The persistent optimizer statistics feature improves plan stability by storing statistics to disk and making them persistent across server restarts so that the optimizer is more likely to make consistent choices each time for a given query.
        Optimizer statistics are persisted to disk when
        innodb_stats_persistent=ON or
        when individual tables are defined with
        STATS_PERSISTENT=1.
        innodb_stats_persistent is
        enabled by default.
      
Formerly, optimizer statistics were cleared when restarting the server and after some other types of operations, and recomputed on the next table access. Consequently, different estimates could be produced when recalculating statistics leading to different choices in query execution plans and variation in query performance.
        Persistent statistics are stored in the
        mysql.innodb_table_stats and
        mysql.innodb_index_stats tables. See
        Section 14.8.11.1.5, “InnoDB Persistent Statistics Tables”.
      
If you prefer not to persist optimizer statistics to disk, see Section 14.8.11.2, “Configuring Non-Persistent Optimizer Statistics Parameters”
          The innodb_stats_auto_recalc
          variable, which is enabled by default, controls whether
          statistics are calculated automatically when a table undergoes
          changes to more than 10% of its rows. You can also configure
          automatic statistics recalculation for individual tables by
          specifying the STATS_AUTO_RECALC clause
          when creating or altering a table.
        
          Because of the asynchronous nature of automatic statistics
          recalculation, which occurs in the background, statistics may
          not be recalculated instantly after running a DML operation
          that affects more than 10% of a table, even when
          innodb_stats_auto_recalc is
          enabled. Statistics recalculation can be delayed by few
          seconds in some cases. If up-to-date statistics are required
          immediately, run ANALYZE TABLE
          to initiate a synchronous (foreground) recalculation of
          statistics.
        
          If innodb_stats_auto_recalc
          is disabled, you can ensure the accuracy of optimizer
          statistics by executing the ANALYZE
          TABLE statement after making substantial changes to
          indexed columns. You might also consider adding
          ANALYZE TABLE to setup scripts
          that you run after loading data, and running
          ANALYZE TABLE on a schedule at
          times of low activity.
        
          When an index is added to an existing table, or when a column
          is added or dropped, index statistics are calculated and added
          to the innodb_index_stats table regardless
          of the value of
          innodb_stats_auto_recalc.
          innodb_stats_persistent,
          innodb_stats_auto_recalc, and
          innodb_stats_persistent_sample_pages
          are global variables. To override these system-wide settings
          and configure optimizer statistics parameters for individual
          tables, you can define STATS_PERSISTENT,
          STATS_AUTO_RECALC, and
          STATS_SAMPLE_PAGES clauses in
          CREATE TABLE or
          ALTER TABLE statements.
STATS_PERSISTENTspecifies whether to enable persistent statistics for anInnoDBtable. The valueDEFAULTcauses the persistent statistics setting for the table to be determined by theinnodb_stats_persistentsetting. A value of1enables persistent statistics for the table, while a value of0disables the feature. After enabling persistent statistics for an individual table, useANALYZE TABLEto calculate statistics after table data is loaded.STATS_AUTO_RECALCspecifies whether to automatically recalculate persistent statistics. The valueDEFAULTcauses the persistent statistics setting for the table to be determined by theinnodb_stats_auto_recalcsetting. A value of1causes statistics to be recalculated when 10% of table data has changed. A value0prevents automatic recalculation for the table. When using a value of 0, useANALYZE TABLEto recalculate statistics after making substantial changes to the table.STATS_SAMPLE_PAGESspecifies the number of index pages to sample when cardinality and other statistics are calculated for an indexed column, by anANALYZE TABLEoperation, for example.
          All three clauses are specified in the following
          CREATE TABLE example:
        
CREATE TABLE `t1` (
`id` int(8) NOT NULL auto_increment,
`data` varchar(255),
`date` datetime,
PRIMARY KEY  (`id`),
INDEX `DATE_IX` (`date`)
) ENGINE=InnoDB,
  STATS_PERSISTENT=1,
  STATS_AUTO_RECALC=1,
  STATS_SAMPLE_PAGES=25;
          The optimizer uses estimated
          statistics about key
          distributions to choose the indexes for an execution plan,
          based on the relative
          selectivity of the
          index. Operations such as ANALYZE
          TABLE cause InnoDB to sample
          random pages from each index on a table to estimate the
          cardinality of the
          index. This sampling technique is known as a
          random dive.
        
