13.2. Statistics Used by the Planner

As we saw in the previous section, the query planner needs to estimate the number of rows retrieved by a query in order to make good choices of query plans. This section provides a quick look at the statistics that the system uses for these estimates.

One component of the statistics is the total number of entries in each table and index, as well as the number of disk blocks occupied by each table and index. This information is kept in the table pg_class, in the columns reltuples and relpages. We can look at it with queries similar to this one:

SELECT relname, relkind, reltuples, relpages FROM pg_class WHERE relname LIKE 'tenk1%';

       relname        | relkind | reltuples | relpages
 tenk1                | r       |     10000 |      358
 tenk1_hundred        | i       |     10000 |       30
 tenk1_thous_tenthous | i       |     10000 |       30
 tenk1_unique1        | i       |     10000 |       30
 tenk1_unique2        | i       |     10000 |       30
(5 rows)

Here we can see that tenk1 contains 10000 rows, as do its indexes, but the indexes are (unsurprisingly) much smaller than the table.

For efficiency reasons, reltuples and relpages are not updated on-the-fly, and so they usually contain somewhat out-of-date values. They are updated by VACUUM, ANALYZE, and a few DDL commands such as CREATE INDEX. A stand-alone ANALYZE, that is one not part of VACUUM, generates an approximate reltuples value since it does not read every row of the table. The planner will scale the values it finds in pg_class to match the current physical table size, thus obtaining a closer approximation.

Most queries retrieve only a fraction of the rows in a table, due to having WHERE clauses that restrict the rows to be examined. The planner thus needs to make an estimate of the selectivity of WHERE clauses, that is, the fraction of rows that match each condition in the WHERE clause. The information used for this task is stored in the pg_statistic system catalog. Entries in pg_statistic are updated by the ANALYZE and VACUUM ANALYZE commands, and are always approximate even when freshly updated.

Rather than look at pg_statistic directly, it's better to look at its view pg_stats when examining the statistics manually. pg_stats is designed to be more easily readable. Furthermore, pg_stats is readable by all, whereas pg_statistic is only readable by a superuser. (This prevents unprivileged users from learning something about the contents of other people's tables from the statistics. The pg_stats view is restricted to show only rows about tables that the current user can read.) For example, we might do:

SELECT attname, n_distinct, most_common_vals FROM pg_stats WHERE tablename = 'road';

 attname | n_distinct |                                                                                                                                                                                  most_common_vals                                                                                                                                                                                   
 name    |  -0.467008 | {"I- 580                        Ramp","I- 880                        Ramp","Sp Railroad                       ","I- 580                            ","I- 680                        Ramp","I- 80                         Ramp","14th                          St  ","5th                           St  ","Mission                       Blvd","I- 880                            "}
 thepath |         20 | {"[(-122.089,37.71),(-122.0886,37.711)]"}
(2 rows)

pg_stats is described in detail in Section 43.46.

The amount of information stored in pg_statistic, in particular the maximum number of entries in the most_common_vals and histogram_bounds arrays for each column, can be set on a column-by-column basis using the ALTER TABLE SET STATISTICS command, or globally by setting the default_statistics_target configuration variable. The default limit is presently 10 entries. Raising the limit may allow more accurate planner estimates to be made, particularly for columns with irregular data distributions, at the price of consuming more space in pg_statistic and slightly more time to compute the estimates. Conversely, a lower limit may be appropriate for columns with simple data distributions.