檢測mysql 數據庫中的不良索引的方法

索引的作用我不說多肯定是提升數據庫的查詢能力了，但是索引用到不好會導致查詢變慢了，下面我們來給各位介紹找到 mysql 數據庫中的不良索引的方法。

為了演示，首先建兩個包含不良索引的表，並弄點數據。

mysql> show create table test1\G
*************************** 1. row ***************************
       Table: test1
Create 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=latin1
1 row in set (0.00 sec)

mysql> show create table test2\G
*************************** 1. row ***************************
       Table: test2
Create 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=latin1
1 row in set (0.00 sec)

mysql> select count(*) from test2 group by b;                                                                                                       
+----------+
| count(*) |
+----------+
|       32 |
|       17 |
+----------+
2 rows in set (0.00 sec)

1. 包含主鍵的索引
innodb 本身是聚簇表，每個二級索引本身就包含主鍵，類似 f1, id 的索引實際雖然沒有害處，但反映了使用者對 mysql 索引不了解。而類似 id, f1 的是多余索引，會浪費存儲空間，並影響數據更新性能。包含主鍵的索引用這樣一句 sql 就能全部找出來。

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)

2. 重復索引前綴
包含重復前綴的索引，索引能由另一個包含該前綴的索引完全代替，是多余索引。多余的索引會浪費存儲空間，並影響數據更新性能。這樣的索引同樣用一句 sql 可以找出來。

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)

3. 低區分度索引
這樣的索引由於仍然會掃描大量記錄，在實際查詢時通常會被忽略。但是在某些情況下仍然是有用的。因此需要根據實際情況進一步分析。這裡是區分度小於 10% 的索引，可以根據需要調整參數。

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)

4. 復合主鍵
由於 innodb 是聚簇表，每個二級索引都會包含主鍵值。復合主鍵會造成二級索引龐大，而影響二級索引查詢性能，並影響更新性能。同樣需要根據實際情況進一步分析。

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)