CREATE STATISTICS - CockroachDB

Use the CREATE STATISTICS to to use. Once you and load data into it (e.g., , ), table statistics can be generated. Table statistics help the cost-based optimizer determine the cardinality of the rows used in each query, which helps to predict more accurate costs. For compatibility with PostgreSQL, CockroachDB supports the ANALYZE/ANALYSE statement as an alias for CREATE STATISTICS. For syntax, see Aliases. By default, CockroachDB on all indexed columns and up to 100 non-indexed columns, and automatically collects multi-column statistics on columns that prefix each index. As a result, most users do not need to directly issue CREATE STATISTICS statements.

Syntax

Parameters

Parameter	Description
`statistics\_name`	The name of the set of statistics you are creating.
`opt\_stats\_columns`	The name of the column(s) to create statistics for.
`create\_stats\_target`	The name of the table to create statistics for.
`opt\_as\_of\_clause`	Create historical stats using the clause. For instructions, see Create statistics as of a given time.

Required privileges

The user must have the CREATE on the parent database.

Aliases

For , CockroachDB supports ANALYZE and ANALYSE as aliases for CREATE STATISTICS.

Alias syntax

Alias parameters

Parameter	Description
`analyze\_target`	The name of the table to create statistics for.

Examples

Setup

To follow along, run to start a temporary, in-memory cluster with the sample dataset preloaded:

$ cockroach demo

Create statistics on a single column

> CREATE STATISTICS revenue_stats ON revenue FROM rides;

> SHOW STATISTICS FOR TABLE rides;

  statistics_name |       column_names        |          created           | row_count | distinct_count | null_count | avg_size |    histogram_id
------------------+---------------------------+----------------------------+-----------+----------------+------------+----------+---------------------
  __auto__        | {city}                    | 2022-04-20 22:43:08.851613 |       500 |              9 |          0 |       12 | 755053982033936385
  __auto__        | {id}                      | 2022-04-20 22:43:08.851613 |       500 |            500 |          0 |       26 | 755053982039703553
  __auto__        | {city,id}                 | 2022-04-20 22:43:08.851613 |       500 |            500 |          0 |       37 |               NULL
  __auto__        | {rider_id}                | 2022-04-20 22:43:08.851613 |       500 |             50 |          0 |       17 | 755053982050910209
  __auto__        | {city,rider_id}           | 2022-04-20 22:43:08.851613 |       500 |             50 |          0 |       29 |               NULL
  __auto__        | {vehicle_city}            | 2022-04-20 22:43:08.851613 |       500 |              9 |          0 |       11 | 755053982061690881
  __auto__        | {vehicle_id}              | 2022-04-20 22:43:08.851613 |       500 |             15 |          0 |       17 | 755053982067392513
  __auto__        | {vehicle_city,vehicle_id} | 2022-04-20 22:43:08.851613 |       500 |             15 |          0 |       28 |               NULL
  __auto__        | {start_address}           | 2022-04-20 22:43:08.851613 |       500 |            500 |          0 |       25 | 755053982080991233
  __auto__        | {end_address}             | 2022-04-20 22:43:08.851613 |       500 |            500 |          0 |       25 | 755053982087544833
  __auto__        | {start_time}              | 2022-04-20 22:43:08.851613 |       500 |             30 |          0 |        7 | 755053982093443073
  __auto__        | {end_time}                | 2022-04-20 22:43:08.851613 |       500 |            367 |          0 |        7 | 755053982099472385
  __auto__        | {revenue}                 | 2022-04-20 22:43:08.851613 |       500 |            100 |          0 |        6 | 755053982105337857
  revenue_stats   | {revenue}                 | 2022-04-20 22:35:42.279266 |       500 |            100 |          0 |        6 | 755052518729449473
(14 rows)

Statistics are automatically collected for all columns, making the revenue_stats statistics a duplicate of the statistics automatically collected on the revenue column.

Create statistics on multiple columns

> CREATE STATISTICS city_revenue_stats ON city, revenue FROM rides;