          The
          innodb_stats_persistent_sample_pages
          controls the number of sampled pages. You can adjust the
          setting at runtime to manage the quality of statistics
          estimates used by the optimizer. The default value is 20.
          Consider modifying the setting when encountering the following
          issues:
Statistics are not accurate enough and the optimizer chooses suboptimal plans, as shown in
EXPLAINoutput. You can check the accuracy of statistics by comparing the actual cardinality of an index (determined by runningSELECT DISTINCTon the index columns) with the estimates in themysql.innodb_index_statstable.If it is determined that statistics are not accurate enough, the value of
innodb_stats_persistent_sample_pagesshould be increased until the statistics estimates are sufficiently accurate. Increasinginnodb_stats_persistent_sample_pagestoo much, however, could causeANALYZE TABLEto run slowly.ANALYZE TABLEis too slow. In this caseinnodb_stats_persistent_sample_pagesshould be decreased untilANALYZE TABLEexecution time is acceptable. Decreasing the value too much, however, could lead to the first problem of inaccurate statistics and suboptimal query execution plans.If a balance cannot be achieved between accurate statistics and
ANALYZE TABLEexecution time, consider decreasing the number of indexed columns in the table or limiting the number of partitions to reduceANALYZE TABLEcomplexity. The number of columns in the table's primary key is also important to consider, as primary key columns are appended to each nonunique index.For related information, see Section 14.8.11.3, “Estimating ANALYZE TABLE Complexity for InnoDB Tables”.
          By default, InnoDB reads uncommitted data
          when calculating statistics. In the case of an uncommitted
          transaction that deletes rows from a table, delete-marked
          records are excluded when calculating row estimates and index
          statistics, which can lead to non-optimal execution plans for
          other transactions that are operating on the table
          concurrently using a transaction isolation level other than
          READ UNCOMMITTED. To avoid
          this scenario,
          innodb_stats_include_delete_marked
          can be enabled to ensure that delete-marked records are
          included when calculating persistent optimizer statistics.
        
          When
          innodb_stats_include_delete_marked
          is enabled, ANALYZE TABLE
          considers delete-marked records when recalculating statistics.
        
          innodb_stats_include_delete_marked
          is a global setting that affects all InnoDB
          tables, and it is only applicable to persistent optimizer
          statistics.
        
          innodb_stats_include_delete_marked
          was introduced in MySQL 5.7.16.
          The persistent statistics feature relies on the internally
          managed tables in the mysql database, named
          innodb_table_stats and
          innodb_index_stats. These tables are set up
          automatically in all install, upgrade, and build-from-source
          procedures.
Table 14.4 Columns of innodb_table_stats
| Column name | Description | 
|---|---|
database_name | 
              Database name | 
table_name | 
              Table name, partition name, or subpartition name | 
last_update | 
              A timestamp indicating the last time the row was updated | 
n_rows | 
              The number of rows in the table | 
clustered_index_size | 
              The size of the primary index, in pages | 
sum_of_other_index_sizes | 
              The total size of other (non-primary) indexes, in pages | 
Table 14.5 Columns of innodb_index_stats
| Column name | Description | 
|---|---|
database_name | 
              Database name | 
table_name | 
              Table name, partition name, or subpartition name | 
index_name | 
              Index name | 
last_update | 
              A timestamp indicating the last time that InnoDB
                updated this row | 
            
stat_name | 
              The name of the statistic, whose value is reported in the
                stat_value column | 
            
stat_value | 
              The value of the statistic that is named in stat_name
                column | 
            
sample_size | 
              The number of pages sampled for the estimate provided in the
                stat_value column | 
            
stat_description | 
              Description of the statistic that is named in the
                stat_name column | 
          The innodb_table_stats and
          innodb_index_stats tables include a
          last_update column that shows when index
          statistics were last updated:
        
