MySQL 索引优化的指导性建议

MySQL 提供 MyISAM 、 InnoDB 、 memory(heap) 等多种存储引擎。每种存储引擎对于索引的支持以及实现都不尽相同,
本文主要讨论 InnoDB 引擎相关的索引应用。

为何使用索引

索引用于快速找出在某个列中有一特定值的行。在查询时如果没有应用索引,MySQL 将不得不扫描表以找出符合条件的数据项,我们知道,IO操作是非常耗时的。

建立索引的几个原则

  • 尽量使用唯一索引,对于有唯一值的列索引效果最好,对于像性别只有很少的值的列索引效果就不明显。

  • 索引长度尽量短,这样做有几个好处,首先短的索引可以节省索引空间,也会使查找的速度得到提升。对于较短的键值,索引高速缓存中的块能容纳更多的键值,MySQL也可以在内存中容纳更多的值。

  • 太长的列,可以选择只建立部分索引

  • 更新非常频繁的数据不适宜建索引

  • 利用最左前缀原则,比如建立了一个联合索引(a,b,c),那么其实我们可利用的索引就有(a), (a,b), (a,b,c)

  • 不要过多创建索引,首先过多的索引会占用更多的空间,而且每次增、删、改操作都会重建索引,而且过多索引也会增加之后的优化复杂度

  • 尽量扩展索引,比如现有索引(a),现在我又要对(a,b)进行索引,不需要再建一个索引(a,b)

  • 请注意,一次查询是不能应用多个索引的

  • <,<=,=,>,>=,BETWEEN,IN 可用到索引,<>,not in ,!= 则不行

  • like “xxxx%” 是可以用到索引的,like “%xxxx” 则不行(like “%xxx%” 同理)

  • NULL会使索引的效果大打折扣

浅谈联合索引

首先因为 InnoDB 的数据文件本身要按主键聚集,所以InnoDB要求表必须有主键(MyISAM可以没有),如果没有显式指定,则MySQL系统会自动选择一个可以唯一标识数据记录的列作为主键,如果不存在这种列,则MySQL自动为InnoDB表生成一个隐含字段作为主键。主键对于 InnoDB 的索引结构是十分重要的。

InnoDB 引擎的索引是使用 B+树 实现索引结构的,当我们建立一个联合索引(a, b, c)时,B+树将按照从左至右来建立搜索树,然后检索时B+树将先比较 a 然后再其基础上比较 b 和 c 。不难看出如果我们的搜索条件中只有 a 和 c ,将不能使用完整的(a, b, c)索引,如果我们的搜索条件中没有 a 那么这条查询将不会用上索引,这其实就是最左前缀特性。

** 接下来我们来看下联合索引应用时的几种情况: **

desc users;

+-------+-------------+------+-----+---------+----------------+
| Field | Type        | Null | Key | Default | Extra          |
+-------+-------------+------+-----+---------+----------------+
| id    | int(11)     | NO   | PRI | NULL    | auto_increment |
| rname | varchar(50) | NO   |     | NULL    |                |
| rdesc | varchar(50) | NO   |     | NULL    |                |
| age   | int(11)     | NO   | MUL | NULL    |                |
| card  | int(5)      | YES  |     | NULL    |                |
+-------+-------------+------+-----+---------+----------------+

show index from users;

+-------+------------+---------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name      | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+-------+------------+---------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| users |          0 | PRIMARY       |            1 | id          | A         |          15 |     NULL | NULL   |      | BTREE      |         |               |
| users |          1 | age_name_desc |            1 | age         | A         |          15 |     NULL | NULL   |      | BTREE      |         |               |
| users |          1 | age_name_desc |            2 | rname       | A         |          15 |       10 | NULL   |      | BTREE      |         |               |
| users |          1 | age_name_desc |            3 | rdesc       | A         |          15 |       15 | NULL   |      | BTREE      |         |               |
+-------+------------+---------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
  • 全列匹配
explain select * from users where age = 11 and rname = "asd" and rdesc = "asd";

