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• Query performance can be improved dramatically in certain situations, particularly when most of the heavily accessed rows of the table are in a single partition or a small number of partitions. Partitioning effectively substitutes for the upper tree levels of indexes, making it more likely that the heavily-used parts of the indexes fit in memory.

• When queries or updates access a large percentage of a single partition, performance can be improved by using a sequential scan of that partition instead of using an index, which would require random-access reads scattered across the whole table.

• Bulk loads and deletes can be accomplished by adding or removing partitions, if the usage pattern is accounted for in the partitioning design. Dropping an individual partition usingDROP TABLE, or doingALTER TABLE DETACH PARTITION, is far faster than a bulk operation. These commands also entirely avoid theVACUUM overhead caused by a bulkDELETE.

• Seldom-used data can be migrated to cheaper and slower storage media.

Range Partitioning

The table is partitioned into“ranges” defined by a key column or set of columns, with no overlap between the ranges of values assigned to different partitions. For example, one might partition by date ranges, or by ranges of identifiers for particular business objects. Each range's bounds are understood as being inclusive at the lower end and exclusive at the upper end. For example, if one partition's range is from1 to10, and the next one's range is from10 to20, then value10 belongs to the second partition not the first.

List Partitioning

The table is partitioned by explicitly listing which key value(s) appear in each partition.

Hash Partitioning

The table is partitioned by specifying a modulus and a remainder for each partition. Each partition will hold the rows for which the hash value of the partition key divided by the specified modulus will produce the specified remainder.

Suppose we are constructing a database for a large ice cream company. The company measures peak temperatures every day as well as ice cream sales in each region. Conceptually, we want a table like:

CREATE TABLE measurement (    city_id         int not null,    logdate         date not null,    peaktemp        int,    unitsales       int);

We know that most queries will access just the last week's, month's or quarter's data, since the main use of this table will be to prepare online reports for management. To reduce the amount of old data that needs to be stored, we decide to keep only the most recent 3 years worth of data. At the beginning of each month we will remove the oldest month's data. In this situation we can use partitioning to help us meet all of our different requirements for the measurements table.

To use declarative partitioning in this case, use the following steps:

In the above example we would be creating a new partition each month, so it might be wise to write a script that generates the required DDL automatically.

Normally the set of partitions established when initially defining the table is not intended to remain static. It is common to want to remove partitions holding old data and periodically add new partitions for new data. One of the most important advantages of partitioning is precisely that it allows this otherwise painful task to be executed nearly instantaneously by manipulating the partition structure, rather than physically moving large amounts of data around.

The simplest option for removing old data is to drop the partition that is no longer necessary:

DROP TABLE measurement_y2006m02;

This can very quickly delete millions of records because it doesn't have to individually delete every record. Note however that the above command requires taking anACCESS EXCLUSIVE lock on the parent table.

Another option that is often preferable is to remove the partition from the partitioned table but retain access to it as a table in its own right:

ALTER TABLE measurement DETACH PARTITION measurement_y2006m02;

This allows further operations to be performed on the data before it is dropped. For example, this is often a useful time to back up the data usingCOPY,pg_dump, or similar tools. It might also be a useful time to aggregate data into smaller formats, perform other data manipulations, or run reports.

Similarly we can add a new partition to handle new data. We can create an empty partition in the partitioned table just as the original partitions were created above:

CREATE TABLE measurement_y2008m02 PARTITION OF measurement    FOR VALUES FROM ('2008-02-01') TO ('2008-03-01')    TABLESPACE fasttablespace;

As an alternative, it is sometimes more convenient to create the new table outside the partition structure, and make it a proper partition later. This allows new data to be loaded, checked, and transformed prior to it appearing in the partitioned table. TheCREATE TABLE ... LIKE option is helpful to avoid tediously repeating the parent table's definition:

CREATE TABLE measurement_y2008m02  (LIKE measurement INCLUDING DEFAULTS INCLUDING CONSTRAINTS)  TABLESPACE fasttablespace;ALTER TABLE measurement_y2008m02 ADD CONSTRAINT y2008m02   CHECK ( logdate >= DATE '2008-02-01' AND logdate < DATE '2008-03-01' );\copy measurement_y2008m02 from 'measurement_y2008m02'-- possibly some other data preparation workALTER TABLE measurement ATTACH PARTITION measurement_y2008m02    FOR VALUES FROM ('2008-02-01') TO ('2008-03-01' );

TheATTACH PARTITION command requires taking aSHARE UPDATE EXCLUSIVE lock on the partitioned table.