mysql> SELECT * FROM innodb_table_stats \G
*************************** 1. row ***************************
           database_name: sakila
              table_name: actor
             last_update: 2014-05-28 16:16:44
                  n_rows: 200
    clustered_index_size: 1
sum_of_other_index_sizes: 1
...mysql> SELECT * FROM innodb_index_stats \G
*************************** 1. row ***************************
   database_name: sakila
      table_name: actor
      index_name: PRIMARY
     last_update: 2014-05-28 16:16:44
       stat_name: n_diff_pfx01
      stat_value: 200
     sample_size: 1
     ...
          The innodb_table_stats and
          innodb_index_stats tables can be updated
          manually, which makes it possible to force a specific query
          optimization plan or test alternative plans without modifying
          the database. If you manually update statistics, use the
          FLUSH TABLE
           statement to
          load the updated statistics.
        tbl_name
          Persistent statistics are considered local information,
          because they relate to the server instance. The
          innodb_table_stats and
          innodb_index_stats tables are therefore not
          replicated when automatic statistics recalculation takes
          place. If you run ANALYZE TABLE
          to initiate a synchronous recalculation of statistics, this
          statement is replicated (unless you suppressed logging for
          it), and recalculation takes place on the replicas.
          The innodb_table_stats table contains one
          row for each table. The following example demonstrates the
          type of data collected.
        
          Table t1 contains a primary index (columns
          a, b) secondary index
          (columns c, d), and
          unique index (columns e,
          f):
        
CREATE TABLE t1 (
a INT, b INT, c INT, d INT, e INT, f INT,
PRIMARY KEY (a, b), KEY i1 (c, d), UNIQUE KEY i2uniq (e, f)
) ENGINE=INNODB;
          After inserting five rows of sample data, table
          t1 appears as follows:
        
mysql> SELECT * FROM t1;
+---+---+------+------+------+------+
| a | b | c    | d    | e    | f    |
+---+---+------+------+------+------+
| 1 | 1 |   10 |   11 |  100 |  101 |
| 1 | 2 |   10 |   11 |  200 |  102 |
| 1 | 3 |   10 |   11 |  100 |  103 |
| 1 | 4 |   10 |   12 |  200 |  104 |
| 1 | 5 |   10 |   12 |  100 |  105 |
+---+---+------+------+------+------+
          To immediately update statistics, run
          ANALYZE TABLE (if
          innodb_stats_auto_recalc is
          enabled, statistics are updated automatically within a few
          seconds assuming that the 10% threshold for changed table rows
          is reached):
        
mysql> ANALYZE TABLE t1;
+---------+---------+----------+----------+
| Table   | Op      | Msg_type | Msg_text |
+---------+---------+----------+----------+
| test.t1 | analyze | status   | OK       |
+---------+---------+----------+----------+
          Table statistics for table t1 show the last
          time InnoDB updated the table statistics
          (2014-03-14 14:36:34), the number of rows
          in the table (5), the clustered index size
          (1 page), and the combined size of the
          other indexes (2 pages).
        
mysql> SELECT * FROM mysql.innodb_table_stats WHERE table_name like 't1'\G
*************************** 1. row ***************************
           database_name: test
              table_name: t1
             last_update: 2014-03-14 14:36:34
                  n_rows: 5
    clustered_index_size: 1
sum_of_other_index_sizes: 2
          The innodb_index_stats table contains
          multiple rows for each index. Each row in the
          innodb_index_stats table provides data
          related to a particular index statistic which is named in the
          stat_name column and described in the
          stat_description column. For example:
        
