Provided by: postgresql-client-17_17.2-1_amd64 bug

NAME

       EXPLAIN - show the execution plan of a statement

SYNOPSIS

       EXPLAIN [ ( option [, ...] ) ] statement

       where option can be one of:

           ANALYZE [ boolean ]
           VERBOSE [ boolean ]
           COSTS [ boolean ]
           SETTINGS [ boolean ]
           GENERIC_PLAN [ boolean ]
           BUFFERS [ boolean ]
           SERIALIZE [ { NONE | TEXT | BINARY } ]
           WAL [ boolean ]
           TIMING [ boolean ]
           SUMMARY [ boolean ]
           MEMORY [ boolean ]
           FORMAT { TEXT | XML | JSON | YAML }

DESCRIPTION

       This command displays the execution plan that the PostgreSQL planner generates for the
       supplied statement. The execution plan shows how the table(s) referenced by the statement
       will be scanned — by plain sequential scan, index scan, etc. — and if multiple tables are
       referenced, what join algorithms will be used to bring together the required rows from
       each input table.

       The most critical part of the display is the estimated statement execution cost, which is
       the planner's guess at how long it will take to run the statement (measured in cost units
       that are arbitrary, but conventionally mean disk page fetches). Actually two numbers are
       shown: the start-up cost before the first row can be returned, and the total cost to
       return all the rows. For most queries the total cost is what matters, but in contexts such
       as a subquery in EXISTS, the planner will choose the smallest start-up cost instead of the
       smallest total cost (since the executor will stop after getting one row, anyway). Also, if
       you limit the number of rows to return with a LIMIT clause, the planner makes an
       appropriate interpolation between the endpoint costs to estimate which plan is really the
       cheapest.

       The ANALYZE option causes the statement to be actually executed, not only planned. Then
       actual run time statistics are added to the display, including the total elapsed time
       expended within each plan node (in milliseconds) and the total number of rows it actually
       returned. This is useful for seeing whether the planner's estimates are close to reality.

           Important
           Keep in mind that the statement is actually executed when the ANALYZE option is used.
           Although EXPLAIN will discard any output that a SELECT would return, other side
           effects of the statement will happen as usual. If you wish to use EXPLAIN ANALYZE on
           an INSERT, UPDATE, DELETE, MERGE, CREATE TABLE AS, or EXECUTE statement without
           letting the command affect your data, use this approach:

               BEGIN;
               EXPLAIN ANALYZE ...;
               ROLLBACK;

PARAMETERS

       ANALYZE
           Carry out the command and show actual run times and other statistics. This parameter
           defaults to FALSE.

       VERBOSE
           Display additional information regarding the plan. Specifically, include the output
           column list for each node in the plan tree, schema-qualify table and function names,
           always label variables in expressions with their range table alias, and always print
           the name of each trigger for which statistics are displayed. The query identifier will
           also be displayed if one has been computed, see compute_query_id for more details.
           This parameter defaults to FALSE.

       COSTS
           Include information on the estimated startup and total cost of each plan node, as well
           as the estimated number of rows and the estimated width of each row. This parameter
           defaults to TRUE.

       SETTINGS
           Include information on configuration parameters. Specifically, include options
           affecting query planning with value different from the built-in default value. This
           parameter defaults to FALSE.

       GENERIC_PLAN
           Allow the statement to contain parameter placeholders like $1, and generate a generic
           plan that does not depend on the values of those parameters. See PREPARE for details
           about generic plans and the types of statement that support parameters. This parameter
           cannot be used together with ANALYZE. It defaults to FALSE.

       BUFFERS
           Include information on buffer usage. Specifically, include the number of shared blocks
           hit, read, dirtied, and written, the number of local blocks hit, read, dirtied, and
           written, the number of temp blocks read and written, and the time spent reading and
           writing data file blocks, local blocks and temporary file blocks (in milliseconds) if
           track_io_timing is enabled. A hit means that a read was avoided because the block was
           found already in cache when needed. Shared blocks contain data from regular tables and
           indexes; local blocks contain data from temporary tables and indexes; while temporary
           blocks contain short-term working data used in sorts, hashes, Materialize plan nodes,
           and similar cases. The number of blocks dirtied indicates the number of previously
           unmodified blocks that were changed by this query; while the number of blocks written
           indicates the number of previously-dirtied blocks evicted from cache by this backend
           during query processing. The number of blocks shown for an upper-level node includes
           those used by all its child nodes. In text format, only non-zero values are printed.
           This parameter defaults to FALSE.

