored in **unencrypted binary format** in the `~/.duckdb/stored_secrets` directory. On startup of DuckDB, persistent secrets are read from this directory and automatically loaded. | 424 | [
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|
Configuration | Secrets Manager | Secrets | Secret Providers | To create a secret, a **Secret Provider** needs to be used. A Secret Provider is a mechanism through which a secret is generated. To illustrate this, for the `S3`, `GCS`, `R2`, and `AZURE` secret types, DuckDB currently supports two providers: `CONFIG` and `CREDENTIAL_CHAIN`. The `CONFIG` provider requires the user to pass all configuration information into the `CREATE SECRET`, whereas the `CREDENTIAL_CHAIN` provider will automatically try to fetch credentials. When no Secret Provider is specified, the `CONFIG` provider is used. For more details on how to create secrets using different providers check out the respective pages on [httpfs](#docs:extensions:httpfs:overview::configuration-and-authentication-using-secrets) and [azure](#docs:extensions:azure::authentication-with-secret). | 172 | [
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Configuration | Secrets Manager | Secrets | Temporary Secrets | To create a temporary unscoped secret to access S3, we can now use the following:
```sql
CREATE SECRET my_secret (
TYPE S3,
KEY_ID 'my_secret_key',
SECRET 'my_secret_value',
REGION 'my_region'
);
```
Note that we implicitly use the default `CONFIG` secret provider here. | 67 | [
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Configuration | Secrets Manager | Secrets | Persistent Secrets | In order to persist secrets between DuckDB database instances, we can now use the `CREATE PERSISTENT SECRET` command, e.g.:
```sql
CREATE PERSISTENT SECRET my_persistent_secret (
TYPE S3,
KEY_ID 'my_secret_key',
SECRET 'my_secret_value'
);
```
By default, this will write the secret (unencrypted) to the `~/.duckdb/stored_secrets` directory. To change the secrets directory, issue:
```sql
SET secret_directory = 'path/to/my_secrets_dir';
```
Note that setting the value of the `home_directory` configuration option has no effect on the location of the secrets.
#### Deleting Secrets {#docs:configuration:secrets_manager::deleting-secrets}
Secrets can be deleted using the [`DROP SECRET` statement](#docs:sql:statements:create_secret::syntax-for-drop-secret), e.g.:
```sql
DROP PERSISTENT SECRET my_persistent_secret;
```
#### Creating Multiple Secrets for the Same Service Type {#docs:configuration:secrets_manager::creating-multiple-secrets-for-the-same-service-type}
If two secrets exist for a service type, the scope can be used to decide which one should be used. For example:
```sql
CREATE SECRET secret1 (
TYPE S3,
KEY_ID 'my_secret_key1',
SECRET 'my_secret_value1',
SCOPE 's3://my-bucket'
);
```
```sql
CREATE SECRET secret2 (
TYPE S3,
KEY_ID 'my_secret_key2',
SECRET 'my_secret_value2',
SCOPE 's3://my-other-bucket'
);
```
Now, if the user queries something from `s3://my-other-bucket/something`, secret `secret2` will be chosen automatically for that request. To see which secret is being used, the `which_secret` scalar function can be used, which takes a path and a secret type as parameters:
```sql
FROM which_secret('s3://my-other-bucket/file.parquet', 's3');
```
#### Listing Secrets {#docs:configuration:secrets_manager::listing-secrets}
Secrets can be listed using the built-in table-producing function, e.g., by using the [`duckdb_secrets()` table function](#docs:sql:meta:duckdb_table_functions::duckdb_secrets):
```sql
FROM duckdb_secrets();
```
Sensitive information will be redacted. | 511 | [
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Extensions | Extensions | Overview | DuckDB has a flexible extension mechanism that allows for dynamically loading extensions.
These may extend DuckDB's functionality by providing support for additional file formats, introducing new types, and domain-specific functionality.
> Extensions are loadable on all clients (e.g., Python and R).
> Extensions distributed via the Core and Community repositories are built and tested on macOS, Windows and Linux. All operating systems are supported for both the AMD64 and the ARM64 architectures. | 92 | [
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|
Extensions | Extensions | Listing Extensions | To get a list of extensions, use `duckdb_extensions`:
```sql
SELECT extension_name, installed, description
FROM duckdb_extensions();
```
<div class="narrow_table"></div>
| extension_name | installed | description |
|-------------------|-----------|--------------------------------------------------------------|
| arrow | false | A zero-copy data integration between Apache Arrow and DuckDB |
| autocomplete | false | Adds support for autocomplete in the shell |
| ... | ... | ... |
This list will show which extensions are available, which extensions are installed, at which version, where it is installed, and more.
The list includes most, but not all, available core extensions. For the full list, we maintain a [list of core extensions](#docs:extensions:core_extensions). | 168 | [
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|
Extensions | Extensions | Built-In Extensions | DuckDB's binary distribution comes standard with a few built-in extensions. They are statically linked into the binary and can be used as is.