mysql> SELECT index_name, stat_name, stat_value, stat_description
       FROM mysql.innodb_index_stats WHERE table_name like 't1';
+------------+--------------+------------+-----------------------------------+
| index_name | stat_name    | stat_value | stat_description                  |
+------------+--------------+------------+-----------------------------------+
| PRIMARY    | n_diff_pfx01 |          1 | a                                 |
| PRIMARY    | n_diff_pfx02 |          5 | a,b                               |
| PRIMARY    | n_leaf_pages |          1 | Number of leaf pages in the index |
| PRIMARY    | size         |          1 | Number of pages in the index      |
| i1         | n_diff_pfx01 |          1 | c                                 |
| i1         | n_diff_pfx02 |          2 | c,d                               |
| i1         | n_diff_pfx03 |          2 | c,d,a                             |
| i1         | n_diff_pfx04 |          5 | c,d,a,b                           |
| i1         | n_leaf_pages |          1 | Number of leaf pages in the index |
| i1         | size         |          1 | Number of pages in the index      |
| i2uniq     | n_diff_pfx01 |          2 | e                                 |
| i2uniq     | n_diff_pfx02 |          5 | e,f                               |
| i2uniq     | n_leaf_pages |          1 | Number of leaf pages in the index |
| i2uniq     | size         |          1 | Number of pages in the index      |
+------------+--------------+------------+-----------------------------------+
          The stat_name column shows the following
          types of statistics:
size: Wherestat_name=size, thestat_valuecolumn displays the total number of pages in the index.n_leaf_pages: Wherestat_name=n_leaf_pages, thestat_valuecolumn displays the number of leaf pages in the index.n_diff_pfx: WhereNNstat_name=n_diff_pfx01, thestat_valuecolumn displays the number of distinct values in the first column of the index. Wherestat_name=n_diff_pfx02, thestat_valuecolumn displays the number of distinct values in the first two columns of the index, and so on. Wherestat_name=n_diff_pfx, theNNstat_descriptioncolumn shows a comma separated list of the index columns that are counted.
          To further illustrate the
          n_diff_pfx
          statistic, which provides cardinality data, consider once
          again the NNt1 table example that was
          introduced previously. As shown below, the
          t1 table is created with a primary index
          (columns a, b), a
          secondary index (columns c,
          d), and a unique index (columns
          e, f):
        
CREATE TABLE t1 (
  a INT, b INT, c INT, d INT, e INT, f INT,
  PRIMARY KEY (a, b), KEY i1 (c, d), UNIQUE KEY i2uniq (e, f)
) ENGINE=INNODB;
          After inserting five rows of sample data, table
          t1 appears as follows:
        
mysql> SELECT * FROM t1;
+---+---+------+------+------+------+
| a | b | c    | d    | e    | f    |
+---+---+------+------+------+------+
| 1 | 1 |   10 |   11 |  100 |  101 |
| 1 | 2 |   10 |   11 |  200 |  102 |
| 1 | 3 |   10 |   11 |  100 |  103 |
| 1 | 4 |   10 |   12 |  200 |  104 |
| 1 | 5 |   10 |   12 |  100 |  105 |
+---+---+------+------+------+------+
          When you query the index_name,
          stat_name, stat_value,
          and stat_description, where
          stat_name LIKE 'n_diff%', the following
          result set is returned:
        
