MySQL 8.0统计信息不准确的原因

前言

不管是Oracle还是mysql/' target='_blank'>mysql，新版本推出的新特性，一方面给产品带来功能、性能、用户体验等方面的提升，另一方面也可能会带来一些问题，如代码bug、客户使用方法不正确引发问题等等。

案例分享

MySQL 5.7下的场景

（1）首先，创建两张表，并插入数据

mysql> select version();+------------+| version() |+------------+| 5.7.30-log |+------------+1 row in set (0.00 sec)mysql> show create table test\G*************************** 1. row ***************************    Table: testCreate Table: CREATE TABLE `test` ( `id` int(10) unsigned NOT NULL AUTO_INCREMENT, `k` int(10) unsigned NOT NULL DEFAULT '0', `c` char(120) NOT NULL DEFAULT '', `pad` char(60) NOT NULL DEFAULT '', PRIMARY KEY (`id`), KEY `k_1` (`k`)) ENGINE=InnoDB AUTO_INCREMENT=101 DEFAULT CHARSET=utf8mb4 MAX_ROWS=10000001 row in set (0.00 sec)mysql> show create table sbtest1\G*************************** 1. row ***************************    Table: sbtest1Create Table: CREATE TABLE `sbtest1` ( `id` int(10) unsigned NOT NULL AUTO_INCREMENT, `k` int(10) unsigned NOT NULL DEFAULT '0', `c` char(120) NOT NULL DEFAULT '', `pad` char(60) NOT NULL DEFAULT '', PRIMARY KEY (`id`), KEY `k_1` (`k`)) ENGINE=InnoDB AUTO_INCREMENT=1000001 DEFAULT CHARSET=utf8mb4 MAX_ROWS=10000001 row in set (0.00 sec)mysql> select count(*) from test;+----------+| count(*) |+----------+|   100 |+----------+1 row in set (0.00 sec)mysql> select count(*) from sbtest1;+----------+| count(*) |+----------+| 1000000 |+----------+1 row in set (0.14 sec)

（2）查看两张表的统计信息，均比较准确

mysql> select table_schema,table_name,table_rows from tables where table_name='test';+--------------+------------+------------+| table_schema | table_name | table_rows |+--------------+------------+------------+| test     | test    |    100 |+--------------+------------+------------+1 row in set (0.00 sec)mysql> select table_schema,table_name,table_rows from tables where table_name='sbtest1';+--------------+------------+------------+| table_schema | table_name | table_rows |+--------------+------------+------------+| test     | sbtest1  |   947263 |+--------------+------------+------------+1 row in set (0.00 sec)

（3）我们持续往test表插入1000w条记录，并再次查看统计信息，还是相对准确的，因为在默认情况下，数据变化量超过10%，就会触发统计信息更新

mysql> select count(*) from test;+----------+| count(*) |+----------+| 10000100 |+----------+1 row in set (1.50 sec)mysql> select table_schema,table_name,table_rows from tables where table_name='test';+--------------+------------+------------+| table_schema | table_name | table_rows |+--------------+------------+------------+| test     | test    |  9749036 |+--------------+------------+------------+1 row in set (0.00 sec)

MySQL 8.0下的场景

（1）接下来我们看看8.0下的情况吧，同样地，我们创建两张表，并插入相同记录

mysql> select version();+-----------+| version() |+-----------+| 8.0.20  |+-----------+1 row in set (0.00 sec)mysql> show create table test\G*************************** 1. row ***************************    Table: testCreate Table: CREATE TABLE `test` ( `id` int unsigned NOT NULL AUTO_INCREMENT, `k` int unsigned NOT NULL DEFAULT '0', `c` char(120) NOT NULL DEFAULT '', `pad` char(60) NOT NULL DEFAULT '', PRIMARY KEY (`id`), KEY `k_1` (`k`)) ENGINE=InnoDB AUTO_INCREMENT=101 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci MAX_ROWS=10000001 row in set (0.00 sec)mysql> show create table sbtest1\G*************************** 1. row ***************************    Table: sbtest1Create Table: CREATE TABLE `sbtest1` ( `id` int unsigned NOT NULL AUTO_INCREMENT, `k` int unsigned NOT NULL DEFAULT '0', `c` char(120) NOT NULL DEFAULT '', `pad` char(60) NOT NULL DEFAULT '', PRIMARY KEY (`id`), KEY `k_1` (`k`)) ENGINE=InnoDB AUTO_INCREMENT=1000001 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci MAX_ROWS=10000001 row in set (0.00 sec)mysql> select count(*) from test;+----------+| count(*) |+----------+|   100 |+----------+1 row in set (0.00 sec)mysql> select count(*) from sbtest1;+----------+| count(*) |+----------+| 1000000 |+----------+1 row in set (0.02 sec)