Before running theATTACH PARTITION command, it is recommended to create aCHECK constraint on the table to be attached that matches the expected partition constraint, as illustrated above. That way, the system will be able to skip the scan which is otherwise needed to validate the implicit partition constraint. Without theCHECK constraint, the table will be scanned to validate the partition constraint while holding anACCESS EXCLUSIVE lock on that partition. It is recommended to drop the now-redundantCHECK constraint after theATTACH PARTITION is complete. If the table being attached is itself a partitioned table, then each of its sub-partitions will be recursively locked and scanned until either a suitableCHECK constraint is encountered or the leaf partitions are reached.

Similarly, if the partitioned table has aDEFAULT partition, it is recommended to create aCHECK constraint which excludes the to-be-attached partition's constraint. If this is not done then theDEFAULT partition will be scanned to verify that it contains no records which should be located in the partition being attached. This operation will be performed whilst holding anACCESS EXCLUSIVE lock on the DEFAULT partition. If theDEFAULT partition is itself a partitioned table, then each of its partitions will be recursively checked in the same way as the table being attached, as mentioned above.

As explained above, it is possible to create indexes on partitioned tables so that they are applied automatically to the entire hierarchy. This is very convenient, as not only will the existing partitions become indexed, but also any partitions that are created in the future will. One limitation is that it's not possible to use theCONCURRENTLY qualifier when creating such a partitioned index. To avoid long lock times, it is possible to useCREATE INDEX ON ONLY the partitioned table; such an index is marked invalid, and the partitions do not get the index applied automatically. The indexes on partitions can be created individually usingCONCURRENTLY, and thenattached to the index on the parent usingALTER INDEX .. ATTACH PARTITION. Once indexes for all partitions are attached to the parent index, the parent index is marked valid automatically. Example:

CREATE INDEX measurement_usls_idx ON ONLY measurement (unitsales);CREATE INDEX CONCURRENTLY measurement_usls_200602_idx    ON measurement_y2006m02 (unitsales);ALTER INDEX measurement_usls_idx    ATTACH PARTITION measurement_usls_200602_idx;...

This technique can be used withUNIQUE andPRIMARY KEY constraints too; the indexes are created implicitly when the constraint is created. Example:

ALTER TABLE ONLY measurement ADD UNIQUE (city_id, logdate);ALTER TABLE measurement_y2006m02 ADD UNIQUE (city_id, logdate);ALTER INDEX measurement_city_id_logdate_key    ATTACH PARTITION measurement_y2006m02_city_id_logdate_key;...

The following limitations apply to partitioned tables:

Individual partitions are linked to their partitioned table using inheritance behind-the-scenes. However, it is not possible to use all of the generic features of inheritance with declaratively partitioned tables or their partitions, as discussed below. Notably, a partition cannot have any parents other than the partitioned table it is a partition of, nor can a table inherit from both a partitioned table and a regular table. That means partitioned tables and their partitions never share an inheritance hierarchy with regular tables.

Since a partition hierarchy consisting of the partitioned table and its partitions is still an inheritance hierarchy,tableoid and all the normal rules of inheritance apply as described inSection 5.10, with a few exceptions:

• For declarative partitioning, partitions must have exactly the same set of columns as the partitioned table, whereas with table inheritance, child tables may have extra columns not present in the parent.

• Table inheritance allows for multiple inheritance.