For example, to use the built-in [`json` extension](#docs:data:json:overview) to read a JSON file:
```sql
SELECT *
FROM 'test.json';
```
To make the DuckDB distribution lightweight, only a few essential extensions are built-in, varying slightly per distribution. Which extension is built-in on which platform is documented in the [list of core extensions](#docs:extensions:core_extensions::default-extensions). | 121 | [
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|
Extensions | Extensions | Installing More Extensions | To make an extension that is not built-in available in DuckDB, two steps need to happen:
1. **Extension installation** is the process of downloading the extension binary and verifying its metadata. During installation, DuckDB stores the downloaded extension and some metadata in a local directory. From this directory DuckDB can then load the Extension whenever it needs to. This means that installation needs to happen only once.
2. **Extension loading** is the process of dynamically loading the binary into a DuckDB instance. DuckDB will search the local extension
directory for the installed extension, then load it to make its features available. This means that every time DuckDB is restarted, all
extensions that are used need to be (re)loaded
> Extension installation and loading are subject to a few [limitations](#docs:extensions:working_with_extensions::limitations).
There are two main methods of making DuckDB perform the **installation** and **loading** steps for an installable extension: **explicitly** and through **autoloading**.
#### Explicit `INSTALL` and `LOAD` {#docs:extensions:overview::explicit-install-and-load}
In DuckDB extensions can also be explicitly installed and loaded. Both non-autoloadable and autoloadable extensions can be installed this way.
To explicitly install and load an extension, DuckDB has the dedicated SQL statements `LOAD` and `INSTALL`. For example,
to install and load the [`spatial` extension](#docs:extensions:spatial:overview), run:
```sql
INSTALL spatial;
LOAD spatial;
```
With these statements, DuckDB will ensure the spatial extension is installed (ignoring the `INSTALL` statement if it is already installed), then proceed
to `LOAD` the spatial extension (again ignoring the statement if it is already loaded). | 371 | [
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|
Extensions | Extensions | Installing More Extensions | Extension Repository | Optionally a repository can be provided where the extension should be installed from, by appending `FROM <repository>` to the `INSTALL`/`FORCE INSTALL` command.
This repository can either be an alias, such as [`community`](#docs:extensions:community_extensions), or it can be a direct URL, provided as a single-quoted string.
After installing/loading an extension, the [`duckdb_extensions` function](#::listing-extensions) can be used to get more information.
#### Autoloading Extensions {#docs:extensions:overview::autoloading-extensions}
For many of DuckDB's core extensions, explicitly loading and installing extensions is not necessary. DuckDB contains an autoloading mechanism
which can install and load the core extensions as soon as they are used in a query. For example, when running:
```sql
SELECT *
FROM 'https://raw.githubusercontent.com/duckdb/duckdb-web/main/data/weather.csv';
```
DuckDB will automatically install and load the [`httpfs`](#docs:extensions:httpfs:overview) extension. No explicit `INSTALL` or `LOAD` statements are required.
Not all extensions can be autoloaded. This can have various reasons: some extensions make several changes to the running DuckDB instance, making autoloading technically not (yet) possible. For others, it is preferred to have users opt-in to the extension explicitly before use due to the way they modify behavior in DuckDB.
To see which extensions can be autoloaded, check the [core extensions list](#docs:extensions:core_extensions).
#### Community Extensions {#docs:extensions:overview::community-extensions}
DuckDB supports installing third-party [Community Extensions](#docs:extensions:community_extensions).
These are contributed by community members but they are built, signed, and distributed in a centralized repository.
#### Installing Extensions through Client APIs {#docs:extensions:overview::installing-extensions-through-client-apis}
For many clients, using SQL to load and install extensions is the preferred method. However, some clients have a dedicated
API to install and load extensions. For example the [Python API client](#docs:api:python:overview::loading-and-installing-extensions),
which has dedicated `install_extension(name: str)` and `load_extension(name: str)` methods. For more details on a specific Client API, refer
to the [Client API docs](#docs:api:overview) | 508 | [
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Extensions | Extensions | Updating Extensions | While built-in extensions are tied to a DuckDB release due to their nature of being built into the DuckDB binary, installable extensions
can and do receive updates. To ensure all currently installed extensions are on the most recent version, call:
```sql
UPDATE EXTENSIONS;
```
For more details on extension version refer to [Extension Versioning](#docs:extensions:versioning_of_extensions). | 82 | [
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|
Extensions | Extensions | Installation Location | By default, extensions are installed under the user's home directory:
```text
~/.duckdb/extensions/β¨duckdb_versionβ©/β¨platform_nameβ©/
```
For stable DuckDB releases, the `β¨duckdb_versionβ©` will be equal to the version tag of that release. For nightly DuckDB builds, it will be equal
to the short git hash of the build. So for example, the extensions for DuckDB version v0.10.3 on macOS ARM64 (Apple Silicon) are installed to `~/.duckdb/extensions/v0.10.3/osx_arm64/`.
An example installation path for a nightly DuckDB build could be `~/.duckdb/extensions/fc2e4b26a6/linux_amd64_gcc4`.
To change the default location where DuckDB stores its extensions, use the `extension_directory` configuration option:
```sql
SET extension_directory = '/path/to/your/extension/directory';
```
Note that setting the value of the `home_directory` configuration option has no effect on the location of the extensions. | 229 | [
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|
Extensions | Extensions | Binary Compatibility | To avoid binary compatibility issues, the binary extensions distributed by DuckDB are tied both to a specific DuckDB version and a platform. This means that DuckDB can automatically detect binary compatibility between it and a loadable extension. When trying to load an extension that was compiled for a different version or platform, DuckDB will throw an error and refuse to load the extension.