（2）查看两张表的统计信息，均比较准确

mysql> select table_schema,table_name,table_rows from tables where table_name='test';+--------------+------------+------------+| TABLE_SCHEMA | TABLE_NAME | TABLE_ROWS |+--------------+------------+------------+| test     | test    |    100 |+--------------+------------+------------+1 row in set (0.00 sec)mysql> select table_schema,table_name,table_rows from tables where table_name='sbtest1';+--------------+------------+------------+| TABLE_SCHEMA | TABLE_NAME | TABLE_ROWS |+--------------+------------+------------+| test     | sbtest1  |   947468 |+--------------+------------+------------+1 row in set (0.01 sec)

（3）同样地，我们持续往test表插入1000w条记录，并再次查看统计信息，发现table_rows显示还是100条，出现了较大偏差

mysql> select count(*) from test;+----------+| count(*) |+----------+| 10000100 |+----------+1 row in set (0.33 sec)mysql> select table_schema,table_name,table_rows from tables where table_name='test';+--------------+------------+------------+| TABLE_SCHEMA | TABLE_NAME | TABLE_ROWS |+--------------+------------+------------+| test     | test    |    100 |+--------------+------------+------------+1 row in set (0.00 sec)

原因剖析

那么导致统计信息不准确的原因是什么呢？其实是MySQL 8.0为了提高information_schema的查询效率，将视图tables和statistics里面的统计信息缓存起来，缓存过期时间由参数information_schema_stats_expiry决定，默认为86400s；如果想获取最新的统计信息，可以通过如下两种方式：

（1）analyze table进行表分析

（2）设置information_schema_stats_expiry=0

继续探索

那么统计信息不准确，会带来哪些影响呢？是否会影响执行计划呢？接下来我们再次进行测试

测试1：表test记录数100，表sbtest1记录数100w

执行如下SQL，查看执行计划，走的是NLJ，小表test作为驱动表(全表扫描)，大表sbtest1作为被驱动表(主键关联)，执行效率很快

mysql> select count(*) from test;+----------+| count(*) |+----------+|   100 |+----------+1 row in set (0.00 sec)mysql> select count(*) from sbtest1;+----------+| count(*) |+----------+| 1000000 |+----------+1 row in set (0.02 sec)mysql> select table_schema,table_name,table_rows from tables where table_name='test';+--------------+------------+------------+| TABLE_SCHEMA | TABLE_NAME | TABLE_ROWS |+--------------+------------+------------+| test     | test    |    100 |+--------------+------------+------------+1 row in set (0.00 sec)mysql> select table_schema,table_name,table_rows from tables where table_name='sbtest1';+--------------+------------+------------+| TABLE_SCHEMA | TABLE_NAME | TABLE_ROWS |+--------------+------------+------------+| test     | sbtest1  |   947468 |+--------------+------------+------------+1 row in set (0.01 sec)mysql> select t.* from test t inner join sbtest1 t1 on t.id=t1.id where t.c='08566691963-88624912351-16662227201-46648573979-64646226163-77505759394-75470094713-41097360717-15161106334-50535565977' and t1.c='08566691963-88624912351-16662227201-46648573979-64646226163-77505759394-75470094713-41097360717-15161106334-50535565977';+----+--------+-------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------+| id | k   | c                                                            | pad                             |+----+--------+-------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------+| 1 | 501885 | 08566691963-88624912351-16662227201-46648573979-64646226163-77505759394-75470094713-41097360717-15161106334-50535565977 | 63188288836-92351140030-06390587585-66802097351-49282961843 |+----+--------+-------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------+1 row in set (0.00 sec)mysql> explain select t.* from test t inner join sbtest1 t1 on t.id=t1.id where t.c='08566691963-88624912351-16662227201-46648573979-64646226163-77505759394-75470094713-41097360717-15161106334-50535565977' and t1.c='08566691963-88624912351-16662227201-4664+----+-------------+-------+------------+--------+---------------+---------+---------+-----------+------+----------+-------------+| id | select_type | table | partitions | type  | possible_keys | key   | key_len | ref    | rows | filtered | Extra    |+----+-------------+-------+------------+--------+---------------+---------+---------+-----------+------+----------+-------------+| 1 | SIMPLE   | t   | NULL    | ALL  | PRIMARY    | NULL  | NULL  | NULL   | 100 |  10.00 | Using where || 1 | SIMPLE   | t1  | NULL    | eq_ref | PRIMARY    | PRIMARY | 4    | test.t.id |  1 |  10.00 | Using where |+----+-------------+-------+------------+--------+---------------+---------+---------+-----------+------+----------+-------------+2 rows in set, 1 warning (0.00 sec)