• Declarative partitioning only supports range, list and hash partitioning, whereas table inheritance allows data to be divided in a manner of the user's choosing. (Note, however, that if constraint exclusion is unable to prune child tables effectively, query performance might be poor.)

• Some operations require a stronger lock when using declarative partitioning than when using table inheritance. For example, removing a partition from a partitioned table requires taking anACCESS EXCLUSIVE lock on the parent table, whereas aSHARE UPDATE EXCLUSIVE lock is enough in the case of regular inheritance.

This example builds a partitioning structure equivalent to the declarative partitioning example above. Use the following steps:

As we can see, a complex table hierarchy could require a substantial amount of DDL. In the above example we would be creating a new child table each month, so it might be wise to write a script that generates the required DDL automatically.

To remove old data quickly, simply drop the child table that is no longer necessary:

DROP TABLE measurement_y2006m02;

To remove the child table from the inheritance hierarchy table but retain access to it as a table in its own right:

ALTER TABLE measurement_y2006m02 NO INHERIT measurement;

To add a new child table to handle new data, create an empty child table just as the original children were created above:

CREATE TABLE measurement_y2008m02 (    CHECK ( logdate >= DATE '2008-02-01' AND logdate < DATE '2008-03-01' )) INHERITS (measurement);

Alternatively, one may want to create and populate the new child table before adding it to the table hierarchy. This could allow data to be loaded, checked, and transformed before being made visible to queries on the parent table.

CREATE TABLE measurement_y2008m02  (LIKE measurement INCLUDING DEFAULTS INCLUDING CONSTRAINTS);ALTER TABLE measurement_y2008m02 ADD CONSTRAINT y2008m02   CHECK ( logdate >= DATE '2008-02-01' AND logdate < DATE '2008-03-01' );\copy measurement_y2008m02 from 'measurement_y2008m02'-- possibly some other data preparation workALTER TABLE measurement_y2008m02 INHERIT measurement;

The following caveats apply to partitioning implemented using inheritance:

• During initialization of the query plan. Partition pruning can be performed here for parameter values which are known during the initialization phase of execution. Partitions which are pruned during this stage will not show up in the query'sEXPLAIN orEXPLAIN ANALYZE. It is possible to determine the number of partitions which were removed during this phase by observing the“Subplans Removed” property in theEXPLAIN output.

• During actual execution of the query plan. Partition pruning may also be performed here to remove partitions using values which are only known during actual query execution. This includes values from subqueries and values from execution-time parameters such as those from parameterized nested loop joins. Since the value of these parameters may change many times during the execution of the query, partition pruning is performed whenever one of the execution parameters being used by partition pruning changes. Determining if partitions were pruned during this phase requires careful inspection of theloops property in theEXPLAIN ANALYZE output. Subplans corresponding to different partitions may have different values for it depending on how many times each of them was pruned during execution. Some may be shown as(never executed) if they were pruned every time.

Note

Execution-time partition pruning currently only occurs for theAppend andMergeAppend node types. It is not yet implemented for theModifyTable node type, but that is likely to be changed in a future release ofPostgreSQL.

• Constraint exclusion is only applied during query planning, unlike partition pruning, which can also be applied during query execution.

• Constraint exclusion only works when the query'sWHERE clause contains constants (or externally supplied parameters). For example, a comparison against a non-immutable function such asCURRENT_TIMESTAMP cannot be optimized, since the planner cannot know which child table the function's value might fall into at run time.

• Keep the partitioning constraints simple, else the planner may not be able to prove that child tables might not need to be visited. Use simple equality conditions for list partitioning, or simple range tests for range partitioning, as illustrated in the preceding examples. A good rule of thumb is that partitioning constraints should contain only comparisons of the partitioning column(s) to constants using B-tree-indexable operators, because only B-tree-indexable column(s) are allowed in the partition key.

• All constraints on all children of the parent table are examined during constraint exclusion, so large numbers of children are likely to increase query planning time considerably. So the legacy inheritance based partitioning will work well with up to perhaps a hundred child tables; don't try to use many thousands of children.