> SHOW STATISTICS FOR TABLE rides;

   statistics_name   |       column_names        |          created           | row_count | distinct_count | null_count | avg_size |    histogram_id
---------------------+---------------------------+----------------------------+-----------+----------------+------------+----------+---------------------
  __auto__           | {city}                    | 2022-04-20 22:43:08.851613 |       500 |              9 |          0 |       12 | 755053982033936385
  __auto__           | {id}                      | 2022-04-20 22:43:08.851613 |       500 |            500 |          0 |       26 | 755053982039703553
  __auto__           | {city,id}                 | 2022-04-20 22:43:08.851613 |       500 |            500 |          0 |       37 |               NULL
  __auto__           | {rider_id}                | 2022-04-20 22:43:08.851613 |       500 |             50 |          0 |       17 | 755053982050910209
  __auto__           | {city,rider_id}           | 2022-04-20 22:43:08.851613 |       500 |             50 |          0 |       29 |               NULL
  __auto__           | {vehicle_city}            | 2022-04-20 22:43:08.851613 |       500 |              9 |          0 |       11 | 755053982061690881
  __auto__           | {vehicle_id}              | 2022-04-20 22:43:08.851613 |       500 |             15 |          0 |       17 | 755053982067392513
  __auto__           | {vehicle_city,vehicle_id} | 2022-04-20 22:43:08.851613 |       500 |             15 |          0 |       28 |               NULL
  __auto__           | {start_address}           | 2022-04-20 22:43:08.851613 |       500 |            500 |          0 |       25 | 755053982080991233
  __auto__           | {end_address}             | 2022-04-20 22:43:08.851613 |       500 |            500 |          0 |       25 | 755053982087544833
  __auto__           | {start_time}              | 2022-04-20 22:43:08.851613 |       500 |             30 |          0 |        7 | 755053982093443073
  __auto__           | {end_time}                | 2022-04-20 22:43:08.851613 |       500 |            367 |          0 |        7 | 755053982099472385
  __auto__           | {revenue}                 | 2022-04-20 22:43:08.851613 |       500 |            100 |          0 |        6 | 755053982105337857
  revenue_stats      | {revenue}                 | 2022-04-20 22:45:40.272665 |       500 |            100 |          0 |        6 | 755054478211481601
  city_revenue_stats | {city,revenue}            | 2022-04-20 22:45:46.925799 |       500 |            372 |          0 |       18 |               NULL
(15 rows)

Multi-column statistics are automatically collected for all columns that prefix an index. In this example, city and revenue are not an index prefix, making the city_revenue_stats statistics unique for the table.

Create statistics on a default set of columns

The CREATE STATISTICS statement shown below automatically figures out which columns to get statistics on.

> CREATE STATISTICS users_stats FROM users;

This statement creates statistics identical to the statistics that CockroachDB creates automatically.

> SHOW STATISTICS FOR TABLE users;

  statistics_name | column_names  |          created           | row_count | distinct_count | null_count | avg_size |    histogram_id
------------------+---------------+----------------------------+-----------+----------------+------------+----------+---------------------
  __auto__        | {city}        | 2022-04-20 22:43:08.819069 |        50 |              9 |          0 |       12 | 755053981927636993
  __auto__        | {id}          | 2022-04-20 22:43:08.819069 |        50 |             50 |          0 |       27 | 755053981933273089
  __auto__        | {city,id}     | 2022-04-20 22:43:08.819069 |        50 |             50 |          0 |       38 |               NULL
  __auto__        | {name}        | 2022-04-20 22:43:08.819069 |        50 |             49 |          0 |       16 | 755053981944184833
  __auto__        | {address}     | 2022-04-20 22:43:08.819069 |        50 |             50 |          0 |       26 | 755053981949001729
  __auto__        | {credit_card} | 2022-04-20 22:43:08.819069 |        50 |             50 |          0 |       12 | 755053981954015233
  users_stats     | {city}        | 2022-04-20 22:46:14.878975 |        50 |              9 |          0 |       12 | 755054591614943233
  users_stats     | {id}          | 2022-04-20 22:46:14.878975 |        50 |             50 |          0 |       27 | 755054591622447105
  users_stats     | {city,id}     | 2022-04-20 22:46:14.878975 |        50 |             50 |          0 |       38 |               NULL
  users_stats     | {name}        | 2022-04-20 22:46:14.878975 |        50 |             49 |          0 |       16 | 755054591638634497
  users_stats     | {address}     | 2022-04-20 22:46:14.878975 |        50 |             50 |          0 |       26 | 755054591645712385
  users_stats     | {credit_card} | 2022-04-20 22:46:14.878975 |        50 |             50 |          0 |       12 | 755054591652691969
(12 rows)

Create statistics as of a given time

To create statistics as of a given time (in this example, 1 minute ago to avoid interfering with the production workload), run a statement like the following:

> CREATE STATISTICS vehicle_stats_1 FROM vehicles AS OF SYSTEM TIME '-1m';

For more information about how the AS OF SYSTEM TIME clause works, including supported time formats, see .