测试2：表test记录数1000w左右，表sbtest1记录数100w

再次执行SQL，查看执行计划，走的也是NLJ，相对小表sbtest1作为驱动表，大表test作为被驱动表，也是正确的执行计划

mysql> select count(*) from test;+----------+| count(*) |+----------+| 10000100 |+----------+1 row in set (0.33 sec)mysql> select count(*) from sbtest1;+----------+| count(*) |+----------+| 1000000 |+----------+1 row in set (0.02 sec)mysql> select table_schema,table_name,table_rows from tables where table_name='test';+--------------+------------+------------+| TABLE_SCHEMA | TABLE_NAME | TABLE_ROWS |+--------------+------------+------------+| test     | test    |    100 |+--------------+------------+------------+1 row in set (0.00 sec)mysql> select table_schema,table_name,table_rows from tables where table_name='sbtest1';+--------------+------------+------------+| TABLE_SCHEMA | TABLE_NAME | TABLE_ROWS |+--------------+------------+------------+| test     | sbtest1  |   947468 |+--------------+------------+------------+1 row in set (0.01 sec)mysql> select t.* from test t inner join sbtest1 t1 on t.id=t1.id where t.c='08566691963-88624912351-16662227201-46648573979-64646226163-77505759394-75470094713-41097360717-15161106334-50535565977' and t1.c='08566691963-88624912351-16662227201-46648573979-64646226163-77505759394-75470094713-41097360717-15161106334-50535565977';+----+--------+-------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------+| id | k   | c                                                            | pad                             |+----+--------+-------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------+| 1 | 501885 | 08566691963-88624912351-16662227201-46648573979-64646226163-77505759394-75470094713-41097360717-15161106334-50535565977 | 63188288836-92351140030-06390587585-66802097351-49282961843 |+----+--------+-------------------------------------------------------------------------------------------------------------------------+-------------------------------------------------------------+1 row in set (0.37 sec)mysql> explain select t.* from test t inner join sbtest1 t1 on t.id=t1.id where t.c='08566691963-88624912351-16662227201-46648573979-64646226163-77505759394-75470094713-41097360717-15161106334-50535565977' and t1.c='08566691963-88624912351-16662227201-46648573979-64646226163-77505759394-75470094713-41097360717-15161106334-50535565977';+----+-------------+-------+------------+--------+---------------+---------+---------+------------+--------+----------+-------------+| id | select_type | table | partitions | type  | possible_keys | key   | key_len | ref    | rows  | filtered | Extra    |+----+-------------+-------+------------+--------+---------------+---------+---------+------------+--------+----------+-------------+| 1 | SIMPLE   | t1  | NULL    | ALL  | PRIMARY    | NULL  | NULL  | NULL    | 947468 |  10.00 | Using where || 1 | SIMPLE   | t   | NULL    | eq_ref | PRIMARY    | PRIMARY | 4    | test.t1.id |   1 |  10.00 | Using where |+----+-------------+-------+------------+--------+---------------+---------+---------+------------+--------+----------+-------------+2 rows in set, 1 warning (0.01 sec)

为什么优化器没有选择错误的执行计划呢？之前文章也提过，MySQL 8.0是将元数据信息存放在mysql库下的数据字典表里，information_schema库只是提供相对方便的视图供用户查询，所以优化器在选择执行计划时，会从数据字典表中获取统计信息，生成正确的执行计划。

总结

MySQL 8.0为了提高information_schema的查询效率，会将视图tables和statistics里面的统计信息缓存起来，缓存过期时间由参数information_schema_stats_expiry决定(建议设置该参数值为0)；这可能会导致用户查询相应视图时，无法获取最新、准确的统计信息，但并不会影响执行计划的选择。

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