See the [Working with Extensions page](#docs:extensions:working_with_extensions::platforms) for details on available platforms. | 100 | [
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|
Extensions | Extensions | Developing Extensions | The same API that the core extensions use is available for developing extensions. This allows users to extend the functionality of DuckDB such that it suits their domain the best.
A template for creating extensions is available in the [`extension-template` repository](https://github.com/duckdb/extension-template/). This template also holds some documentation on how to get started building your own extension. | 76 | [
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|
Extensions | Extensions | Extension Signing | Extensions are signed with a cryptographic key, which also simplifies distribution (this is why they are served over HTTP and not HTTPS).
By default, DuckDB uses its built-in public keys to verify the integrity of extension before loading them.
All extensions provided by the DuckDB core team are signed.
#### Unsigned Extensions {#docs:extensions:overview::unsigned-extensions}
> **Warning. ** Only load unsigned extensions from sources you trust. Also, avoid loading them over HTTP.
If you wish to load your own extensions or extensions from third-parties you will need to enable the `allow_unsigned_extensions` flag.
To load unsigned extensions using the [CLI client](#docs:api:cli:overview), pass the `-unsigned` flag to it on startup:
```bash
duckdb -unsigned
```
Now any extension can be loaded, signed or not:
```sql
LOAD './some/local/ext.duckdb_extension';
```
For Client APIs, the `allow_unsigned_extensions` database configuration options needs to be set, see the respective [Client API docs](#docs:api:overview).
For example, for the Python client, see the [Loading and Installing Extensions section in the Python API documentation](#docs:api:python:overview::loading-and-installing-extensions). | 266 | [
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|
Extensions | Extensions | Working with Extensions | For advanced installation instructions and more details on extensions, see the [Working with Extensions page](#docs:extensions:working_with_extensions). | 27 | [
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|
Extensions | Core Extensions | List of Core Extensions | | Name | GitHub | Description | Autoloadable | Aliases |
|:-----------------------------|----------------------------------------------------------------------------------|:-----------------------------------------------------------------------------------|:--------------|:------------------------|
| [arrow](#docs:extensions:arrow) | [<span class="github">GitHub</span>](https://github.com/duckdb/arrow) | A zero-copy data integration between Apache Arrow and DuckDB | no | |
| [autocomplete](#docs:extensions:autocomplete) | | Adds support for autocomplete in the shell | yes | |
| [aws](#docs:extensions:aws) | [<span class="github">GitHub</span>](https://github.com/duckdb/duckdb_aws) | Provides features that depend on the AWS SDK | yes | |
| [azure](#docs:extensions:azure) | [<span class="github">GitHub</span>](https://github.com/duckdb/duckdb_azure) | Adds a filesystem abstraction for Azure blob storage to DuckDB | yes | |
| [delta](#docs:extensions:delta) | [<span class="github">GitHub</span>](https://github.com/duckdb/duckdb_delta) | Adds support for Delta Lake | yes | |
| [excel](#docs:extensions:excel) | [<span class="github">GitHub</span>](https://github.com/duckdb/duckdb_excel) | Adds support for Excel-like format strings | yes | |
| [fts](#docs:extensions:full_text_search) | | Adds support for Full-Text Search Indexes | yes | |
| [httpfs](#docs:extensions:httpfs:overview) | | Adds support for reading and writing files over an HTTP(S) or S3 connection | yes | http, https, s3 |
| [iceberg](#docs:extensions:iceberg) | [<span class="github">GitHub</span>](https://github.com/duckdb/duckdb_iceberg) | Adds support for Apache Iceberg | no | |
| [icu](#docs:extensions:icu) | | Adds support for time zones and collations using the ICU library | yes | |
| [inet](#docs:extensions:inet) | [<span class="github">GitHub</span>](https://github.com/duckdb/duckdb_inet) | Adds support for IP-related data types and functions | yes | |
| [jemalloc](#docs:extensions:jemalloc) | | Overwrites system allocator with jemalloc | no | |
| [json](#docs:data:json:overview) | | Adds support for JSON operations | yes | |
| [mysql](#docs:extensions:mysql) | [<span class="github">GitHub</span>](https://github.com/duckdb/duckdb_mysql) | Adds support for reading from and writing to a MySQL database | no | |
| [parquet](#docs:data:parquet:overview) | | Adds support for reading and writing Parquet files | (built-in) | |
| [postgres](#docs:extensions:postgres) | [<span class="github">GitHub</span>](https://github.com/duckdb/postgres_scanner) | Adds support for reading from and writing to a PostgreSQL database | yes | postgres_scanner |
| [spatial](#docs:extensions:spatial:overview) | [<span class="github">GitHub</span>](https://github.com/duckdb/duckdb_spatial) | Geospatial extension that adds support for working with spatial data and functions | no | |
| [sqlite](#docs:extensions:sqlite) | [<span class="github">GitHub</span>](https://github.com/duckdb/sqlite_scanner) | Adds support for reading from and writing to SQLite database files | yes | sqlite_scanner, sqlite3 |
| [substrait](#docs:extensions:substrait) | [<span class="github">GitHub</span>](https://github.com/duckdb/substrait) | Adds support for the Substrait integration | no | |
| [tpcds](#docs:extensions:tpcds) | | Adds TPC-DS data generation and query support | yes | |
| [tpch](#docs:extensions:tpch) | | Adds TPC-H data generation and query support | yes | |
| [vss](#docs:extensions:vss) | [<span class="github">GitHub</span>](https://github.com/duckdb/duckdb_vss) | Adds support for vector similarity search queries | no | | | 1,071 | [
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|
Extensions | Core Extensions | Default Extensions | Different DuckDB clients ship a different set of extensions.
