EXPLAIN(7)

NAME
EXPLAIN - show the execution plan of a statement

SYNOPSIS

EXPLAIN [ ( option [, ...] ) ] statement
EXPLAIN [ ANALYZE ] [ VERBOSE ] statement
where option can be one of:
    ANALYZE [ boolean ]
    VERBOSE [ boolean ]
    COSTS [ boolean ]
    BUFFERS [ boolean ]
    TIMING [ 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, CREATE TABLE AS, or EXECUTE statement without letting the command affect your data, use this approach:

        BEGIN;
        EXPLAIN ANALYZE ...;
        ROLLBACK;

Only the ANALYZE and VERBOSE options can be specified, and only in that order, without surrounding the option list in parentheses. Prior to PostgreSQL 9.0, the unparenthesized syntax was the only one supported. It is expected that all new options will be supported only in the parenthesized syntax.

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. 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.

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, and the number of temp blocks read and written. 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 temp 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 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.

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, 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, “Using EXPLAIN”, in the documentation 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(7) 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=9.54..9.54 rows=1 width=8) (actual time=0.156..0.161 rows=11 loops=1)
       Group Key: foo
       ->  Index Scan using test_pkey on test  (cost=0.29..9.29 rows=50 width=8) (actual time=0.039..0.091 rows=99 loops=1)
             Index Cond: ((id > $1) AND (id < $2))
     Planning time: 0.197 ms
     Execution time: 0.225 ms
    (6 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.

COMPATIBILITY

There is no EXPLAIN statement defined in the SQL standard.

SEE ALSO
ANALYZE(7)