Create partial statistics using extremes

To create partial statistics that collect statistics on the highest and lowest index values:

SET enable_create_stats_using_extremes = true;

CREATE STATISTICS rides_extremes_stats FROM rides USING EXTREMES;

This creates partial statistics on all single-column prefixes of non-inverted indexes in the rides table by scanning only the highest and lowest index values, rather than performing a full table scan. You can also create extremes statistics on specific columns, provided there is an index with the specified column as the first key column:

CREATE STATISTICS revenue_extremes_stats ON revenue FROM rides USING EXTREMES;

Delete statistics

To delete statistics for all tables in all databases:

DELETE FROM system.table_statistics WHERE true;

To delete a named set of statistics (e.g, one named “users_stats”), run a query like the following:

DELETE FROM system.table_statistics WHERE name = 'users_stats';

For more information about the DELETE statement, see .

View statistics jobs

Every time the CREATE STATISTICS statement is executed, it starts a background job. This is true for queries issued by your application as well as queries issued for . To view statistics jobs, there are two options:

Use to see all statistics jobs that were created by user queries (i.e., someone entering CREATE STATISTICS at the SQL prompt or via application code):

> WITH x AS (SHOW JOBS) SELECT * FROM x WHERE job_type LIKE '%CREATE STATS%';

        job_id       |   job_type   |                                           description                                            | statement | user_name |  status   | running_status |          created           |          started           |          finished          |          modified          | fraction_completed | error | coordinator_id |      trace_id       |          last_run          |          next_run          | num_runs | execution_errors
---------------------+--------------+--------------------------------------------------------------------------------------------------+-----------+-----------+-----------+----------------+----------------------------+----------------------------+----------------------------+----------------------------+--------------------+-------+----------------+---------------------+----------------------------+----------------------------+----------+-------------------
  755053959919108097 | CREATE STATS | CREATE STATISTICS revenue_stats ON revenue FROM movr.public.rides                                |           | demo      | succeeded | NULL           | 2022-04-20 22:43:02.104229 | 2022-04-20 22:43:02.109754 | 2022-04-20 22:43:02.123381 | 2022-04-20 22:43:02.122569 |                  1 |       |              1 | 2935658651779633570 | 2022-04-20 22:43:02.109755 | 2022-04-20 22:43:32.109755 |        1 | {}
  755054478158364673 | CREATE STATS | CREATE STATISTICS revenue_stats ON revenue FROM movr.public.rides                                |           | demo      | succeeded | NULL           | 2022-04-20 22:45:40.25829  | 2022-04-20 22:45:40.26361  | 2022-04-20 22:45:40.275882 | 2022-04-20 22:45:40.275032 |                  1 |       |              1 | 3941365223642966402 | 2022-04-20 22:45:40.263611 | 2022-04-20 22:46:10.263611 |        1 | {}
  755054499947053057 | CREATE STATS | CREATE STATISTICS city_revenue_stats ON city, revenue FROM movr.public.rides                     |           | demo      | succeeded | NULL           | 2022-04-20 22:45:46.907672 | 2022-04-20 22:45:46.912906 | 2022-04-20 22:45:46.929632 | 2022-04-20 22:45:46.928409 |                  1 |       |              1 | 6666823949040131150 | 2022-04-20 22:45:46.912906 | 2022-04-20 22:46:16.912906 |        1 | {}
  755054591559172097 | CREATE STATS | CREATE STATISTICS users_stats FROM movr.public.users                                             |           | demo      | succeeded | NULL           | 2022-04-20 22:46:14.865479 | 2022-04-20 22:46:14.869725 | 2022-04-20 22:46:14.895666 | 2022-04-20 22:46:14.89469  |                  1 |       |              1 | 6731618360724088456 | 2022-04-20 22:46:14.869726 | 2022-04-20 22:46:44.869726 |        1 | {}
  755055101600661505 | CREATE STATS | CREATE STATISTICS vehicle_stats_1 FROM movr.public.vehicles WITH OPTIONS AS OF SYSTEM TIME '-1m' |           | demo      | succeeded | NULL           | 2022-04-20 22:48:50.517787 | 2022-04-20 22:48:50.523002 | 2022-04-20 22:48:50.552397 | 2022-04-20 22:48:50.551333 |                  1 |       |              1 | 8797094911788373312 | 2022-04-20 22:48:50.523003 | 2022-04-20 22:49:20.523003 |        1 | {}
(5 rows)

Use SHOW AUTOMATIC JOBS to see statistics jobs that were created by :