We summarize the main distributions in the table below.
<div class="narrow_table"></div>
| Name | CLI (duckdb.org) | CLI (Homebrew) | Python | R | Java | Node.js |
|------|------|------|---|---|---|---|---|
| [autocomplete](#docs:extensions:autocomplete) | yes | yes | | | | |
| [excel](#docs:extensions:excel) | yes | | | | | |
| [fts](#docs:extensions:full_text_search) | yes | | yes | | | |
| [httpfs](#docs:extensions:httpfs:overview) | | | | | | |
| [icu](#docs:extensions:icu) | yes | yes | yes | | yes | yes |
| [json](#docs:data:json:overview) | yes | yes | yes | | yes | yes |
| [parquet](#docs:data:parquet:overview) | yes | yes | yes | yes | yes | yes |
| [tpcds](#docs:extensions:tpcds) | | | yes | | | |
| [tpch](#docs:extensions:tpch) | yes | | yes | | | |
The [jemalloc](#docs:extensions:jemalloc) extension's availability is based on the operating system.
Starting with version 0.10.1, `jemalloc` is a built-in extension on Linux x86_64 (AMD64) distributions, while it will be optionally available on Linux ARM64 distributions and on macOS (via compiling from source).
On Windows, it is not available. | 398 | [
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|
Extensions | Community Extensions | DuckDB recently launched a [Community Extensions repository](https://github.com/duckdb/community-extensions).
For details, see the [announcement blog post](https://duckdb.org/2024/07/05/community-extensions). | 48 | [
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||
Extensions | Community Extensions | User Experience | We are going to use the [`h3` extension](https://github.com/isaacbrodsky/h3-duckdb) as our example.
This extension implements [hierarchical hexagonal indexing](https://github.com/uber/h3) for geospatial data.
Using the DuckDB Community Extensions repository, you can install and load the `h3` extension as follows:
```sql
INSTALL h3 FROM community;
LOAD h3;
```
Then, you can instantly start using it. Note that the sample data is 500 MB:
```sql
SELECT
h3_latlng_to_cell(pickup_latitude, pickup_longitude, 9) AS cell_id,
h3_cell_to_boundary_wkt(cell_id) AS boundary,
count() AS cnt
FROM read_parquet('https://blobs.duckdb.org/data/yellow_tripdata_2010-01.parquet')
GROUP BY cell_id
HAVING cnt > 10;
```
On load, the extensionβs signature is checked, both to ensure platform and versions are compatible, and to verify that the source of the binary is the community extensions repository. Extensions are built, signed and distributed for Linux, macOS, Windows, and WebAssembly. This allows extensions to be available to any DuckDB client using version 1.0.0 and upcoming versions.
For more details, see the [`h3` extensionβs documentation](#community_extensions:extensions:h3). | 298 | [
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|
Extensions | Community Extensions | Developer Experience | From the developerβs perspective, the Community Extensions repository performs the steps required for publishing extensions, including building the extensions for all relevant [platforms](#docs:dev:building:platforms), signing the extension binaries and serving them from the repository.
For the [maintainer of `h3`](https://github.com/isaacbrodsky/), the publication process required performing the following steps:
1. Sending a PR with a metadata file `description.yml` contains the description of the extension:
```yaml
extension:
name: h3
description: Hierarchical hexagonal indexing for geospatial data
version: 1.0.0
language: C++
build: cmake
license: Apache-2.0
maintainers:
- isaacbrodsky
repo:
github: isaacbrodsky/h3-duckdb
ref: 3c8a5358e42ab8d11e0253c70f7cc7d37781b2ef
```
2. The CI will build and test the extension. The checks performed by the CI are aligned with the [`extension-template` repository](https://github.com/duckdb/extension-template), so iterations can be done independently.
3. Wait for approval from the DuckDB Community Extension repositoryβs maintainers and for the build process to complete. | 279 | [
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|
Extensions | Community Extensions | Security Considerations | See the [Securing Extensions page](#docs:operations_manual:securing_duckdb:securing_extensions) for details. | 27 | [
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|
Extensions | Community Extensions | List of Community Extensions | See the [DuckDB Community Extensions repository site](https://duckdb.org/community_extensions). | 19 | [
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|
Extensions | Working with Extensions | Platforms | Extension binaries must be built for each platform. Pre-built binaries are distributed for several platforms (see below).
For platforms where packages for certain extensions are not available, users can build them from source and [install the resulting binaries manually](#::installing-an-extension-from-an-explicit-path).
All official extensions are distributed for the following platforms.
