F.36. pg_pathman
The pg_pathman is a Postgres Pro extension that provides an optimized partitioning solution for large and distributed databases. Using pg_pathman, you can:
Partition large databases without downtime.
Speed up query execution for partitioned tables.
Manage existing partitions and add new partitions on the fly.
Add foreign tables as partitions.
Join partitioned tables for read and write operations.
The extension is compatible with Postgres Pro 9.5 or higher.
F.36.1. Installation and Setup
The pg_pathman extension is included into the Postgres Pro. Once you have Postgres Pro installed, complete the following steps to enable pg_pathman:
Add
pg_pathmanto theshared_preload_librariesvariable in thepostgresql.conffile:shared_preload_libraries = 'pg_pathman'
Important
pg_pathmanmay have conflicts with other extensions that use the same hook functions. For example,pg_pathmanmay interfere with thepg_stat_statementsextension as they both useProcessUtility_hook. To avoid such issues,pg_pathmanmust always be the last in the list of libraries:shared_preload_libraries = 'pg_stat_statements, pg_pathman'Restart the Postgres Pro instance for the settings to take effect.
Create the
pg_pathmanextension using the following query:CREATE EXTENSION pg_pathman;
Once pg_pathman is enabled, you can start partitioning tables.
Tip
You can also build pg_pathman from source code by executing the following command in the pg_pathman directory:
make install USE_PGXS=1
When this operation is complete, follow the steps described above to complete the setup.
In addition, do not forget to set the PG_CONFIG variable if you want to test pg_pathman on a custom build of Postgres Pro. For details, see Building and Installing PostgreSQL Extension Modules.
You can toggle pg_pathman or its specific custom nodes on and off using GUC variables. For details, see Section F.36.5.1.
If you want to permanently disable pg_pathman for a previously partitioned table, use the disable_pathman_for() function:
SELECT disable_pathman_for('range_rel');
All sections and data will remain unchanged and will be handled by the standard Postgres Pro inheritance mechanism.
F.36.1.1. Updating pg_pathman
If you already have a previous version of pg_pathman installed, complete the following steps to upgrade to a newer version:
Install Postgres Pro.
Restart your Postgres Pro cluster.
Execute the following queries:
ALTER EXTENSION pg_pathman UPDATE TO
version; SET pg_pathman.enable = t;where
versionis thepg_pathmanversion number, such as 1.3.
F.36.2. Usage
Contents
Choosing Partitioning Strategies
Running Non-Blocking Data Migration
Partitioning by a Single Expression
As your database grows, indexing mechanisms may become inefficient and cause high latency as you run queries. To improve performance, ensure scalability, and optimize database administration processes you can use partitioning — splitting a large table into smaller pieces, with each row moved to a single partition according to the partitioning key. Postgres Pro supports partitioning via table inheritance. Each partition is created as a child table with a CHECK constraint. For example:
CREATE TABLE test (id SERIAL PRIMARY KEY, title TEXT); CREATE TABLE test_1 (CHECK ( id >= 100 AND id < 200 )) INHERITS (test); CREATE TABLE test_2 (CHECK ( id >= 200 AND id < 300 )) INHERITS (test);
However, too many partitions may cause significant planning overhead as the query planner has to perform an exhaustive search and check constraints on each partition to build a query plan. The pg_pathman extension resolves this issue with optimized planning algorithms and partition functions based on the internal structure of the partitioned tables. For details on pg_pathman implementation specifics, see Section F.36.4.
F.36.2.1. Choosing Partitioning Strategies
The pg_pathman extension supports the following partitioning strategies:
Hash — maps rows to partitions using a generic hash function. Choose this strategy if most of your queries will be of the exact-match type.
Range — maps rows to partitions based on partitioning key ranges assigned to each partition. Choose this strategy if your database contains numeric data that you are likely to query or manage by ranges. For example, you may want to query historical data by years, or review experiment results by specific numeric ranges. To achieve performance gains,
pg_pathmanuses the binary search algorithm.
By default, pg_pathman migrates all data from the parent table to the newly created partitions at once (blocking partitioning). This approach enables you to restructure the table in a single transaction, but may cause downtime if you have a lot of data. If it is critical to avoid downtime, you can use concurrent partitioning. In this case, pg_pathman writes all the updates to the newly created partitions, but keeps the original data in the parent table until you explicitly migrate it. This enables you to partition large databases without downtime, as you can choose convenient time for migration and copy data in small batches without blocking other transactions. For details on concurrent partitioning, see Section F.36.2.2.