> WITH x AS (SHOW AUTOMATIC JOBS) SELECT * FROM x WHERE job_type LIKE '%CREATE STATS%';

        job_id       |     job_type      |                             description                             |                                         statement                                          | user_name |  status   | running_status |          created           |          started           |          finished          |          modified          | fraction_completed | error | coordinator_id |      trace_id       |          last_run          |          next_run          | num_runs | execution_errors
---------------------+-------------------+---------------------------------------------------------------------+--------------------------------------------------------------------------------------------+-----------+-----------+----------------+----------------------------+----------------------------+----------------------------+----------------------------+--------------------+-------+----------------+---------------------+----------------------------+----------------------------+----------+-------------------
  755046859132338177 | AUTO CREATE STATS | Table statistics refresh for movr.public.vehicle_location_histories | CREATE STATISTICS __auto__ FROM [109] WITH OPTIONS THROTTLING 0.9 AS OF SYSTEM TIME '-30s' | root      | succeeded | NULL           | 2022-04-20 22:06:55.116073 | 2022-04-20 22:06:55.126215 | 2022-04-20 22:06:55.81112  | 2022-04-20 22:06:55.809757 |                  1 |       |              1 | 7300707583932918060 | 2022-04-20 22:06:55.126216 | 2022-04-20 22:07:25.126216 |        1 | {}
  755046861432094721 | AUTO CREATE STATS | Table statistics refresh for movr.public.user_promo_codes           | CREATE STATISTICS __auto__ FROM [111] WITH OPTIONS THROTTLING 0.9 AS OF SYSTEM TIME '-30s' | root      | succeeded | NULL           | 2022-04-20 22:06:55.817903 | 2022-04-20 22:06:55.825208 | 2022-04-20 22:06:55.858624 | 2022-04-20 22:06:55.857442 |                  1 |       |              1 |  944378671132247270 | 2022-04-20 22:06:55.825209 | 2022-04-20 22:07:25.825209 |        1 | {}
  755046861588529153 | AUTO CREATE STATS | Table statistics refresh for movr.public.rides                      | CREATE STATISTICS __auto__ FROM [108] WITH OPTIONS THROTTLING 0.9 AS OF SYSTEM TIME '-30s' | root      | succeeded | NULL           | 2022-04-20 22:06:55.865648 | 2022-04-20 22:06:55.871917 | 2022-04-20 22:06:56.772123 | 2022-04-20 22:06:56.770818 |                  1 |       |              1 |  107998367520189635 | 2022-04-20 22:06:55.871917 | 2022-04-20 22:07:25.871917 |        1 | {}
  755046864579690497 | AUTO CREATE STATS | Table statistics refresh for movr.public.vehicles                   | CREATE STATISTICS __auto__ FROM [107] WITH OPTIONS THROTTLING 0.9 AS OF SYSTEM TIME '-30s' | root      | succeeded | NULL           | 2022-04-20 22:06:56.778476 | 2022-04-20 22:06:56.785127 | 2022-04-20 22:06:56.887308 | 2022-04-20 22:06:56.886099 |                  1 |       |              1 | 1370771572055208171 | 2022-04-20 22:06:56.785128 | 2022-04-20 22:07:26.785128 |        1 | {}
  755046864953376769 | AUTO CREATE STATS | Table statistics refresh for movr.public.promo_codes                | CREATE STATISTICS __auto__ FROM [110] WITH OPTIONS THROTTLING 0.9 AS OF SYSTEM TIME '-30s' | root      | succeeded | NULL           | 2022-04-20 22:06:56.892515 | 2022-04-20 22:06:56.898684 | 2022-04-20 22:06:57.416186 | 2022-04-20 22:06:57.414741 |                  1 |       |              1 | 3756312875539405235 | 2022-04-20 22:06:56.898685 | 2022-04-20 22:07:26.898685 |        1 | {}
  755046866689851393 | AUTO CREATE STATS | Table statistics refresh for movr.public.users                      | CREATE STATISTICS __auto__ FROM [106] WITH OPTIONS THROTTLING 0.9 AS OF SYSTEM TIME '-30s' | root      | succeeded | NULL           | 2022-04-20 22:06:57.422449 | 2022-04-20 22:06:57.428999 | 2022-04-20 22:06:57.573797 | 2022-04-20 22:06:57.57256  |                  1 |       |              1 | 6690084610338235566 | 2022-04-20 22:06:57.428999 | 2022-04-20 22:07:27.428999 |        1 | {}
(6 rows)

​Syntax

​Parameters

​Required privileges

​Aliases

​Alias syntax

​Alias parameters

​Examples

​Setup

​Create statistics on a single column

​Create statistics on multiple columns

​Create statistics on a default set of columns

​Create statistics as of a given time

​Create partial statistics using extremes

​Delete statistics

​View statistics jobs

​See also