<div class="narrow_table"></div>
| Platform name | Operating system | Architecture | CPU types | Used by |
|--------------------|------------------|-----------------|---------------------------------|------------------------------|
| `linux_amd64` | Linux | x86_64 (AMD64) | | Node.js packages, etc. |
| `linux_amd64_gcc4` | Linux | x86_64 (AMD64) | | Python packages, CLI, etc. |
| `linux_arm64` | Linux | AArch64 (ARM64) | AWS Graviton, Snapdragon, etc. | all packages |
| `osx_amd64` | macOS | x86_64 (AMD64) | Intel | all packages |
| `osx_arm64` | macOS | AArch64 (ARM64) | Apple Silicon M1, M2, etc. | all packages |
| `windows_amd64` | Windows | x86_64 (AMD64) | Intel, AMD, etc. | all packages |
> For some Linux ARM distributions (e.g., Python), two different binaries are distributed. These target either the `linux_arm64` or `linux_arm64_gcc4` platforms. Note that extension binaries are distributed for the first, but not the second. Effectively that means that on these platforms your glibc version needs to be 2.28 or higher to use the distributed extension binaries.
Some extensions are distributed for the following platforms:
* `windows_amd64_mingw`
* `wasm_eh` and `wasm_mvp` (see [DuckDB-Wasm's extensions](#docs:api:wasm:extensions))
For platforms outside the ones listed above, we do not officially distribute extensions (e.g., `linux_arm64_android`, `linux_arm64_gcc4`).
#### Sharing Extensions between Clients {#docs:extensions:working_with_extensions::sharing-extensions-between-clients}
The shared installation location allows extensions to be shared between the client APIs _of the same DuckDB version_, as long as they share the same `platform` or ABI. For example, if an extension is installed with version 0.10.0 of the CLI client on macOS, it is available from the Python, R, etc. client libraries provided that they have access to the user's home directory and use DuckDB version 0.10.0. | 601 | [
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|
Extensions | Working with Extensions | Extension Repositories | By default, DuckDB extensions are installed from a single repository containing extensions built and signed by the core
DuckDB team. This ensures the stability and security of the core set of extensions. These extensions live in the default `core` repository
which points to `http://extensions.duckdb.org`.
Besides the core repository, DuckDB also supports installing extensions from other repositories. For example, the `core_nightly` repository contains nightly builds for core extensions
that are built for the latest stable release of DuckDB. This allows users to try out new features in extensions before they are officially published.
#### Installing Extensions from a Repository {#docs:extensions:working_with_extensions::installing-extensions-from-a-repository}
To install extensions from the default repository (default repository: `core`):
```sql
INSTALL httpfs;
```
To explicitly install an extension from the core repository, run either of:
```sql
INSTALL httpfs FROM core;
```
Or:
```sql
INSTALL httpfs FROM 'http://extensions.duckdb.org';
```
To install an extension from the core nightly repository:
```sql
INSTALL spatial FROM core_nightly;
```
Or:
```sql
INSTALL spatial FROM 'http://nightly-extensions.duckdb.org';
```
To install an extensions from a custom repository unknown to DuckDB:
```sql
INSTALL β¨custom_extensionβ© FROM 'https://my-custom-extension-repository';
```
Alternatively, the `custom_extension_repository` setting can be used to change the default repository used by DuckDB:
```sql
SET custom_extension_repository = 'http://nightly-extensions.duckdb.org';
```
While any URL or local path can be used as a repository, DuckDB currently contains the following predefined repositories:
<div class="narrow_tabl"></div>
| Alias | URL | Description |
|:----------------------|:-----------------------------------------|:---------------------------------------------------------------------------------------|
| `core` | `http://extensions.duckdb.org` | DuckDB core extensions |
| `core_nightly` | `http://nightly-extensions.duckdb.org` | Nightly builds for `core` |
| `community` | `http://community-extensions.duckdb.org` | DuckDB community extensions |
| `local_build_debug` | `./build/debug/repository` | Repository created when building DuckDB from source in debug mode (for development) |
| `local_build_release` | `./build/release/repository` | Repository created when building DuckDB from source in release mode (for development) |
#### Working with Multiple Repositories {#docs:extensions:working_with_extensions::working-with-multiple-repositories}
When working with extensions from different repositories, especially mixing `core` and `core_nightly`, it is important to keep track of the origins
and version of the different extensions. For this reason, DuckDB keeps track of this in the extension installation metadata. For example:
```sql
INSTALL httpfs FROM core;
INSTALL aws FROM core_nightly;
SELECT extension_name, extension_version, installed_from, install_mode FROM duckdb_extensions();
```
This outputs:
<div class="narrow_table monospace_table"></div>
| extensions_name | extensions_version | installed_from | install_mode |
|:----------------|:-------------------|:---------------|:-------------|
| httpfs | 62d61a417f | core | REPOSITORY |
| aws | 42c78d3 | core_nightly | REPOSITORY |
| ... | ... | ... | ... |
#### Creating a Custom Repository {#docs:extensions:working_with_extensions::creating-a-custom-repository}
A DuckDB repository is an HTTP, HTTPS, S3, or local file based directory that serves the extensions files in a specific structure.
This structure is described in the [βDownloading Extensions Directly from S3β section](#::downloading-extensions-directly-from-s3), and is the same
for local paths and remote servers, for example:
```text
base_repository_path_or_url
βββ v1.0.0
βββ osx_arm64
βββ autocomplete.duckdb_extension
βββ httpfs.duckdb_extension
βββ icu.duckdb_extension
βββ inet.duckdb_extension
βββ json.duckdb_extension
βββ parquet.duckdb_extension
βββ tpcds.duckdb_extension
βββ tpcds.duckdb_extension
βββ tpch.duckdb_extension
```
See the [`extension-template` repository](https://github.com/duckdb/extension-template/) for all necessary code and scripts
to set up a repository.