       SERIALIZE
           Include information on the cost of serializing the query's output data, that is
           converting it to text or binary format to send to the client. This can be a
           significant part of the time required for regular execution of the query, if the
           datatype output functions are expensive or if TOASTed values must be fetched from
           out-of-line storage.  EXPLAIN's default behavior, SERIALIZE NONE, does not perform
           these conversions. If SERIALIZE TEXT or SERIALIZE BINARY is specified, the appropriate
           conversions are performed, and the time spent doing so is measured (unless TIMING OFF
           is specified). If the BUFFERS option is also specified, then any buffer accesses
           involved in the conversions are counted too. In no case, however, will EXPLAIN
           actually send the resulting data to the client; hence network transmission costs
           cannot be investigated this way. Serialization may only be enabled when ANALYZE is
           also enabled. If SERIALIZE is written without an argument, TEXT is assumed.

       WAL
           Include information on WAL record generation. Specifically, include the number of
           records, number of full page images (fpi) and the amount of WAL generated in bytes. In
           text format, only non-zero values are printed. This parameter may only be used when
           ANALYZE is also enabled. It defaults to FALSE.

       TIMING
           Include actual startup time and time spent in each node in the output. The overhead of
           repeatedly reading the system clock can slow down the query significantly on some
           systems, so it may be useful to set this parameter to FALSE when only actual row
           counts, and not exact times, are needed. Run time of the entire statement is always
           measured, even when node-level timing is turned off with this option. This parameter
           may only be used when ANALYZE is also enabled. It defaults to TRUE.

       SUMMARY
           Include summary information (e.g., totaled timing information) after the query plan.
           Summary information is included by default when ANALYZE is used but otherwise is not
           included by default, but can be enabled using this option. Planning time in EXPLAIN
           EXECUTE includes the time required to fetch the plan from the cache and the time
           required for re-planning, if necessary.

       MEMORY
           Include information on memory consumption by the query planning phase. Specifically,
           include the precise amount of storage used by planner in-memory structures, as well as
           total memory considering allocation overhead. This parameter defaults to FALSE.

       FORMAT
           Specify the output format, which can be TEXT, XML, JSON, or YAML. Non-text output
           contains the same information as the text output format, but is easier for programs to
           parse. This parameter defaults to TEXT.

       boolean
           Specifies whether the selected option should be turned on or off. You can write TRUE,
           ON, or 1 to enable the option, and FALSE, OFF, or 0 to disable it. The boolean value
           can also be omitted, in which case TRUE is assumed.

       statement
           Any SELECT, INSERT, UPDATE, DELETE, MERGE, VALUES, EXECUTE, DECLARE, CREATE TABLE AS,
           or CREATE MATERIALIZED VIEW AS statement, whose execution plan you wish to see.

OUTPUTS

       The command's result is a textual description of the plan selected for the statement,
       optionally annotated with execution statistics.  Section 14.1 describes the information
       provided.

NOTES

       In order to allow the PostgreSQL query planner to make reasonably informed decisions when
       optimizing queries, the pg_statistic data should be up-to-date for all tables used in the
       query. Normally the autovacuum daemon will take care of that automatically. But if a table
       has recently had substantial changes in its contents, you might need to do a manual
       ANALYZE rather than wait for autovacuum to catch up with the changes.

       In order to measure the run-time cost of each node in the execution plan, the current
       implementation of EXPLAIN ANALYZE adds profiling overhead to query execution. As a result,
       running EXPLAIN ANALYZE on a query can sometimes take significantly longer than executing
       the query normally. The amount of overhead depends on the nature of the query, as well as
       the platform being used. The worst case occurs for plan nodes that in themselves require
       very little time per execution, and on machines that have relatively slow operating system
       calls for obtaining the time of day.

EXAMPLES

       To show the plan for a simple query on a table with a single integer column and 10000
       rows:

           EXPLAIN SELECT * FROM foo;

                                  QUERY PLAN
           ---------------------------------------------------------
            Seq Scan on foo  (cost=0.00..155.00 rows=10000 width=4)
           (1 row)

       Here is the same query, with JSON output formatting:

           EXPLAIN (FORMAT JSON) SELECT * FROM foo;
                      QUERY PLAN
           --------------------------------
            [                             +
              {                           +
                "Plan": {                 +
                  "Node Type": "Seq Scan",+
                  "Relation Name": "foo", +
                  "Alias": "foo",         +
                  "Startup Cost": 0.00,   +
                  "Total Cost": 155.00,   +
                  "Plan Rows": 10000,     +
                  "Plan Width": 4         +
                }                         +
              }                           +
            ]
           (1 row)

