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EXPLAIN

   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. Buffers
          information is automatically included when ANALYZE is used.

   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),
          the amount of WAL generated in bytes and the number of times the
          WAL buffers became full. 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 r
ows=10.00 loops=1)
   Group Key: foo
   Batches: 1  Memory Usage: 24kB
   Buffers: shared hit=4
   ->  Index Scan using test_pkey on test  (cost=0.29..10.27 rows=99 width=8) (a
ctual time=0.009..0.025 rows=99.00 loops=1)
         Index Cond: ((id > 100) AND (id < 200))
         Index Searches: 1
         Buffers: shared hit=4
 Planning Time: 0.244 ms
 Execution Time: 0.073 ms
(10 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