When installing an extension from a custom repository, DuckDB will search for both a gzipped and non-gzipped version. For example:
```sql
INSTALL icu FROM 'β¨custom repositoryβ©';
```
The execution of this statement will first look `icu.duckdb_extension.gz`, then `icu.duckdb_extension` in the repository's directory structure.
If the custom repository is served over HTTPS or S3, the [`httpfs` extension](#docs:extensions:httpfs:overview) is required. DuckDB will attempt to [autoload](#docs:extensions:overview::autoloading-extensions)
the `httpfs` extension when an installation over HTTPS or S3 is attempted. | 1,158 | [
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|
Extensions | Working with Extensions | Force Installing to Upgrade Extensions | When DuckDB installs an extension, it is copied to a local directory to be cached and avoid future network traffic.
Any subsequent calls to `INSTALL β¨extension_nameβ©` will use the local version instead of downloading the extension again. To force re-downloading the extension, run:
```sql
FORCE INSTALL extension_name;
```
Force installing can also be used to overwrite an extension with an extension with the same name from another repository,
For example, first, `spatial` is installed from the core repository:
```sql
INSTALL spatial;
```
Then, to overwrite this installation with the `spatial` extension from the `core_nightly` repository:
```sql
FORCE INSTALL spatial FROM core_nightly;
``` | 149 | [
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|
Extensions | Working with Extensions | Alternative Approaches to Loading and Installing Extensions | #### Downloading Extensions Directly from S3 {#docs:extensions:working_with_extensions::downloading-extensions-directly-from-s3}
Downloading an extension directly can be helpful when building a [Lambda service](https://aws.amazon.com/pm/lambda/) or container that uses DuckDB.
DuckDB extensions are stored in public S3 buckets, but the directory structure of those buckets is not searchable.
As a result, a direct URL to the file must be used.
To download an extension file directly, use the following format:
```text
http://extensions.duckdb.org/vβ¨duckdb_versionβ©/β¨platform_nameβ©/β¨extension_nameβ©.duckdb_extension.gz
```
For example:
```text
http://extensions.duckdb.org/v{{ site.currentduckdbversion }}/windows_amd64/json.duckdb_extension.gz
```
#### Installing an Extension from an Explicit Path {#docs:extensions:working_with_extensions::installing-an-extension-from-an-explicit-path}
`INSTALL` can be used with the path to a `.duckdb_extension` file:
```sql
INSTALL 'path/to/httpfs.duckdb_extension';
```
Note that compressed `.duckdb_extension.gz` files need to be decompressed beforehand. It is also possible to specify remote paths.
#### Loading an Extension from an Explicit Path {#docs:extensions:working_with_extensions::loading-an-extension-from-an-explicit-path}
`LOAD` can be used with the path to a `.duckdb_extension`.
For example, if the file was available at the (relative) path `path/to/httpfs.duckdb_extension`, you can load it as follows:
```sql
LOAD 'path/to/httpfs.duckdb_extension';
```
This will skip any currently installed extensions and load the specified extension directly.
Note that using remote paths for compressed files is currently not possible.
#### Building and Installing Extensions from Source {#docs:extensions:working_with_extensions::building-and-installing-extensions-from-source}
For building and installing extensions from source, see the [building guide](#docs:dev:building:build_instructions::building-and-installing-extensions-from-source).
#### Statically Linking Extensions {#docs:extensions:working_with_extensions::statically-linking-extensions}
To statically link extensions, follow the [developer documentation's βUsing extension config filesβ section](https://github.com/duckdb/duckdb/blob/main/extension/README.md#using-extension-config-files). | 521 | [
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|
Extensions | Working with Extensions | In-Tree vs. Out-of-Tree | Originally, DuckDB extensions lived exclusively in the DuckDB main repository, `github.com/duckdb/duckdb`. These extensions are called in-tree. Later, the concept
of out-of-tree extensions was added, where extensions where separated into their own repository, which we call out-of-tree.
While from a user's perspective, there are generally no noticeable differences, there are some minor differences related to versioning:
* in-tree extensions use the version of DuckDB instead of having their own version
* in-tree extensions do not have dedicated release notes, their changes are reflected in the regular [DuckDB release notes](https://github.com/duckdb/duckdb/releases)
* core out-of tree extensions tend to live in a repository in `github.com/duckdb/duckdb_β¨ext_nameβ©` but the name may vary. See the [full list](#docs:extensions:core_extensions) of core extensions for details. | 195 | [
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|
Extensions | Working with Extensions | Limitations | DuckDB's extension mechanism has the following limitations:
* Once loaded, an extension cannot be reinstalled.
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|
Extensions | Versioning of Extensions | Extension Versioning | Most software has some sort of version number. Version numbers serve a few important goals:
* Tie a binary to a specific state of the source code
* Allow determining the expected feature set
* Allow determining the state of the APIs
* Allow efficient processing of bug reports (e.g., bug `#1337` was introduced in version `v3.4.5` )
* Allow determining chronological order of releases (e.g., version `v1.2.3` is older than `v1.2.4`)
* Give an indication of expected stability (e.g., `v0.0.1` is likely not very stable, whereas `v13.11.0` probably is stable)
Just like [DuckDB itself](#docs:dev:release_calendar), DuckDB extensions have their own version number. To ensure consistent semantics
of these version numbers across the various extensions, DuckDB's [Core Extensions](#docs:extensions:core_extensions) use
a versioning scheme that prescribes how extensions should be versioned. The versioning scheme for Core Extensions is made up of 3 different stability levels: **unstable**, **pre-release**, and **stable**.
