pg_pathman 1.3.1

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pg_pathman 1.3.1
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pg_pathman 1.4.7 —
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Partitioning tool
Description
The `pg_pathman` module provides optimized partitioning mechanism and functions to manage partitions.
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zilder
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The PostgreSQL License
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Extensions

pg_pathman 1.3.1
Partitioning tool

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README.rus
pg_pathman
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README

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pg_pathman

The pg_pathman module provides optimized partitioning mechanism and functions to manage partitions.

The extension is compatible with PostgreSQL 9.5+.

Overview

Partitioning means splitting one large table into smaller pieces. Each row in such table is moved to a single partition according to the partitioning key. PostgreSQL supports partitioning via table inheritance: each partition must be created as a child table with CHECK CONSTRAINT. For example:

plpgsql 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);

Despite the flexibility, this approach forces the planner to perform an exhaustive search and to check constraints on each partition to determine whether it should be present in the plan or not. Large amount of partitions may result in significant planning overhead.

The pg_pathman module features partition managing functions and optimized planning mechanism which utilizes knowledge of the partitions' structure. It 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:

plpgsql WHERE id = 150

Based on the partitioning type and condition's operator, pg_pathman searches for the corresponding partitions and builds the plan. Currently pg_pathman supports two partitioning schemes:

  • RANGE - maps rows to partitions using partitioning key ranges assigned to each partition. Optimization is achieved by using the binary search algorithm;
  • HASH - maps rows to partitions using a generic hash function.

More interesting features are yet to come. Stay tuned!

Feature highlights

  • HASH and RANGE partitioning schemes;
  • Both automatic and manual partition management;
  • Support for integer, floating point, date and other types, including domains;
  • Effective query planning for partitioned tables (JOINs, subselects etc);
  • RuntimeAppend & RuntimeMergeAppend custom plan nodes to pick partitions at runtime;
  • PartitionFilter: an efficient drop-in replacement for INSERT triggers;
  • Automatic partition creation for new INSERTed data (only for RANGE partitioning);
  • Improved COPY FROM\TO statement that is able to insert rows directly into partitions;
  • UPDATE triggers generation out of the box (will be replaced with custom nodes too);
  • User-defined callbacks for partition creation event handling;
  • Non-blocking concurrent table partitioning;
  • FDW support (foreign partitions);
  • Various GUC toggles and configurable settings.

Roadmap

  • Implement LIST partitioning scheme;
  • Optimize hash join (both tables are partitioned by join key).

Installation guide

To install pg_pathman, execute this in the module's directory: shell make install USE_PGXS=1 Modify the shared_preload_libraries parameter in postgresql.conf as following: shared_preload_libraries = 'pg_pathman'

Important: pg_pathman may cause conflicts with some other extensions that use the same hook functions. For example, pg_pathman uses ProcessUtility_hook to handle COPY queries for partitioned tables, which means it may interfere with pg_stat_statements from time to time. In this case, try listing libraries in certain order: shared_preload_libraries = 'pg_stat_statements, pg_pathman'.

It is essential to restart the PostgreSQL instance. After that, execute the following query in psql: plpgsql CREATE EXTENSION pg_pathman;

Done! Now it's time to setup your partitioning schemes.

Important: Don't forget to set the PG_CONFIG variable in case you want to test pg_pathman on a custom build of PostgreSQL. Read more here.

How to update

In order to update pg_pathman:

  1. Install the latest stable release of pg_pathman.
  2. Restart your PostgreSQL cluster.
  3. Execute the following queries:

plpgsql /* replace X.Y with the version number, e.g. 1.3 */ ALTER EXTENSION pg_pathman UPDATE TO "X.Y"; SET pg_pathman.enable = t;

Available functions

Partition creation

plpgsql 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 then all the data will be automatically copied from the parent table to partitions. Note that data migration may took 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()).

```plpgsql create_range_partitions(relation REGCLASS, attribute TEXT, start_value ANYELEMENT, p_interval ANYELEMENT, p_count INTEGER DEFAULT NULL partition_data BOOLEAN DEFAULT TRUE)

create_range_partitions(relation REGCLASS, attribute TEXT, start_value ANYELEMENT, p_interval INTERVAL, p_count INTEGER DEFAULT NULL, partition_data BOOLEAN DEFAULT TRUE) `` Performs RANGE partitioning forrelationby partitioning keyattribute,start_valueargument specifies initial value,p_intervalsets the default range for auto created partitions or partitions created withappend_range_partition()orprepend_range_partition()(ifNULLthen auto partition creation feature won't work),p_countis the number of premade partitions (if not set thenpg_pathman` tries to determine it based on attribute values). Partition creation callback is invoked for each partition if set beforehand.