F.36.2.1.1. Setting up Hash Partitioning
To perform hash partitioning with pg_pathman, run the create_hash_partitions() function:
create_hash_partitions(relation REGCLASS,
attribute TEXT,
partitions_count INTEGER,
partition_data BOOLEAN DEFAULT TRUE,
partition_names TEXT[] DEFAULT NULL,
tablespaces TEXT[] DEFAULT NULL)
The pg_pathman module creates the specified number of partitions based on the hash function. Optionally, you can specify partition names and tablespaces by setting partition_names and tablespaces options, respectively.
You cannot add or remove partitions after the parent table is split. If required, you can replace the specified partition with another table:
replace_hash_partition(old_partition REGCLASS,
new_partition REGCLASS,
lock_parent BOOL DEFAULT TRUE);
When set to true, lock_parent parameter will prevent any INSERT/UPDATE/ALTER TABLE queries to parent table.
If you omit the optional partition_data parameter or set it to true, all the data from the parent table gets migrated to partitions. The pg_pathman module blocks the table for other transactions until data migration completes. To avoid downtime, you can set the partition_data parameter to false and later use the partition_table_concurrently() function to migrate your data to partitions without blocking other queries. For details, see the Section F.36.2.2.
F.36.2.1.2. Setting up Range Partitioning
The pg_pathman module provides the create_range_partitions() for range partitioning. This function creates partitions based on the specified interval and the initial partitioning key value. New partitions are created automatically when you insert data outside of the already covered range.
create_range_partitions(relation REGCLASS,
expression TEXT,
start_value ANYELEMENT,
p_interval ANYELEMENT | INTERVAL,
p_count INTEGER DEFAULT NULL,
partition_data BOOLEAN DEFAULT TRUE)
The pg_pathman module creates partitions based on the specified parameters. If you omit the optional p_count parameter, pg_pathman calculates the required number of partitions based on the specified start value and interval. If you insert new data outside of the existing partition range, pg_pathman creates new partitions automatically, keeping the specified interval. This approach ensures that all partitions are of the same size, which can improve query performance and facilitate database management.
Alternatively, you can specify an array defining the bounds of partitions to be created using the bounds parameter:
create_range_partitions(relation REGCLASS,
expression TEXT,
bounds ANYARRAY,
partition_names TEXT[] DEFAULT NULL,
tablespaces TEXT[] DEFAULT NULL,
partition_data BOOLEAN DEFAULT TRUE)
If required, you can also use partition management functions to add partitions manually. For example, if there is a gap between the created partitions, pg_pathman cannot fill it with a new partition in an automated mode.
By default, all the data from the parent table gets migrated to the specified number of partitions. The pg_pathman module blocks the table for other transactions until data migration completes. To avoid downtime, you can set the partition_data parameter to false and later use the partition_table_concurrently() function to migrate your data to partitions without blocking other queries. For details, see the Section F.36.2.2.
F.36.2.2. Running Non-Blocking Data Migration
If it is critical to avoid downtime, you can perform concurrent partitioning by setting the partition_data parameter of the partitioning function to false. In this case, pg_pathman creates empty partitions, keeping all the original data in the parent table. At the same time, all the database updates are written to the newly created partitions. You can later migrate the original data to partitions without blocking other queries using the partition_table_concurrently() function:
partition_table_concurrently(relation REGCLASS,
batch_size INTEGER DEFAULT 1000,
sleep_time FLOAT8 DEFAULT 1.0)
where:
relationis the parent table.batch_sizeis the number of rows to copy from the parent table to partitions at a time. You can set this parameter to any integer value from 1 to 10000.sleep_timeis the time interval between migration attempts, in seconds.
The pg_pathman module starts a background worker to move the data from the parent table to partitions in small batches of the specified batch_size. If one or more rows in the batch are locked by other queries, pg_pathman waits for the specified sleep_time and tries again, up to 60 times. You can monitor the migration process in the pathman_concurrent_part_tasks view that shows the number of rows migrated so far:
[user]postgres: select * from pathman_concurrent_part_tasks ; userid | pid | dbid | relid | processed | status --------+-------+-------+-------+-----------+--------- user | 20012 | 12413 | test | 334000 | working (1 row)
If you need to stop data migration, run the stop_concurrent_part_task() function at any time:
SELECT stop_concurrent_part_task(relation REGCLASS);
pg_pathman completes the migration of the current batch and terminates the migration process.
Tip
When pg_pathman migrates all the data from the parent table, you can exclude the parent table from the query plan. See the set_enable_parent() function description for details.
F.36.2.3. Partitioning by a Single Expression
For both range and hash partitioning strategies, pg_pathman supports partitioning by expression that returns a single scalar value. The partitioning expression can reference a table column, as well as calculate the partitioning key based on one or more column values.