Let's go over each of the 3 levels and describe their format:
#### Unstable Extensions {#docs:extensions:versioning_of_extensions::unstable-extensions}
Unstable extensions are extensions that can't (or don't want to) give any guarantees regarding their current stability,
or their goals of becoming stable. Unstable extensions are tagged with the **short git hash** of the extension.
For example, at the time of writing this, the version of the `vss` extension is an unstable extension of version `690bfc5`.
What to expect from an extension that has a version number in the **unstable** format?
* The state of the source code of the extension can be found by looking up the hash in the extension repository
* Functionality may change or be removed completely with every release
* This extension's API could change with every release
* This extension may not follow a structured release cycle, new (breaking) versions can be pushed at any time
#### Pre-Release Extensions {#docs:extensions:versioning_of_extensions::pre-release-extensions}
Pre-release extensions are the next step up from Unstable extensions. They are tagged with version in the **[SemVer](https://semver.org/)** format, more specifically, those in the `v0.y.z` format.
In semantic versioning, versions starting with `v0` have a special meaning: they indicate that the more strict semantics of regular (` >v1.0.0`) versions do not yet apply. It basically means that an extensions is working
towards becoming a stable extension, but is not quite there yet.
For example, at the time of writing this, the version of the `delta` extension is a pre-release extension of version `v0.1.0`.
What to expect from an extension that has a version number in the **pre-release** format?
* The extension is compiled from the source code corresponding to the tag.
* Semantic Versioning semantics apply. See the [Semantic Versioning](https://semver.org/) specification for details.
* The extension follows a release cycle where new features are tested in nightly builds before being grouped into a release and pushed to the `core` repository.
* Release notes describing what has been added each release should be available to make it easy to understand the difference between versions.
#### Stable Extensions {#docs:extensions:versioning_of_extensions::stable-extensions}
Stable extensions are the final step of extension stability. This is denoted by using a **stable SemVer** of format `vx.y.z` where `x>0`.
For example, at the time of writing this, the version of the `parquet` extension is a stable extension of version `v1.0.0`.
What to expect from an extension that has a version number in the **stable** format? Essentially the same as pre-release extensions, but now the more
strict SemVer semantics apply: the API of the extension should now be stable and will only change in backwards incompatible ways when the major version is bumped.
See the SemVer specification for details | 894 | [
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|
Extensions | Versioning of Extensions | Release Cycle of Pre-Release and Stable Core Extensions | In general for extensions the release cycle depends on their stability level. **unstable** extensions are often in
sync with DuckDB's release cycle, but may also be quietly updated between DuckDB releases. **pre-release** and **stable**
extensions follow their own release cycle. These may or may not coincide with DuckDB releases. To find out more about the release cycle of a specific
extension, refer to the documentation or GitHub page of the respective extension. Generally, **pre-release** and **stable** extensions will document
their releases as GitHub releases, an example of which you can see in the [delta extension](https://github.com/duckdb/duckdb_delta/releases).
Finally, there is a small exception: All [in-tree](#docs:extensions:working_with_extensions::in-tree-vs-out-of-tree) extensions simply
follow DuckDB's release cycle. | 179 | [
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|
Extensions | Versioning of Extensions | Nightly Builds | Just like DuckDB itself, DuckDB's core extensions have nightly or dev builds that can be used to try out features before they are officially released.
This can be useful when your workflow depends on a new feature, or when you need to confirm that your stack is compatible with the upcoming version.
Nightly builds for extensions are slightly complicated due to the fact that currently DuckDB extensions binaries are tightly bound to a single DuckDB version. Because of this tight connection,
there is a potential risk for a combinatory explosion. Therefore, not all combinations of nightly extension build and nightly DuckDB build are available.
In general, there are 2 ways of using nightly builds: using a nightly DuckDB build and using a stable DuckDB build. Let's go over the differences between the two:
#### From Stable DuckDB {#docs:extensions:versioning_of_extensions::from-stable-duckdb}
In most cases, user's will be interested in a nightly build of a specific extension, but don't necessarily want to switch to using the nightly build of DuckDB itself. This allows using a specific bleeding-edge
feature while limiting the exposure to unstable code.
To achieve this, Core Extensions tend to regularly push builds to the [`core_nightly` repository](#docs:extensions:working_with_extensions::extension-repositories). Let's look at an example:
First we install a [**stable DuckDB build**](https://duckdb.org/docs/installation/index.html).
Then we can install and load a **nightly** extension like this:
```sql
INSTALL aws FROM core_nightly;
LOAD aws;
```
In this example we are using the latest **nightly** build of the aws extension with the latest **stable** version of DuckDB.