```plpgsql create_partitions_from_range(relation REGCLASS, attribute TEXT, start_value ANYELEMENT, end_value ANYELEMENT, p_interval ANYELEMENT, partition_data BOOLEAN DEFAULT TRUE)

create_partitions_from_range(relation REGCLASS, attribute TEXT, start_value ANYELEMENT, end_value ANYELEMENT, p_interval INTERVAL, partition_data BOOLEAN DEFAULT TRUE) `` Performs RANGE-partitioning from specified range forrelationby partitioning keyattribute`. Partition creation callback is invoked for each partition if set beforehand.

Data migration

plpgsql partition_table_concurrently(relation REGCLASS, batch_size INTEGER DEFAULT 1000, sleep_time FLOAT8 DEFAULT 1.0) 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. If the worker is unable to lock rows of a batch, it sleeps for sleep_time seconds before the next attempt and tries again up to 60 times, and quits if it's still unable to lock the batch.

plpgsql 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.

Triggers

plpgsql 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. plpgsql create_range_update_trigger(parent REGCLASS) Same as above, but for a RANGE-partitioned table.

Post-creation partition management

plpgsql replace_hash_partition(old_partition REGCLASS, new_partition REGCLASS, lock_parent BOOL DEFAULT TRUE) Replaces specified partition of HASH-partitioned table with another table. The lock_parent parameter will prevent any INSERT/UPDATE/ALTER TABLE queries to parent table.

plpgsql split_range_partition(partition REGCLASS, split_value ANYELEMENT, partition_name TEXT DEFAULT NULL) Split RANGE partition in two by split_value. Partition creation callback is invoked for a new partition if available.

plpgsql merge_range_partitions(partition1 REGCLASS, partition2 REGCLASS) Merge two adjacent RANGE partitions. First, data from partition2 is copied to partition1, then partition2 is removed.

plpgsql 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.

plpgsql append_range_partition(parent REGCLASS, partition_name TEXT DEFAULT NULL, tablespace TEXT DEFAULT NULL) Append new RANGE partition with pathman_config.range_interval as interval.

plpgsql prepend_range_partition(parent REGCLASS, partition_name TEXT DEFAULT NULL, tablespace TEXT DEFAULT NULL) Prepend new RANGE partition with pathman_config.range_interval as interval.

plpgsql add_range_partition(relation REGCLASS, start_value ANYELEMENT, end_value ANYELEMENT, partition_name TEXT DEFAULT NULL, tablespace TEXT DEFAULT NULL) Create new RANGE partition for relation with specified range bounds. If start_value or end_value are NULL then corresponding range bound will be infinite.

plpgsql drop_range_partition(partition TEXT, delete_data BOOLEAN DEFAULT TRUE) Drop RANGE partition and all of its data if delete_data is true.

plpgsql 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).

plpgsql detach_range_partition(partition REGCLASS) Detach partition from the existing RANGE-partitioned relation.

plpgsql 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.

plpgsql 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.

Additional parameters

plpgsql 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.

plpgsql set_enable_parent(relation REGCLASS, value BOOLEAN) Include/exclude parent table into/from query plan. In original PostgreSQL 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.

plpgsql set_auto(relation REGCLASS, value BOOLEAN) Enable/disable auto partition propagation (only for RANGE partitioning). It is enabled by default.

plpgsql 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: ```json /* 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" } ```

plpgsql set_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.

Views and tables

pathman_config --- main config storage

plpgsql CREATE TABLE IF NOT EXISTS pathman_config ( partrel REGCLASS NOT NULL PRIMARY KEY, attname TEXT NOT NULL, parttype INTEGER NOT NULL, range_interval TEXT); This table stores a list of partitioned tables.

pathman_config_params --- optional parameters

plpgsql 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); This table stores optional parameters which override standard behavior.

pathman_concurrent_part_tasks --- currently running partitioning workers

```plpgsql -- 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(); ``` This view lists all currently running concurrent partitioning tasks.

pathman_partition_list --- list of all existing partitions

```plpgsql -- 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(); ``` This view lists all existing partitions, as well as their parents and range boundaries (NULL for HASH partitions).