Tip
If you would like to partition a table by a tuple, see Section F.36.2.4.
To partition a table by expression, use pg_pathman partitioning functions. The partitioning expression must satisfy the following conditions:
Expression must reference at least one column of the partitioned table.
All referenced columns must be marked as
NOT NULL.Expression cannot reference system attributes, such as
oid,xmin,xmax, etc.Expression cannot include subqueries.
All functions used by expression must be marked as
IMMUTABLE.
As the expression can return a value of virtually any type, make sure to convert it to the type you need for partitioning.
To access a partition, you must use the exact expression used for partitioning. Otherwise, pg_pathman cannot optimize the query. You can view the partitioning expression for each partitioned table in the pathman_config table.
F.36.2.3.1. Examples
Suppose you have the test table that stores some jsonb data:
CREATE TABLE test(col jsonb not null);
INSERT INTO test
SELECT format('{"key": %s, "date": "%s", "value": "%s"}',
i, current_date, md5(i::text))::jsonb
FROM generate_series(1, 10000 * 10) as g(i);
To partition this data by range of the key value, you need to extract this value from the jsonb object and convert it to a numeric type, such as bigint:
SELECT create_range_partitions('test', '(col->>''key'')::bigint', 1, 10000, 10);
pg_pathman splits the parent table into ten partitions, with each partition storing 10000 rows:
SELECT * FROM pathman_partition_list; parent | partition | parttype | expr | range_min | range_max --------+-----------+----------+---------------------------------+-----------+----------- test | test_1 | 2 | ((col ->> 'key'::text))::bigint | 1 | 10001 test | test_2 | 2 | ((col ->> 'key'::text))::bigint | 10001 | 20001 test | test_3 | 2 | ((col ->> 'key'::text))::bigint | 20001 | 30001 test | test_4 | 2 | ((col ->> 'key'::text))::bigint | 30001 | 40001 test | test_5 | 2 | ((col ->> 'key'::text))::bigint | 40001 | 50001 test | test_6 | 2 | ((col ->> 'key'::text))::bigint | 50001 | 60001 test | test_7 | 2 | ((col ->> 'key'::text))::bigint | 60001 | 70001 test | test_8 | 2 | ((col ->> 'key'::text))::bigint | 70001 | 80001 test | test_9 | 2 | ((col ->> 'key'::text))::bigint | 80001 | 90001 test | test_10 | 2 | ((col ->> 'key'::text))::bigint | 90001 | 100001 (10 rows)
F.36.2.4. Partitioning by Composite Key
Using pg_pathman, you can also perform range partitioning by composite key. A composite key consists of two or more comma-separated values, which can be columns or expressions extracting the values from the table. The expressions defining the composite key must satisfy the conditions described in Section F.36.2.3.
Although pg_pathman does not support automatic partition creation by composite key, you can add partitions using the add_range_partition() function. A typical workflow is as follows:
Enable automatic partition naming for your table by running the
create_naming_sequence()function.Create a composite partitioning key.
Register a table you are going to partition with
pg_pathmanusing theadd_to_pathman_config()function.Add a partition based on the defined composite partitioning key using the
add_range_partition()function.
F.36.2.4.1. Examples
Suppose you have the test table that stores some temporal data:
CREATE TABLE test (logdate date not null, comment text);
To partition this data by month and year, you have to create a composite key:
CREATE TYPE test_key AS (year float8, month float8);
To enable automatic partition naming, run the create_naming_sequence() function passing the table name as an argument:
SELECT create_naming_sequence('test');
Register the test table with pg_pathman, specifying the partitioning key you are going to use:
SELECT add_to_pathman_config('test',
'( extract(year from logdate),
extract(month from logdate) )::test_key',
NULL);
Create a partition that includes all the data in the range of ten years, starting from January of the current year:
SELECT add_range_partition('test',
(extract(year from current_date), 1)::test_key,
(extract(year from current_date + '10 years'::interval), 1)::test_key);
F.36.2.5. Managing Partitions
pg_pathman provides multiple functions for easy partition management. For details, see Section F.36.5.3.4.
