为了演示，首先建两个包含不良索引的表，并弄点数据。

1. mysql> show create table test1\G
2. *************************** 1. row ***************************
3. Table: test1
4. Create Table: CREATE TABLE `test1` (
5. `id` int(11) NOT NULL,
6. `f1` int(11) DEFAULT NULL,
7. `f2` int(11) DEFAULT NULL,
8. `f3` int(11) DEFAULT NULL,
9. PRIMARY KEY (`id`),
10. KEY `k1` (`f1`,`id`),
11. KEY `k2` (`id`,`f1`),
12. KEY `k3` (`f1`),
13. KEY `k4` (`f1`,`f3`),
14. KEY `k5` (`f1`,`f3`,`f2`)
15. ) ENGINE=InnoDB DEFAULT CHARSET=latin1
16. 1 row in set (0.00 sec)
17. mysql> show create table test2\G
18. *************************** 1. row ***************************
19. Table: test2
20. Create Table: CREATE TABLE `test2` (
21. `id1` int(11) NOT NULL DEFAULT '0',
22. `id2` int(11) NOT NULL DEFAULT '0',
23. `b` int(11) DEFAULT NULL,
24. PRIMARY KEY (`id1`,`id2`),
25. KEY `k1` (`b`)
26. ) ENGINE=InnoDB DEFAULT CHARSET=latin1
27. 1 row in set (0.00 sec)
28. mysql> select count(*) from test2 group by b;
29. +----------+
30. | count(*) |
31. +----------+
32. | 32 |
33. | 17 |
34. +----------+
35. 2 rows in set (0.00 sec)

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。

1. mysql> select c.*, pk from
2. -> (select table_schema, table_name, index_name, concat('|', group_concat(column_name order by seq_in_index separator '|'), '|') cols
3. -> from INFORMATION_SCHEMA.STATISTICS
4. -> where index_name != 'PRIMARY' and table_schema != 'mysql'
5. -> group by table_schema, table_name, index_name) c,
6. -> (select table_schema, table_name, concat('|', group_concat(column_name order by seq_in_index separator '|'), '|') pk
7. -> from INFORMATION_SCHEMA.STATISTICS
8. -> where index_name = 'PRIMARY' and table_schema != 'mysql'
9. -> group by table_schema, table_name) p
10. -> where c.table_name = p.table_name and c.table_schema = p.table_schema and c.cols like concat('%', pk, '%');
11. +--------------+------------+------------+---------+------+
12. | table_schema | table_name | index_name | cols | pk |
13. +--------------+------------+------------+---------+------+
14. | test | test1 | k1 | |f1|id| | |id| |
15. | test | test1 | k2 | |id|f1| | |id| |
16. +--------------+------------+------------+---------+------+
17. 2 rows in set (0.04 sec)

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。

1. mysql> select c1.table_schema, c1.table_name, c1.index_name,c1.cols,c2.index_name, c2.cols from
2. -> (select table_schema, table_name, index_name, concat('|', group_concat(column_name order by seq_in_index separator '|'), '|') cols
3. -> from INFORMATION_SCHEMA.STATISTICS
4. -> where table_schema != 'mysql' and index_name!='PRIMARY'
5. -> group by table_schema,table_name,index_name) c1,
6. -> (select table_schema, table_name,index_name, concat('|', group_concat(column_name order by seq_in_index separator '|'), '|') cols
7. -> from INFORMATION_SCHEMA.STATISTICS
8. -> where table_schema != 'mysql' and index_name != 'PRIMARY'
9. -> group by table_schema, table_name, index_name) c2
10. -> 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;
11. +--------------+------------+------------+------------+------------+---------+
12. | table_schema | table_name | index_name | cols | index_name | cols |
13. +--------------+------------+------------+------------+------------+---------+
14. | test | test1 | k1 | |f1|id| | k3 | |f1| |
15. | test | test1 | k4 | |f1|f3| | k3 | |f1| |
16. | test | test1 | k5 | |f1|f3|f2| | k3 | |f1| |
17. | test | test1 | k5 | |f1|f3|f2| | k4 | |f1|f3| |
18. +--------------+------------+------------+------------+------------+---------+
19. 4 rows in set (0.02 sec)

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。

1. mysql> select p.table_schema, p.table_name, c.index_name, c.car, p.car total from
2. -> (select table_schema, table_name, index_name, max(cardinality) car
3. -> from INFORMATION_SCHEMA.STATISTICS
4. -> where index_name != 'PRIMARY'
5. -> group by table_schema, table_name,index_name) c,
6. -> (select table_schema, table_name, max(cardinality) car
7. -> from INFORMATION_SCHEMA.STATISTICS
8. -> where index_name = 'PRIMARY' and table_schema != 'mysql'
9. -> group by table_schema,table_name) p
10. -> 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;
11. +--------------+------------+------------+------+-------+
12. | table_schema | table_name | index_name | car | total |
13. +--------------+------------+------------+------+-------+
14. | test | test2 | k1 | 4 | 49 |
15. +--------------+------------+------------+------+-------+
16. 1 row in set (0.04 sec)

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。

1. mysql> select table_schema, table_name, group_concat(column_name order by seq_in_index separator ',') cols, max(seq_in_index) len
2. -> from INFORMATION_SCHEMA.STATISTICS
3. -> where index_name = 'PRIMARY' and table_schema != 'mysql'
4. -> group by table_schema, table_name having len>1;
5. +--------------+------------+-----------------------------------+------+
6. | table_schema | table_name | cols | len |
7. +--------------+------------+-----------------------------------+------+
8. | test | test2 | id1,id2 | 2 |
9. +--------------+------------+-----------------------------------+------+
10. 1 rows in set (0.01 sec)

11. 本文来自云栖社区合作伙伴“Linux中国”，原文发布日期：2015-08-18