mysql> SELECT index_name, stat_name, stat_value, stat_description
       FROM mysql.innodb_index_stats
       WHERE table_name like 't1' AND stat_name LIKE 'n_diff%';
+------------+--------------+------------+------------------+
| index_name | stat_name    | stat_value | stat_description |
+------------+--------------+------------+------------------+
| PRIMARY    | n_diff_pfx01 |          1 | a                |
| PRIMARY    | n_diff_pfx02 |          5 | a,b              |
| i1         | n_diff_pfx01 |          1 | c                |
| i1         | n_diff_pfx02 |          2 | c,d              |
| i1         | n_diff_pfx03 |          2 | c,d,a            |
| i1         | n_diff_pfx04 |          5 | c,d,a,b          |
| i2uniq     | n_diff_pfx01 |          2 | e                |
| i2uniq     | n_diff_pfx02 |          5 | e,f              |
+------------+--------------+------------+------------------+
          For the PRIMARY index, there are two
          n_diff% rows. The number of rows is equal
          to the number of columns in the index.
            For nonunique indexes, InnoDB appends the
            columns of the primary key.
Where
index_name=PRIMARYandstat_name=n_diff_pfx01, thestat_valueis1, which indicates that there is a single distinct value in the first column of the index (columna). The number of distinct values in columnais confirmed by viewing the data in columnain tablet1, in which there is a single distinct value (1). The counted column (a) is shown in thestat_descriptioncolumn of the result set.Where
index_name=PRIMARYandstat_name=n_diff_pfx02, thestat_valueis5, which indicates that there are five distinct values in the two columns of the index (a,b). The number of distinct values in columnsaandbis confirmed by viewing the data in columnsaandbin tablet1, in which there are five distinct values: (1,1), (1,2), (1,3), (1,4) and (1,5). The counted columns (a,b) are shown in thestat_descriptioncolumn of the result set.
          For the secondary index (i1), there are
          four n_diff% rows. Only two columns are
          defined for the secondary index (c,d) but
          there are four n_diff% rows for the
          secondary index because InnoDB suffixes all
          nonunique indexes with the primary key. As a result, there are
          four n_diff% rows instead of two to account
          for the both the secondary index columns
          (c,d) and the primary key columns
          (a,b).
Where
index_name=i1andstat_name=n_diff_pfx01, thestat_valueis1, which indicates that there is a single distinct value in the first column of the index (columnc). The number of distinct values in columncis confirmed by viewing the data in columncin tablet1, in which there is a single distinct value: (10). The counted column (c) is shown in thestat_descriptioncolumn of the result set.Where
index_name=i1andstat_name=n_diff_pfx02, thestat_valueis2, which indicates that there are two distinct values in the first two columns of the index (c,d). The number of distinct values in columnscandis confirmed by viewing the data in columnscanddin tablet1, in which there are two distinct values: (10,11) and (10,12). The counted columns (c,d) are shown in thestat_descriptioncolumn of the result set.Where
index_name=i1andstat_name=n_diff_pfx03, thestat_valueis2, which indicates that there are two distinct values in the first three columns of the index (c,d,a). The number of distinct values in columnsc,d, andais confirmed by viewing the data in columnc,d, andain tablet1, in which there are two distinct values: (10,11,1) and (10,12,1). The counted columns (c,d,a) are shown in thestat_descriptioncolumn of the result set.Where
index_name=i1andstat_name=n_diff_pfx04, thestat_valueis5, which indicates that there are five distinct values in the four columns of the index (c,d,a,b). The number of distinct values in columnsc,d,aandbis confirmed by viewing the data in columnsc,d,a, andbin tablet1, in which there are five distinct values: (10,11,1,1), (10,11,1,2), (10,11,1,3), (10,12,1,4), and (10,12,1,5). The counted columns (c,d,a,b) are shown in thestat_descriptioncolumn of the result set.
          For the unique index (i2uniq), there are
          two n_diff% rows.
Where
index_name=i2uniqandstat_name=n_diff_pfx01, thestat_valueis2, which indicates that there are two distinct values in the first column of the index (columne). The number of distinct values in columneis confirmed by viewing the data in columnein tablet1, in which there are two distinct values: (100) and (200). The counted column (e) is shown in thestat_descriptioncolumn of the result set.Where
index_name=i2uniqandstat_name=n_diff_pfx02, thestat_valueis5, which indicates that there are five distinct values in the two columns of the index (e,f). The number of distinct values in columnseandfis confirmed by viewing the data in columnseandfin tablet1, in which there are five distinct values: (100,101), (200,102), (100,103), (200,104), and (100,105). The counted columns (e,f) are shown in thestat_descriptioncolumn of the result set.
          You can retrieve the index size for tables, partitions, or
          subpartitions can using the
          innodb_index_stats table. In the following
          example, index sizes are retrieved for table
          t1. For a definition of table
          t1 and corresponding index statistics, see
          Section 14.8.11.1.6, “InnoDB Persistent Statistics Tables Example”.
        
mysql> SELECT SUM(stat_value) pages, index_name,
       SUM(stat_value)*@@innodb_page_size size
       FROM mysql.innodb_index_stats WHERE table_name='t1'
       AND stat_name = 'size' GROUP BY index_name;
+-------+------------+-------+
| pages | index_name | size  |
+-------+------------+-------+
|     1 | PRIMARY    | 16384 |
|     1 | i1         | 16384 |
|     1 | i2uniq     | 16384 |
+-------+------------+-------+
          For partitions or subpartitions, you can use the same query
          with a modified WHERE clause to retrieve
          index sizes. For example, the following query retrieves index
          sizes for partitions of table t1:
        
mysql> SELECT SUM(stat_value) pages, index_name,
       SUM(stat_value)*@@innodb_page_size size
       FROM mysql.innodb_index_stats WHERE table_name like 't1#P%'
       AND stat_name = 'size' GROUP BY index_name;