F.36.3. Examples
F.36.3.1. Common Tips
You can add
partitioncolumn containing the names of the underlying partitions using the system attribute calledtableoid:SELECT tableoid::regclass AS partition, * FROM partitioned_table;
Though indices on a parent table are not particularly useful (since the parent table is supposed to be empty), they act as prototypes for indices on partitions. For each index on the parent table,
pg_pathmancreates a similar index on each partition.All running concurrent partitioning tasks can be listed using the
pathman_concurrent_part_tasksview:SELECT * FROM pathman_concurrent_part_tasks; userid | pid | dbid | relid | processed | status --------+------+-------+-------+-----------+--------- user | 7367 | 16384 | test | 472000 | working (1 row)
The
pathman_partition_listin conjunction withdrop_range_partition()can be used to drop range partitions in a more flexible way compared toDROP TABLE:SELECT drop_range_partition(partition, false) /* move data to parent */ FROM pathman_partition_list WHERE parent = 'part_test'::regclass AND range_min::int < 500; NOTICE: 1 rows copied from part_test_11 NOTICE: 100 rows copied from part_test_1 NOTICE: 100 rows copied from part_test_2 drop_range_partition ---------------------- dummy_test_11 dummy_test_1 dummy_test_2 (3 rows)
F.36.3.2. Hash Partitioning
Consider an example of hash partitioning. First create a table with an integer column:
CREATE TABLE items ( id SERIAL PRIMARY KEY, name TEXT, code BIGINT); INSERT INTO items (id, name, code) SELECT g, md5(g::text), random() * 100000 FROM generate_series(1, 100000) as g;
Now run the create_hash_partitions() function with appropriate arguments:
SELECT create_hash_partitions('items', 'id', 100);
This will create new partitions and move the data from the parent table to partitions.
Here is an example of the query performing filtering by partitioning key:
SELECT * FROM items WHERE id = 1234; id | name | code ------+----------------------------------+------ 1234 | 81dc9bdb52d04dc20036dbd8313ed055 | 1855 (1 row) EXPLAIN SELECT * FROM items WHERE id = 1234; QUERY PLAN ------------------------------------------------------------------------------------ Append (cost=0.28..8.29 rows=0 width=0) -> Index Scan using items_34_pkey on items_34 (cost=0.28..8.29 rows=0 width=0) Index Cond: (id = 1234)
Notice that the Append node contains only one child scan, which corresponds to the WHERE clause.
Important
Pay attention to the fact that pg_pathman excludes the parent table from the query plan.
To access the parent table, use the ONLY modifier:
EXPLAIN SELECT * FROM ONLY items; QUERY PLAN ------------------------------------------------------ Seq Scan on items (cost=0.00..0.00 rows=1 width=45)
F.36.3.3. Range Partitioning
Consider an example of range partitioning. Let's create a table containing some dummy logs:
CREATE TABLE journal (
id SERIAL,
dt TIMESTAMP NOT NULL,
level INTEGER,
msg TEXT);
-- similar index will also be created for each partition
CREATE INDEX ON journal(dt);
-- generate some data
INSERT INTO journal (dt, level, msg)
SELECT g, random() * 6, md5(g::text)
FROM generate_series('2015-01-01'::date, '2015-12-31'::date, '1 minute') as g;
Run the create_range_partitions() function to create partitions so that each partition would contain the data for one day:
SELECT create_range_partitions('journal', 'dt', '2015-01-01'::date, '1 day'::interval);
It will create 364 partitions and move the data from the parent table to partitions.
New partitions are appended automatically by insert trigger, but it can be done manually with the following functions:
-- add new partition with specified range
SELECT add_range_partition('journal', '2016-01-01'::date, '2016-01-07'::date);
-- append new partition with default range
SELECT append_range_partition('journal');
The first one creates a partition with specified range. The second one creates a partition with default interval and appends it to the partition list. It is also possible to attach an existing table as partition. For example, we may want to attach an archive table (or even foreign table from another server) for some outdated data:
CREATE FOREIGN TABLE journal_archive (
id INTEGER NOT NULL,
dt TIMESTAMP NOT NULL,
level INTEGER,
msg TEXT)
SERVER archive_server;
SELECT attach_range_partition('journal', 'journal_archive', '2014-01-01'::date, '2015-01-01'::date);
Important
The attached table must have the same columns as the partitioned table, except for the dropped columns. The attached columns must have the same type, collation, and not NULL settings as the original columns.