Custom plan nodes

pg_pathman provides a couple of custom plan nodes which aim to reduce execution time, namely:

  • RuntimeAppend (overrides Append plan node)
  • RuntimeMergeAppend (overrides MergeAppend plan 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:

```plpgsql 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:

```plpgsql /* 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) ```plpgsql 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 ...) ```plpgsql 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) ```

  • NestLoop involving a partitioned table, which is omitted since it's occasionally shown above.

In case you're interested, you can read more about custom nodes at Alexander Korotkov's blog.

Examples

Common tips

  • You can easily add partition column containing the names of the underlying partitions using the system attribute called tableoid: plpgsql SELECT tableoid::regclass AS partition, * FROM partitioned_table;

  • Though indices on a parent table aren't particularly useful (since it's supposed to be empty), they act as prototypes for indices on partitions. For each index on the parent table, pg_pathman will create a similar index on every partition.

  • All running concurrent partitioning tasks can be listed using the pathman_concurrent_part_tasks view: plpgsql SELECT * FROM pathman_concurrent_part_tasks; userid | pid | dbid | relid | processed | status
    --------+------+-------+-------+-----------+--------- dmitry | 7367 | 16384 | test | 472000 | working (1 row)

  • pathman_partition_list in conjunction with drop_range_partition() can be used to drop RANGE partitions in a more flexible way compared to good old DROP TABLE: ```plpgsql 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) ```

  • You can turn foreign tables into partitions using the attach_range_partition() function. Rows that were meant to be inserted into parent will be redirected to foreign partitions (as usual, PartitionFilter will be involved), though by default it is prohibited to insert rows into partitions provided not by postgres_fdw. Only superuser is allowed to set pg_pathman.insert_into_fdw GUC variable.

HASH partitioning

Consider an example of HASH partitioning. First create a table with some integer column: ```plpgsql 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: plpgsql SELECT create_hash_partitions('items', 'id', 100); ``` This will create new partitions and move the data from parent to partitions.

Here's an example of the query performing filtering by partitioning key: ```plpgsql 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 parent table use ONLY modifier: ```plpgsql EXPLAIN SELECT * FROM ONLY items;

QUERY PLAN

Seq Scan on items (cost=0.00..0.00 rows=1 width=45) ```

RANGE partitioning

Consider an example of RANGE partitioning. Let's create a table containing some dummy logs: ```plpgsql 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: plpgsql SELECT create_range_partitions('journal', 'dt', '2015-01-01'::date, '1 day'::interval); ``` It will create 365 partitions and move the data from parent to partitions.

New partitions are appended automaticaly by insert trigger, but it can be done manually with the following functions: ```plpgsql -- 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: plpgsql 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 definition of the attached table must match the one of the existing partitioned table, including the dropped columns.

To merge to adjacent partitions, use the merge_range_partitions() function: plpgsql SELECT merge_range_partitions('journal_archive', 'journal_1'); To split partition by value, use the split_range_partition() function: plpgsql SELECT split_range_partition('journal_366', '2016-01-03'::date); To detach partition, use the detach_range_partition() function: plpgsql SELECT detach_range_partition('journal_archive');

Here's an example of the query performing filtering by partitioning key: ```plpgsql 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) ```

Disabling pg_pathman

There are several user-accessible GUC variables designed to toggle the whole module or specific custom nodes on and off:

  • pg_pathman.enable --- disable (or enable) pg_pathman completely
  • pg_pathman.enable_runtimeappend --- toggle RuntimeAppend custom node on\off
  • pg_pathman.enable_runtimemergeappend --- toggle RuntimeMergeAppend custom node on\off
  • pg_pathman.enable_partitionfilter --- toggle PartitionFilter custom node on\off
  • pg_pathman.enable_auto_partition --- toggle automatic partition creation on\off (per session)
  • pg_pathman.insert_into_fdw --- allow INSERTs into various FDWs (disabled | postgres | any_fdw)
  • pg_pathman.override_copy --- toggle COPY statement hooking on\off

To permanently disable pg_pathman for some previously partitioned table, use the disable_pathman_for() function: plpgsql SELECT disable_pathman_for('range_rel'); All sections and data will remain unchanged and will be handled by the standard PostgreSQL inheritance mechanism.

Feedback

Do not hesitate to post your issues, questions and new ideas at the issues page.

Authors

Ildar Musin i.musin@postgrespro.ru Postgres Professional Ltd., Russia
Alexander Korotkov a.korotkov@postgrespro.ru Postgres Professional Ltd., Russia
Dmitry Ivanov d.ivanov@postgrespro.ru Postgres Professional Ltd., Russia