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postgresql-docs-8.0.11-0.1.20060mdk.x86_64.rpm

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><A
NAME="PLANNER-STATS"
>13.2. Statistics Used by the Planner</A
></H1
><A
NAME="AEN14821"
></A
><P
>   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.
  </P
><P
>   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
   <TT
CLASS="STRUCTNAME"
>pg_class</TT
> in the columns <TT
CLASS="STRUCTFIELD"
>reltuples</TT
>
   and <TT
CLASS="STRUCTFIELD"
>relpages</TT
>.  We can look at it
   with queries similar to this one:

</P><PRE
CLASS="SCREEN"
>SELECT relname, relkind, reltuples, relpages FROM pg_class WHERE relname LIKE 'tenk1%';

    relname    | relkind | reltuples | relpages
---------------+---------+-----------+----------
 tenk1         | r       |     10000 |      233
 tenk1_hundred | i       |     10000 |       30
 tenk1_unique1 | i       |     10000 |       30
 tenk1_unique2 | i       |     10000 |       30
(4 rows)</PRE
><P>

   Here we can see that <TT
CLASS="STRUCTNAME"
>tenk1</TT
> contains 10000
   rows, as do its indexes, but the indexes are (unsurprisingly) much
   smaller than the table.
  </P
><P
>   For efficiency reasons, <TT
CLASS="STRUCTFIELD"
>reltuples</TT
> 
   and <TT
CLASS="STRUCTFIELD"
>relpages</TT
> are not updated on-the-fly,
   and so they usually contain somewhat out-of-date values.
   They are updated by <TT
CLASS="COMMAND"
>VACUUM</TT
>, <TT
CLASS="COMMAND"
>ANALYZE</TT
>, and a
   few DDL commands such as <TT
CLASS="COMMAND"
>CREATE INDEX</TT
>.  A stand-alone
   <TT
CLASS="COMMAND"
>ANALYZE</TT
>, that is one not part of <TT
CLASS="COMMAND"
>VACUUM</TT
>,
   generates an approximate <TT
CLASS="STRUCTFIELD"
>reltuples</TT
> value
   since it does not read every row of the table.  The planner
   will scale the values it finds in <TT
CLASS="STRUCTNAME"
>pg_class</TT
>
   to match the current physical table size, thus obtaining a closer
   approximation.
  </P
><A
NAME="AEN14841"
></A
><P
>   Most queries retrieve only a fraction of the rows in a table, due
   to having <TT
CLASS="LITERAL"
>WHERE</TT
> clauses that restrict the rows to be examined.
   The planner thus needs to make an estimate of the
   <I
CLASS="FIRSTTERM"
>selectivity</I
> of <TT
CLASS="LITERAL"
>WHERE</TT
> clauses, that is, the fraction of
   rows that match each condition in the <TT
CLASS="LITERAL"
>WHERE</TT
> clause.  The information
   used for this task is stored in the <TT
CLASS="STRUCTNAME"
>pg_statistic</TT
>
   system catalog.  Entries in <TT
CLASS="STRUCTNAME"
>pg_statistic</TT
> are
   updated by <TT
CLASS="COMMAND"
>ANALYZE</TT
> and <TT
CLASS="COMMAND"
>VACUUM ANALYZE</TT
> commands
   and are always approximate even when freshly updated.
  </P
><A
NAME="AEN14852"
></A
><P
>   Rather than look at <TT
CLASS="STRUCTNAME"
>pg_statistic</TT
> directly,
   it's better to look at its view <TT
CLASS="STRUCTNAME"
>pg_stats</TT
>
   when examining the statistics manually.  <TT
CLASS="STRUCTNAME"
>pg_stats</TT
>
   is designed to be more easily readable.  Furthermore,
   <TT
CLASS="STRUCTNAME"
>pg_stats</TT
> is readable by all, whereas
   <TT
CLASS="STRUCTNAME"
>pg_statistic</TT
> 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
   <TT
CLASS="STRUCTNAME"
>pg_stats</TT
> view is restricted to show only
   rows about tables that the current user can read.)
   For example, we might do:

</P><PRE
CLASS="SCREEN"
>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)</PRE
><P>
  </P
><P
>   <TT
CLASS="STRUCTNAME"
>pg_stats</TT
> is described in detail in
   <A
HREF="view-pg-stats.html"
>Section 41.36</A
>.
  </P
><P
>   The amount of information stored in <TT
CLASS="STRUCTNAME"
>pg_statistic</TT
>,
   in particular the maximum number of entries in the
   <TT
CLASS="STRUCTFIELD"
>most_common_vals</TT
> and <TT
CLASS="STRUCTFIELD"
>histogram_bounds</TT
>
   arrays for each column, can be set on a
   column-by-column basis using the <TT
CLASS="COMMAND"
>ALTER TABLE SET STATISTICS</TT
>
   command, or globally by setting the
   <A
HREF="runtime-config.html#GUC-DEFAULT-STATISTICS-TARGET"
>default_statistics_target</A
> 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 <TT
CLASS="STRUCTNAME"
>pg_statistic</TT
> and slightly more
   time to compute the estimates.  Conversely, a lower limit may be
   appropriate for columns with simple data distributions.
  </P
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