To merge two adjacent partitions, use the merge_range_partitions() function:
SELECT merge_range_partitions('journal_archive', 'journal_1');
To split partition by value, use the split_range_partition() function:
SELECT split_range_partition('journal_366', '2016-01-03'::date);
To detach partition, use the detach_range_partition() function:
SELECT detach_range_partition('journal_archive');
Here is an example of the query performing filtering by partitioning key:
SELECT * FROM journal WHERE dt >= '2015-06-01' AND dt < '2015-06-03'; id | dt | level | msg --------+---------------------+-------+---------------------------------- 217441 | 2015-06-01 00:00:00 | 2 | 15053892d993ce19f580a128f87e3dbf 217442 | 2015-06-01 00:01:00 | 1 | 3a7c46f18a952d62ce5418ac2056010c 217443 | 2015-06-01 00:02:00 | 0 | 92c8de8f82faf0b139a3d99f2792311d ... (2880 rows) EXPLAIN SELECT * FROM journal WHERE dt >= '2015-06-01' AND dt < '2015-06-03'; QUERY PLAN ------------------------------------------------------------------ Append (cost=0.00..58.80 rows=0 width=0) -> Seq Scan on journal_152 (cost=0.00..29.40 rows=0 width=0) -> Seq Scan on journal_153 (cost=0.00..29.40 rows=0 width=0) (3 rows)
F.36.4. Internals
pg_pathman stores partitioning configuration in the pathman_config table; each row contains a single entry for a partitioned table (relation name, partitioning column and its type). During the initialization stage the pg_pathman module caches some information about child partitions in the shared memory, which is used later for plan construction. Before a SELECT query is executed, pg_pathman traverses the condition tree in search of expressions like:
VARIABLE OP CONST
where VARIABLE is a partitioning key, OP is a comparison operator (supported operators are =, <, <=, >, >=), CONST is a scalar value. For example:
WHERE id = 150
Based on the partitioning type and condition's operator, pg_pathman searches for the corresponding partitions and builds the plan.
F.36.4.1. Custom Plan Nodes
pg_pathman provides a couple of custom plan nodes which aim to reduce execution time, namely:
RuntimeAppend(overridesAppendplan node)RuntimeMergeAppend(overridesMergeAppendplan node)PartitionFilter(drop-in replacement for INSERT triggers)
PartitionFilter acts as a proxy node for INSERT's child scan, which means it can redirect output tuples to the corresponding partition:
EXPLAIN (COSTS OFF)
INSERT INTO partitioned_table
SELECT generate_series(1, 10), random();
QUERY PLAN
-----------------------------------------
Insert on partitioned_table
-> Custom Scan (PartitionFilter)
-> Subquery Scan on "*SELECT*"
-> Result
(4 rows)
RuntimeAppend and RuntimeMergeAppend have much in common: they come in handy in a case when WHERE condition takes form of:
VARIABLE OP PARAM
This kind of expressions can no longer be optimized at planning time since the parameter's value is not known until the execution stage takes place. The problem can be solved by embedding the WHERE condition analysis routine into the original Append's code, thus making it pick only required scans out of a whole bunch of planned partition scans. This effectively boils down to creation of a custom node capable of performing such a check.
There are at least several cases that demonstrate usefulness of these nodes:
/* create table we're going to partition */
CREATE TABLE partitioned_table(id INT NOT NULL, payload REAL);
/* insert some data */
INSERT INTO partitioned_table
SELECT generate_series(1, 1000), random();
/* perform partitioning */
SELECT create_hash_partitions('partitioned_table', 'id', 100);
/* create ordinary table */
CREATE TABLE some_table AS SELECT generate_series(1, 100) AS VAL;
id = (select ... limit 1)EXPLAIN (COSTS OFF, ANALYZE) SELECT * FROM partitioned_table WHERE id = (SELECT * FROM some_table LIMIT 1); QUERY PLAN ---------------------------------------------------------------------------------------------------- Custom Scan (RuntimeAppend) (actual time=0.030..0.033 rows=1 loops=1) InitPlan 1 (returns $0) -> Limit (actual time=0.011..0.011 rows=1 loops=1) -> Seq Scan on some_table (actual time=0.010..0.010 rows=1 loops=1) -> Seq Scan on partitioned_table_70 partitioned_table (actual time=0.004..0.006 rows=1 loops=1) Filter: (id = $0) Rows Removed by Filter: 9 Planning time: 1.131 ms Execution time: 0.075 ms (9 rows) /* disable RuntimeAppend node */ SET pg_pathman.enable_runtimeappend = f; EXPLAIN (COSTS OFF, ANALYZE) SELECT * FROM partitioned_table WHERE id = (SELECT * FROM