       If there is an index and we use a query with an indexable WHERE condition, EXPLAIN might
       show a different plan:

           EXPLAIN SELECT * FROM foo WHERE i = 4;

                                    QUERY PLAN
           --------------------------------------------------------------
            Index Scan using fi on foo  (cost=0.00..5.98 rows=1 width=4)
              Index Cond: (i = 4)
           (2 rows)

       Here is the same query, but in YAML format:

           EXPLAIN (FORMAT YAML) SELECT * FROM foo WHERE i='4';
                     QUERY PLAN
           -------------------------------
            - Plan:                      +
                Node Type: "Index Scan"  +
                Scan Direction: "Forward"+
                Index Name: "fi"         +
                Relation Name: "foo"     +
                Alias: "foo"             +
                Startup Cost: 0.00       +
                Total Cost: 5.98         +
                Plan Rows: 1             +
                Plan Width: 4            +
                Index Cond: "(i = 4)"
           (1 row)

       XML format is left as an exercise for the reader.

       Here is the same plan with cost estimates suppressed:

           EXPLAIN (COSTS FALSE) SELECT * FROM foo WHERE i = 4;

                   QUERY PLAN
           ----------------------------
            Index Scan using fi on foo
              Index Cond: (i = 4)
           (2 rows)

       Here is an example of a query plan for a query using an aggregate function:

           EXPLAIN SELECT sum(i) FROM foo WHERE i < 10;

                                        QUERY PLAN
           ---------------------------------------------------------------------
            Aggregate  (cost=23.93..23.93 rows=1 width=4)
              ->  Index Scan using fi on foo  (cost=0.00..23.92 rows=6 width=4)
                    Index Cond: (i < 10)
           (3 rows)

       Here is an example of using EXPLAIN EXECUTE to display the execution plan for a prepared
       query:

           PREPARE query(int, int) AS SELECT sum(bar) FROM test
               WHERE id > $1 AND id < $2
               GROUP BY foo;

           EXPLAIN ANALYZE EXECUTE query(100, 200);

                                                                  QUERY PLAN
           -------------------------------------------------------------------------------------------------------------------------
            HashAggregate  (cost=10.77..10.87 rows=10 width=12) (actual time=0.043..0.044 rows=10 loops=1)
              Group Key: foo
              Batches: 1  Memory Usage: 24kB
              ->  Index Scan using test_pkey on test  (cost=0.29..10.27 rows=99 width=8) (actual time=0.009..0.025 rows=99 loops=1)
                    Index Cond: ((id > 100) AND (id < 200))
            Planning Time: 0.244 ms
            Execution Time: 0.073 ms
           (7 rows)

       Of course, the specific numbers shown here depend on the actual contents of the tables
       involved. Also note that the numbers, and even the selected query strategy, might vary
       between PostgreSQL releases due to planner improvements. In addition, the ANALYZE command
       uses random sampling to estimate data statistics; therefore, it is possible for cost
       estimates to change after a fresh run of ANALYZE, even if the actual distribution of data
       in the table has not changed.

       Notice that the previous example showed a “custom” plan for the specific parameter values
       given in EXECUTE. We might also wish to see the generic plan for a parameterized query,
       which can be done with GENERIC_PLAN:

           EXPLAIN (GENERIC_PLAN)
             SELECT sum(bar) FROM test
               WHERE id > $1 AND id < $2
               GROUP BY foo;

                                             QUERY PLAN
           -------------------------------------------------------------------------------
            HashAggregate  (cost=26.79..26.89 rows=10 width=12)
              Group Key: foo
              ->  Index Scan using test_pkey on test  (cost=0.29..24.29 rows=500 width=8)
                    Index Cond: ((id > $1) AND (id < $2))
           (4 rows)

       In this case the parser correctly inferred that $1 and $2 should have the same data type
       as id, so the lack of parameter type information from PREPARE was not a problem. In other
       cases it might be necessary to explicitly specify types for the parameter symbols, which
       can be done by casting them, for example:

           EXPLAIN (GENERIC_PLAN)
             SELECT sum(bar) FROM test
               WHERE id > $1::integer AND id < $2::integer
               GROUP BY foo;

COMPATIBILITY

       There is no EXPLAIN statement defined in the SQL standard.

       The following syntax was used before PostgreSQL version 9.0 and is still supported:

           EXPLAIN [ ANALYZE ] [ VERBOSE ] statement

       Note that in this syntax, the options must be specified in exactly the order shown.

SEE ALSO

       ANALYZE(7)