#### From Nightly DuckDB {#docs:extensions:versioning_of_extensions::from-nightly-duckdb}
When DuckDB CI produces a nightly binary of DuckDB itself, the binaries are distributed with a set of extensions that are pinned at a specific version. This extension version will be tested for that specific build of DuckDB, but might not be the latest dev build. Let's look at an example:
First, we install a [**nightly DuckDB build**](https://duckdb.org/docs/installation/index.html). Then, we can install and load the `aws` extension as expected:
```sql
INSTALL aws;
LOAD aws;
``` | 500 | [
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|
Extensions | Versioning of Extensions | Updating Extensions | DuckDB has a dedicated statement that will automatically update all extensions to their latest version. The output will
give the user information on which extensions were updated to/from which version. For example:
```sql
UPDATE EXTENSIONS;
```
<div class="narrow_table"></div>
| extension_name | repository | update_result | previous_version | current_version |
|:---------------|:-------------|:----------------------|:-----------------|:----------------|
| httpfs | core | NO_UPDATE_AVAILABLE | 70fd6a8a24 | 70fd6a8a24 |
| delta | core | UPDATED | d9e5cc1 | 04c61e4 |
| azure | core | NO_UPDATE_AVAILABLE | 49b63dc | 49b63dc |
| aws | core_nightly | NO_UPDATE_AVAILABLE | 42c78d3 | 42c78d3 |
Note that DuckDB will look for updates in the source repository for each extension. So if an extension was installed from
`core_nightly`, it will be updated with the latest nightly build.
The update statement can also be provided with a list of specific extensions to update:
```sql
UPDATE EXTENSIONS (httpfs, azure);
```
<div class="narrow_table"></div>
| extension_name | repository | update_result | previous_version | current_version |
|:---------------|:-------------|:----------------------|:-----------------|:----------------|
| httpfs | core | NO_UPDATE_AVAILABLE | 70fd6a8a24 | 70fd6a8a24 |
| azure | core | NO_UPDATE_AVAILABLE | 49b63dc | 49b63dc | | 384 | [
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Extensions | Versioning of Extensions | Target DuckDB Version | Currently, when extensions are compiled, they are tied to a specific version of DuckDB. What this means is that, for example, an extension binary compiled for v0.10.3 does not work for v1.0.0. In most cases, this will not cause any issues and is fully transparent; DuckDB will automatically ensure it installs the correct binary for its version. For extension developers, this means that they must ensure that new binaries are created whenever a new version of DuckDB is released. However, note that DuckDB provides an [extension template](https://github.com/duckdb/extension-template) that makes this fairly simple. | 132 | [
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|
Extensions | Arrow Extension | The `arrow` extension implements features for using [Apache Arrow](https://arrow.apache.org/), a cross-language development platform for in-memory analytics. | 30 | [
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||
Extensions | Arrow Extension | Installing and Loading | The `arrow` extension will be transparently autoloaded on first use from the official extension repository.
If you would like to install and load it manually, run:
```sql
INSTALL arrow;
LOAD arrow;
``` | 44 | [
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] |
|
Extensions | Arrow Extension | Functions | <div class="narrow_table"></div>
| Function | Type | Description |
|--|----|-------|
| `to_arrow_ipc` | Table in-out function | Serializes a table into a stream of blobs containing Arrow IPC buffers |
| `scan_arrow_ipc` | Table function | Scan a list of pointers pointing to Arrow IPC buffers | | 70 | [
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|
Extensions | AutoComplete Extension | The `autocomplete` extension adds supports for autocomplete in the [CLI client](#docs:api:cli:overview).
The extension is shipped by default with the CLI client. | 35 | [
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||
Extensions | AutoComplete Extension | Behavior | For the behavior of the `autocomplete` extension, see the [documentation of the CLI client](#docs:api:cli:autocomplete). | 28 | [
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|
Extensions | AutoComplete Extension | Functions | <div class="narrow_table"></div>
| Function | Description |
|:----------------------------------|:-----------------------------------------------------|
| `sql_auto_complete(query_string)` | Attempts autocompletion on the given `query_string`. | | 47 | [
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|
Extensions | AutoComplete Extension | Example | ```sql
SELECT *
FROM sql_auto_complete('SEL');
```
Returns:
<div class="narrow_table"></div>
| suggestion | suggestion_start |
|-------------|------------------|
| SELECT | 0 |
| DELETE | 0 |
| INSERT | 0 |
| CALL | 0 |
| LOAD | 0 |
| CALL | 0 |
| ALTER | 0 |
| BEGIN | 0 |
| EXPORT | 0 |
| CREATE | 0 |
| PREPARE | 0 |
| EXECUTE | 0 |
| EXPLAIN | 0 |
| ROLLBACK | 0 |
| DESCRIBE | 0 |
| SUMMARIZE | 0 |
| CHECKPOINT | 0 |
| DEALLOCATE | 0 |
| UPDATE | 0 |
| DROP | 0 | | 213 | [
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|
Extensions | AWS Extension | The `aws` extension adds functionality (e.g., authentication) on top of the `httpfs` extension's [S3 capabilities](#docs:extensions:httpfs:overview::s3-api), using the AWS SDK.
> **Warning. ** In most cases, you will not need to explicitly interact with the `aws` extension.
> It will automatically be invoked whenever you use DuckDB's [S3 Secret functionality](#docs:sql:statements:create_secret).
> See the [`httpfs` extension's S3 capabilities](#docs:extensions:httpfs:overview::s3) for instructions. | 126 | [
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Subsets and Splits