some_table LIMIT 1); QUERY PLAN ---------------------------------------------------------------------------------- Append (actual time=0.196..0.274 rows=1 loops=1) InitPlan 1 (returns $0) -> Limit (actual time=0.005..0.005 rows=1 loops=1) -> Seq Scan on some_table (actual time=0.003..0.003 rows=1 loops=1) -> Seq Scan on partitioned_table_0 (actual time=0.014..0.014 rows=0 loops=1) Filter: (id = $0) Rows Removed by Filter: 6 -> Seq Scan on partitioned_table_1 (actual time=0.003..0.003 rows=0 loops=1) Filter: (id = $0) Rows Removed by Filter: 5 ... /* more plans follow */ Planning time: 1.140 ms Execution time: 0.855 ms (306 rows)id = ANY (select ...)EXPLAIN (COSTS OFF, ANALYZE) SELECT * FROM partitioned_table WHERE id = any (SELECT * FROM some_table limit 4); QUERY PLAN ----------------------------------------------------------------------------------------------------------- Nested Loop (actual time=0.025..0.060 rows=4 loops=1) -> Limit (actual time=0.009..0.011 rows=4 loops=1) -> Seq Scan on some_table (actual time=0.008..0.010 rows=4 loops=1) -> Custom Scan (RuntimeAppend) (actual time=0.002..0.004 rows=1 loops=4) -> Seq Scan on partitioned_table_70 partitioned_table (actual time=0.001..0.001 rows=10 loops=1) -> Seq Scan on partitioned_table_26 partitioned_table (actual time=0.002..0.003 rows=9 loops=1) -> Seq Scan on partitioned_table_27 partitioned_table (actual time=0.001..0.002 rows=20 loops=1) -> Seq Scan on partitioned_table_63 partitioned_table (actual time=0.001..0.002 rows=9 loops=1) Planning time: 0.771 ms Execution time: 0.101 ms (10 rows) /* disable RuntimeAppend node */ SET pg_pathman.enable_runtimeappend = f; EXPLAIN (COSTS OFF, ANALYZE) SELECT * FROM partitioned_table WHERE id = any (SELECT * FROM some_table limit 4); QUERY PLAN ----------------------------------------------------------------------------------------- Nested Loop Semi Join (actual time=0.531..1.526 rows=4 loops=1) Join Filter: (partitioned_table.id = some_table.val) Rows Removed by Join Filter: 3990 -> Append (actual time=0.190..0.470 rows=1000 loops=1) -> Seq Scan on partitioned_table (actual time=0.187..0.187 rows=0 loops=1) -> Seq Scan on partitioned_table_0 (actual time=0.002..0.004 rows=6 loops=1) -> Seq Scan on partitioned_table_1 (actual time=0.001..0.001 rows=5 loops=1) -> Seq Scan on partitioned_table_2 (actual time=0.002..0.004 rows=14 loops=1) ... /* 96 scans follow */ -> Materialize (actual time=0.000..0.000 rows=4 loops=1000) -> Limit (actual time=0.005..0.006 rows=4 loops=1) -> Seq Scan on some_table (actual time=0.003..0.004 rows=4 loops=1) Planning time: 2.169 ms Execution time: 2.059 ms (110 rows)NestLoopinvolving a partitioned table, which is omitted since it's occasionally shown above.
To learn more about custom nodes, see Alexander Korotkov's blog.
F.36.5. Reference
F.36.5.1. GUC Variables
There are several user-accessible GUC variables designed to toggle pg_pathman or its specific custom nodes on and off.
pg_pathman.enable— enable/disable thepg_pathmanmodule.Default:
onpg_pathman.enable_runtimeappend— toggle theRuntimeAppendcustom node on/off.Default:
onpg_pathman.enable_runtimemergeappend— toggle theRuntimeMergeAppendcustom node on/off.Default:
onpg_pathman.enable_partitionfilter— toggle thePartitionFiltercustom node on/off.Default:
onpg_pathman.enable_auto_partition— toggle automatic partition creation on/off (per session).Default:
onpg_pathman.enable_bounds_cache— toggle bounds cache on/off.Default:
onpg_pathman.insert_into_fdw— allowINSERToperations into various foreign-data wrappers. Possible values:disabled,postgres, andany_fdw.Default:
postgrespg_pathman.override_copy— toggleCOPYstatement hooking on/off.Default:
on
F.36.5.2. Views and Tables
F.36.5.2.1. pathman_config
This table stores the list of partitioned tables. This is the main configuration storage.
CREATE TABLE IF NOT EXISTS pathman_config (
partrel REGCLASS NOT NULL PRIMARY KEY,
attname TEXT NOT NULL,
parttype INTEGER NOT NULL,
range_interval TEXT);
F.36.5.2.2. pathman_config_params
This table stores optional parameters that override standard pg_pathman behavior.
CREATE TABLE IF NOT EXISTS pathman_config_params (
partrel REGCLASS NOT NULL PRIMARY KEY,
enable_parent BOOLEAN NOT NULL DEFAULT TRUE,
auto BOOLEAN NOT NULL DEFAULT TRUE,
init_callback REGPROCEDURE NOT NULL DEFAULT 0,
spawn_using_bgw BOOLEAN NOT NULL DEFAULT FALSE);
F.36.5.2.3. pathman_concurrent_part_tasks
This view lists all currently running concurrent partitioning tasks.