+----+-------------+-------+------+---------------+---------------+---------+-------------------+------+-------------+
| id | select_type | table | type | possible_keys | key           | key_len | ref               | rows | Extra       |
+----+-------------+-------+------+---------------+---------------+---------+-------------------+------+-------------+
|  1 | SIMPLE      | users | ref  | age_name_desc | age_name_desc | 83      | const,const,const |    1 | Using where |
+----+-------------+-------+------+---------------+---------------+---------+-------------------+------+-------------+

以上 explain 的结果可以看出,当对索引中所有列进行精确匹配的时候,可以用到完整索引。

explain select * from users where  rname = "asd" and age = 11 and rdesc = "asd";

+----+-------------+-------+------+---------------+---------------+---------+-------------------+------+-------------+
| id | select_type | table | type | possible_keys | key           | key_len | ref               | rows | Extra       |
+----+-------------+-------+------+---------------+---------------+---------+-------------------+------+-------------+
|  1 | SIMPLE      | users | ref  | age_name_desc | age_name_desc | 83      | const,const,const |    1 | Using where |
+----+-------------+-------+------+---------------+---------------+---------+-------------------+------+-------------+

按照B+树的结构联合索引本是对顺序十分敏感的,但是从以上结果可看出调整顺序并没有影响到索引的选用,这是因为MySQL的查询优化器会自动调整where子句的条件顺序以使用适合的索引。

  • 部分匹配(左前缀)
explain select * from users where age = 11;

+----+-------------+-------+------+---------------+---------------+---------+-------+------+-------+
| id | select_type | table | type | possible_keys | key           | key_len | ref   | rows | Extra |
+----+-------------+-------+------+---------------+---------------+---------+-------+------+-------+
|  1 | SIMPLE      | users | ref  | age_name_desc | age_name_desc | 4       | const |    1 | NULL  |
+----+-------------+-------+------+---------------+---------------+---------+-------+------+-------+

从上述结果可看出当精确匹配最左前缀的列时,是可以用到索引的,但是 key_len = 4,只用到了第一列前缀索引。

explain select * from users where age = 11 and rdesc = "asd";

+----+-------------+-------+------+---------------+---------------+---------+-------+------+-------------+
| id | select_type | table | type | possible_keys | key           | key_len | ref   | rows | Extra       |
+----+-------------+-------+------+---------------+---------------+---------+-------+------+-------------+
|  1 | SIMPLE      | users | ref  | age_name_desc | age_name_desc | 4       | const |    1 | Using where |
+----+-------------+-------+------+---------------+---------------+---------+-------+------+-------------+

上述查询缺失了rname列,可以看出当缺失中间列时将不能使用完整的联合索引。查询只用到了最左部分索引,而rdesc由于没有rname无法和左前缀衔接。

explain select * from users where rname = "asd";

+----+-------------+-------+------+---------------+------+---------+------+------+-------------+
| id | select_type | table | type | possible_keys | key  | key_len | ref  | rows | Extra       |
+----+-------------+-------+------+---------------+------+---------+------+------+-------------+
|  1 | SIMPLE      | users | ALL  | NULL          | NULL | NULL    | NULL |   15 | Using where |
+----+-------------+-------+------+---------------+------+---------+------+------+-------------+

上述查询由于查询条件不是最左前缀,将不能使用联合索引age_name_desc,建立联合索引时顺序是很重要的,必须在建索引前考虑清楚。

  • 非精确查询
explain select * from users where age = 11 and rname like 'sad%';

+----+-------------+-------+-------+---------------+---------------+---------+------+------+------------------------------------+
| id | select_type | table | type  | possible_keys | key           | key_len | ref  | rows | Extra                              |
+----+-------------+-------+-------+---------------+---------------+---------+------+------+------------------------------------+
|  1 | SIMPLE      | users | range | age_name_desc | age_name_desc | 36      | NULL |    1 | Using index condition; Using where |
+----+-------------+-------+-------+---------------+---------------+---------+------+------+------------------------------------+

explain select * from users where age = 11 and rname like 'sad%' and rdesc = 'asd';

