CREATE STATISTICS
CREATE STATISTICS
CREATE STATISTICS  define extended statistics
Synopsis
CREATE STATISTICS [ IF NOT EXISTS ]statistics_name
[ (statistics_kind
[, ... ] ) ] ONcolumn_name
,column_name
[, ...] FROMtable_name
Description
CREATE STATISTICS
will create a new extended statistics
object tracking data about the specified table, foreign table or
materialized view. The statistics object will be created in the current
database and will be owned by the user issuing the command.
If a schema name is given (for example,
CREATE STATISTICS
myschema.mystat ...
) then the statistics object is created in the
specified schema. Otherwise it is created in the current schema.
The name of the statistics object must be distinct from the name of any
other statistics object in the same schema.
Parameters

IF NOT EXISTS

Do not throw an error if a statistics object with the same name already exists. A notice is issued in this case. Note that only the name of the statistics object is considered here, not the details of its definition.

statistics_name

The name (optionally schemaqualified) of the statistics object to be created.

statistics_kind

A statistics kind to be computed in this statistics object. Currently supported kinds are
ndistinct
, which enables ndistinct statistics,dependencies
, which enables functional dependency statistics, andmcv
which enables mostcommon values lists. If this clause is omitted, all supported statistics kinds are included in the statistics object. For more information, see Section 14.2.2 and Section 71.2 . 
column_name

The name of a table column to be covered by the computed statistics. At least two column names must be given; the order of the column names is insignificant.

table_name

The name (optionally schemaqualified) of the table containing the column(s) the statistics are computed on; see ANALYZE for an explanation of the handling of inheritance and partitions.
Notes
You must be the owner of a table to create a statistics object reading it. Once created, however, the ownership of the statistics object is independent of the underlying table(s).
Extended statistics are not currently used by the planner for selectivity estimations made for table joins. This limitation will likely be removed in a future version of PostgreSQL .
Examples
Create table
t1
with two functionally dependent columns, i.e.,
knowledge of a value in the first column is sufficient for determining the
value in the other column. Then functional dependency statistics are built
on those columns:
CREATE TABLE t1 ( a int, b int ); INSERT INTO t1 SELECT i/100, i/500 FROM generate_series(1,1000000) s(i); ANALYZE t1;  the number of matching rows will be drastically underestimated: EXPLAIN ANALYZE SELECT * FROM t1 WHERE (a = 1) AND (b = 0); CREATE STATISTICS s1 (dependencies) ON a, b FROM t1; ANALYZE t1;  now the row count estimate is more accurate: EXPLAIN ANALYZE SELECT * FROM t1 WHERE (a = 1) AND (b = 0);
Without functionaldependency statistics, the planner would assume
that the two
WHERE
conditions are independent, and would
multiply their selectivities together to arrive at a muchtoosmall
row count estimate.
With such statistics, the planner recognizes that the
WHERE
conditions are redundant and does not underestimate the row count.
Create table
t2
with two perfectly correlated columns
(containing identical data), and a MCV list on those columns:
CREATE TABLE t2 ( a int, b int ); INSERT INTO t2 SELECT mod(i,100), mod(i,100) FROM generate_series(1,1000000) s(i); CREATE STATISTICS s2 (mcv) ON a, b FROM t2; ANALYZE t2;  valid combination (found in MCV) EXPLAIN ANALYZE SELECT * FROM t2 WHERE (a = 1) AND (b = 1);  invalid combination (not found in MCV) EXPLAIN ANALYZE SELECT * FROM t2 WHERE (a = 1) AND (b = 2);
The MCV list gives the planner more detailed information about the specific values that commonly appear in the table, as well as an upper bound on the selectivities of combinations of values that do not appear in the table, allowing it to generate better estimates in both cases.
Compatibility
There is no
CREATE STATISTICS
command in the SQL standard.