-- helper SRF function
CREATE OR REPLACE FUNCTION show_concurrent_part_tasks()
RETURNS TABLE (
userid REGROLE,
pid INT,
dbid OID,
relid REGCLASS,
processed INT,
status TEXT)
AS 'pg_pathman', 'show_concurrent_part_tasks_internal'
LANGUAGE C STRICT;
CREATE OR REPLACE VIEW pathman_concurrent_part_tasks
AS SELECT * FROM show_concurrent_part_tasks();
F.36.5.2.4. pathman_partition_list
This view lists all existing partitions, as well as their parents and range boundaries (NULL for hash partitions).
-- helper SRF function
CREATE OR REPLACE FUNCTION show_partition_list()
RETURNS TABLE (
parent REGCLASS,
partition REGCLASS,
parttype INT4,
partattr TEXT,
range_min TEXT,
range_max TEXT)
AS 'pg_pathman', 'show_partition_list_internal'
LANGUAGE C STRICT;
CREATE OR REPLACE VIEW pathman_partition_list
AS SELECT * FROM show_partition_list();
F.36.5.3. Functions
F.36.5.3.1. Partitioning Functions
create_hash_partitions(relation REGCLASS,
attribute TEXT,
partitions_count INTEGER,
partition_data BOOLEAN DEFAULT TRUE,
partition_names TEXT[] DEFAULT NULL,
tablespaces TEXT[] DEFAULT NULL)
Performs hash partitioning for relation by integer key attribute. The partitions_count parameter specifies the number of partitions to create; it cannot be changed afterwards. If partition_data is true, all the data will be automatically migrated from the parent table to partitions. Note that data migration may take a while to finish and the table will be locked until transaction commits. See partition_table_concurrently() for a lock-free way to migrate data. Partition creation callback is invoked for each partition if set beforehand (see set_init_callback()).
create_range_partitions(relation REGCLASS,
expression TEXT,
start_value ANYELEMENT,
p_interval ANYELEMENT,
p_count INTEGER DEFAULT NULL,
partition_data BOOLEAN DEFAULT TRUE)
create_range_partitions(relation REGCLASS,
expression TEXT,
start_value ANYELEMENT,
p_interval INTERVAL,
p_count INTEGER DEFAULT NULL,
partition_data BOOLEAN DEFAULT TRUE)
create_range_partitions(relation REGCLASS,
expression TEXT,
bounds ANYARRAY,
partition_names TEXT[] DEFAULT NULL,
tablespaces TEXT[] DEFAULT NULL,
partition_data BOOLEAN DEFAULT TRUE)
Performs range partitioning for relation by partitioning key defined by expression. The start_value argument specifies the initial value, p_interval sets the default range for automatically created partitions or partitions created with append_range_partition() or prepend_range_partition(). If p_interval is set to NULL, automatic partition creation is disabled. p_count is the number of premade partitions. If p_count is not set, than pg_pathman tries to determine the number of partitions based on the expression value. The bounds array defines the bounds for partitions to be created. You can build this array using the generate_range_bounds() function. Partition creation callback is invoked for each partition if set beforehand.
F.36.5.3.2. Data Migration
partition_table_concurrently(relation REGCLASS)
Starts a background worker to move data from parent table to partitions. The worker utilizes short transactions to copy small batches of data (up to 10K rows per transaction) and thus doesn't significantly interfere with user's activity.
stop_concurrent_part_task(relation REGCLASS)
Stops a background worker performing a concurrent partitioning task. Note: worker will exit after it finishes relocating a current batch.
F.36.5.3.3. Triggers
create_hash_update_trigger(parent REGCLASS)
Creates the trigger on UPDATE for hash partitions. The UPDATE trigger isn't created by default because of the overhead. It's useful in cases when the key attribute might change.
create_range_update_trigger(parent REGCLASS)
Same as above, but for a range-partitioned table.
F.36.5.3.4. Partition Management Functions
replace_hash_partition(old_partition REGCLASS,
new_partition REGCLASS,
lock_parent BOOL DEFAULT TRUE)
Replaces the specified partition of hash-partitioned table with another table. When set to true, the lock_parent parameter prevents any INSERT/UPDATE/ALTER TABLE queries to the parent table.
split_range_partition(partition REGCLASS,
value ANYELEMENT,
partition_name TEXT DEFAULT NULL)
Split range partition in two by value, with the specified value included into the second partition. Partition creation callback is invoked for a new partition if available.
merge_range_partitions(partition1 REGCLASS, partition2 REGCLASS)
Merge two adjacent range partitions. First, data from partition2 is copied to partition1, then partition2 is removed.