+----+-------------+-------+-------+---------------+---------------+---------+------+------+------------------------------------+
| id | select_type | table | type  | possible_keys | key           | key_len | ref  | rows | Extra                              |
+----+-------------+-------+-------+---------------+---------------+---------+------+------+------------------------------------+
|  1 | SIMPLE      | users | range | age_name_desc | age_name_desc | 83      | NULL |    1 | Using index condition; Using where |
+----+-------------+-------+-------+---------------+---------------+---------+------+------+------------------------------------+

可以看出like查询当通配符’%’不出现在开头时,是可以应用到索引的。

explain select * from users where age = 11 and rname like '%sad%';

+----+-------------+-------+------+---------------+---------------+---------+-------+------+-------------+
| id | select_type | table | type | possible_keys | key           | key_len | ref   | rows | Extra       |
+----+-------------+-------+------+---------------+---------------+---------+-------+------+-------------+
|  1 | SIMPLE      | users | ref  | age_name_desc | age_name_desc | 4       | const |    1 | Using where |
+----+-------------+-------+------+---------------+---------------+---------+-------+------+-------------+

通配符’%’出现在开头则不行

接下来我们看看范围查询

explain select * from users where age = 61 and rname < 'fasd';

+----+-------------+-------+-------+---------------+---------------+---------+------+------+------------------------------------+
| id | select_type | table | type  | possible_keys | key           | key_len | ref  | rows | Extra                              |
+----+-------------+-------+-------+---------------+---------------+---------+------+------+------------------------------------+
|  1 | SIMPLE      | users | range | age_name_desc | age_name_desc | 36      | NULL |    1 | Using index condition; Using where |
+----+-------------+-------+-------+---------------+---------------+---------+------+------+------------------------------------+
  • 函数和表达式
explain select * from users where (age + 1) = 33;

+----+-------------+-------+------+---------------+------+---------+------+------+-------------+
| id | select_type | table | type | possible_keys | key  | key_len | ref  | rows | Extra       |
+----+-------------+-------+------+---------------+------+---------+------+------+-------------+
|  1 | SIMPLE      | users | ALL  | NULL          | NULL | NULL    | NULL |   15 | Using where |
+----+-------------+-------+------+---------------+------+---------+------+------+-------------+

当查询条件中出现函数或表达式时,将不能应用索引。写查询语句时要尽量避免表达式和函数的出现。

指导性建议

建议在选择性高的列上建立索引,所谓索引的选择性,是指不重复的索引值与表记录数的比值:

Index Selectivity = Cardinality / Count

显然选择性的取值范围为(0, 1],选择性越高的索引价值越大。
比例越大我们扫描的记录数越少,唯一键的区分度是1,而一些状态、性别字段可能在大数据面前区分度就趋近于0

select count(distinct(rname))/count(*) as selectivity from users;

+-------------+
| selectivity |
+-------------+
|      0.9333 |
+-------------+

有一种与索引选择性有关的索引优化策略叫做前缀索引,就是用列的前缀代替整个列作为索引key,当前缀长度合适时,可以做到既使得前缀索引的选择性接近全列索引,同时因为索引key变短而减少了索引文件的大小和维护开销。

select count(distinct(left(rname, 3)))/count(*) as selectivity from users;

+-------------+
| selectivity |
+-------------+
|      0.7333 |
+-------------+

select count(distinct(left(rname, 5)))/count(*) as selectivity from users;

+-------------+
| selectivity |
+-------------+
|      0.9333 |
+-------------+

可以看到,当把前缀取到5时selectivity值就和完整的selectivity值一样了,这样可以大幅度减小索引所占用的空间,而且相应的查询速度也会有一定提升。

    原文作者:elibinary
    原文地址: https://www.jianshu.com/p/79c83531dfd1
    本文转自网络文章,转载此文章仅为分享知识,如有侵权,请联系博主进行删除。
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