为了演示，首先建两个包含不良索引的表，并弄点数据。
mysql> show create table test1\G*************************** 1. row *************************** Table: test1Create Table: CREATE TABLE `test1` ( `id` int(11) NOT NULL, `f1` int(11) DEFAULT NULL, `f2` int(11) DEFAULT NULL, `f3` int(11) DEFAULT NULL, PRIMARY KEY (`id`), KEY `k1` (`f1`,`id`), KEY `k2` (`id`,`f1`), KEY `k3` (`f1`), KEY `k4` (`f1`,`f3`), KEY `k5` (`f1`,`f3`,`f2`)) ENGINE=InnoDB DEFAULT CHARSET=latin11 row in set (0.00 sec)mysql> show create table test2\G*************************** 1. row *************************** Table: test2Create Table: CREATE TABLE `test2` ( `id1` int(11) NOT NULL DEFAULT '0', `id2` int(11) NOT NULL DEFAULT '0', `b` int(11) DEFAULT NULL, PRIMARY KEY (`id1`,`id2`), KEY `k1` (`b`)) ENGINE=InnoDB DEFAULT CHARSET=latin11 row in set (0.00 sec)mysql> select count(*) from test2 group by b; +----------+| count(*) |+----------+| 32 || 17 |+----------+2 rows in set (0.00 sec)
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1. 包含主键的索引
innodb 本身是聚簇表，每个二级索引本身就包含主键，类似 f1, id 的索引实际虽然没有害处，但反映了使用者对 mysql 索引不了解。而类似 id, f1 的是多余索引，会浪费存储空间，并影响数据更新性能。包含主键的索引用这样一句 sql 就能全部找出来。
mysql> select c.*, pk from -> (select table_schema, table_name, index_name, concat('|', group_concat(column_name order by seq_in_index separator '|'), '|') cols -> from INFORMATION_SCHEMA.STATISTICS -> where index_name != 'PRIMARY' and table_schema != 'mysql' -> group by table_schema, table_name, index_name) c, -> (select table_schema, table_name, concat('|', group_concat(column_name order by seq_in_index separator '|'), '|') pk -> from INFORMATION_SCHEMA.STATISTICS -> where index_name = 'PRIMARY' and table_schema != 'mysql' -> group by table_schema, table_name) p -> where c.table_name = p.table_name and c.table_schema = p.table_schema and c.cols like concat('%', pk, '%');+--------------+------------+------------+---------+------+| table_schema | table_name | index_name | cols | pk |+--------------+------------+------------+---------+------+| test | test1 | k1 | |f1|id| | |id| || test | test1 | k2 | |id|f1| | |id| |+--------------+------------+------------+---------+------+2 rows in set (0.04 sec)
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2. 重复索引前缀
包含重复前缀的索引，索引能由另一个包含该前缀的索引完全代替，是多余索引。多余的索引会浪费存储空间，并影响数据更新性能。这样的索引同样用一句 sql 可以找出来。
mysql> select c1.table_schema, c1.table_name, c1.index_name,c1.cols,c2.index_name, c2.cols from -> (select table_schema, table_name, index_name, concat('|', group_concat(column_name order by seq_in_index separator '|'), '|') cols -> from INFORMATION_SCHEMA.STATISTICS -> where table_schema != 'mysql' and index_name!='PRIMARY' -> group by table_schema,table_name,index_name) c1, -> (select table_schema, table_name,index_name, concat('|', group_concat(column_name order by seq_in_index separator '|'), '|') cols -> from INFORMATION_SCHEMA.STATISTICS -> where table_schema != 'mysql' and index_name != 'PRIMARY' -> group by table_schema, table_name, index_name) c2 -> where c1.table_name = c2.table_name and c1.table_schema = c2.table_schema and c1.cols like concat(c2.cols, '%') and c1.index_name != c2.index_name;+--------------+------------+------------+------------+------------+---------+| table_schema | table_name | index_name | cols | index_name | cols |+--------------+------------+------------+------------+------------+---------+| test | test1 | k1 | |f1|id| | k3 | |f1| || test | test1 | k4 | |f1|f3| | k3 | |f1| || test | test1 | k5 | |f1|f3|f2| | k3 | |f1| || test | test1 | k5 | |f1|f3|f2| | k4 | |f1|f3| |+--------------+------------+------------+------------+------------+---------+4 rows in set (0.02 sec)
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3. 低区分度索引
这样的索引由于仍然会扫描大量记录，在实际查询时通常会被忽略。但是在某些情况下仍然是有用的。因此需要根据实际情况进一步分析。这里是区分度小于 10% 的索引，可以根据需要调整参数。
mysql> select p.table_schema, p.table_name, c.index_name, c.car, p.car total from -> (select table_schema, table_name, index_name, max(cardinality) car -> from INFORMATION_SCHEMA.STATISTICS -> where index_name != 'PRIMARY' -> group by table_schema, table_name,index_name) c, -> (select table_schema, table_name, max(cardinality) car -> from INFORMATION_SCHEMA.STATISTICS -> where index_name = 'PRIMARY' and table_schema != 'mysql' -> group by table_schema,table_name) p -> where c.table_name = p.table_name and c.table_schema = p.table_schema and p.car > 0 and c.car / p.car < 0.1;+--------------+------------+------------+------+-------+| table_schema | table_name | index_name | car | total |+--------------+------------+------------+------+-------+| test | test2 | k1 | 4 | 49 |+--------------+------------+------------+------+-------+1 row in set (0.04 sec)
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4. 复合主键
由于 innodb 是聚簇表，每个二级索引都会包含主键值。复合主键会造成二级索引庞大，而影响二级索引查询性能，并影响更新性能。同样需要根据实际情况进一步分析。
mysql> select table_schema, table_name, group_concat(column_name order by seq_in_index separator ',') cols, max(seq_in_index) len -> from INFORMATION_SCHEMA.STATISTICS -> where index_name = 'PRIMARY' and table_schema != 'mysql' -> group by table_schema, table_name having len>1;+--------------+------------+-----------------------------------+------+| table_schema | table_name | cols | len |+--------------+------------+-----------------------------------+------+| test | test2 | id1,id2 | 2 |+--------------+------------+-----------------------------------+------+1 rows in set (0.01 sec)
本文来自云栖社区合作伙伴“Linux中国”，原文发布日期：2015-08-18
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