merge_range_partitions(partitions REGCLASS[])
Merge several adjacent range partitions (partitions must be specified in ascending or descending order). All the data will be accumulated in the first partition.
append_range_partition(p_relation REGCLASS,
partition_name TEXT DEFAULT NULL,
tablespace TEXT DEFAULT NULL)
Append new range partition with pathman_config.range_interval as interval.
prepend_range_partition(p_relation REGCLASS,
partition_name TEXT DEFAULT NULL,
tablespace TEXT DEFAULT NULL)
Prepend new range partition with pathman_config.range_interval as interval.
add_range_partition(relation REGCLASS,
start_value ANYELEMENT,
end_value ANYELEMENT,
partition_name TEXT DEFAULT NULL,
tablespace TEXT DEFAULT NULL)
Create a new range partition for relation with the specified range bounds. If the start_value or the end_value is NULL, than the corresponding range bound will be infinite.
drop_range_partition(partition TEXT, delete_data BOOLEAN DEFAULT TRUE)
Drop range partition and all of its data if delete_data is true.
attach_range_partition(relation REGCLASS,
partition REGCLASS,
start_value ANYELEMENT,
end_value ANYELEMENT)
Attach partition to the existing range-partitioned relation. The attached table must have exactly the same structure as the parent table, including the dropped columns. Partition creation callback is invoked if set (see pathman_config_params).
detach_range_partition(partition REGCLASS)
Detach partition from the existing range-partitioned relation.
disable_pathman_for(relation TEXT)
Permanently disable pg_pathman partitioning mechanism for the specified parent table and remove the insert trigger if it exists. All partitions and data remain unchanged.
drop_partitions(parent REGCLASS,
delete_data BOOLEAN DEFAULT FALSE)
Drop partitions of the parent table (both foreign and local relations). If delete_data is false, the data is copied to the parent table first. Default is false.
F.36.5.3.5. Additional Parameters
set_interval(relation REGCLASS, value ANYELEMENT)
Update range-partitioned table interval. Note that interval must not be negative and it must not be trivial, i.e. its value should be greater than zero for numeric types, at least 1 microsecond for timestamp and at least 1 day for date.
set_enable_parent(relation REGCLASS, value BOOLEAN)
Include/exclude parent table into/from query plan. In original Postgres Pro planner parent table is always included into query plan even if it's empty which can lead to additional overhead. You can use disable_parent() if you are never going to use parent table as a storage. Default value depends on the partition_data parameter that was specified during initial partitioning in create_range_partitions() or create_partitions_from_range() functions. If the partition_data parameter was true then all data have already been migrated to partitions and parent table disabled. Otherwise it is enabled.
set_auto(relation REGCLASS, value BOOLEAN)
Enable/disable auto partition propagation (only for range partitioning). It is enabled by default.
set_init_callback(relation REGCLASS, callback REGPROC DEFAULT 0)
Set partition creation callback to be invoked for each attached or created partition (both hash and range). The callback must have the following signature: part_init_callback(args JSONB) RETURNS VOID. Parameter arg consists of several fields whose presence depends on partitioning type:
/* Range-partitioned table abc (child abc_4) */
{
"parent": "abc",
"parttype": "2",
"partition": "abc_4",
"range_max": "401",
"range_min": "301"
}
/* Hash-partitioned table abc (child abc_0) */
{
"parent": "abc",
"parttype": "1",
"partition": "abc_0"
}
set_spawn_using_bgw(relation REGCLASS, value BOOLEAN)
When inserting new data beyond the partitioning range, use SpawnPartitionsWorker to create new partitions in a separate transaction.
create_naming_sequence(relation REGCLASS)
Enable automatic partition naming for the specified relation table. You must run this function when partitioning this table by composite key.
add_to_pathman_config(relation REGCLASS,
expression TEXT,
range_interval TEXT)
add_to_pathman_config(relation REGCLASS,
expression TEXT)
Register the specified relation table with pg_pathman to enable partitioning by the provided expression. For range partitioning, the range_interval argument is mandatory. You can set it to NULL if you are going to add partition manually.
generate_range_bounds(p_start ANYELEMENT,
p_interval INTERVAL,
p_count INTEGER)
generate_range_bounds(p_start ANYELEMENT,
p_interval ANYELEMENT,
p_count INTEGER)
Build the bounds array that defines the bounds for partitions to be created. You can pass this array as an argument to the create_range_partitions() function.
F.36.6. Authors
Ildar Musin
<[email protected]>Postgres Professional Ltd., RussiaAlexander Korotkov
<[email protected]>Postgres Professional Ltd., RussiaDmitry Ivanov
<[email protected]>Postgres Professional Ltd., Russia