EXPLAIN

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 units of disk page fetches). Actually two numbers are shown: the start-up time before the first row can be returned, and the total time to return all the rows. For most queries the total time is what matters, but in contexts such as a subquery in EXISTS, the planner will choose the smallest start-up time instead of the smallest total time (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. The total elapsed time expended within each plan node (in milliseconds) and total number of rows it actually returned are added to the display. This is useful for seeing whether the planner's estimates are close to reality.

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

Notes

There is only sparse documentation on the optimizer's use of cost information in PostgreSQL. Refer to Section 14.1 for more information.

In order to allow the PostgreSQL query planner to make reasonably informed decisions when optimizing queries, the ANALYZE statement should be run to record statistics about the distribution of data within the table. If you have not done this (or if the statistical distribution of the data in the table has changed significantly since the last time ANALYZE was run), the estimated costs are unlikely to conform to the real properties of the query, and consequently an inferior query plan might be chosen.

In order to measure the run-time cost of each node in the execution plan, the current implementation of EXPLAIN ANALYZE can add considerable 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.

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 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 output:

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 output is left as an exercise to the reader.

Here is the same plan with costs 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=39.53..39.53 rows=1 width=8) (actual time=0.661..0.672 rows=7 loops=1)
   ->  Index Scan using test_pkey on test  (cost=0.00..32.97 rows=1311 width=8) (actual time=0.050..0.395 rows=99 loops=1)
         Index Cond: ((id > $1) AND (id < $2))
 Total runtime: 0.851 ms
(4 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