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MySQL优化（1）--------常用的优化步骤

2018-07-24 08:01:19来源：博客园阅读 ()

在开始博客之前，还是同样的给一个大概的目录结构，实则即为一般MySQL的优化步骤

1、查看SQL的执行频率---------------使用show status命令

2、定位哪些需要优化的SQL------------通过慢查询记录+show processlist命令查看当前线程

3、分析为什么SQL执行效率低------------使用explain/desc命令分析

相关列简单解释：type、table、select_type...

4、对症下药采取优化措施-----------举例采取index进行优化

如何使用索引？
使用索引应该注意的事项
查看索引使用情况

主要参考资料：《深入浅出MySQL》，https://dev.mysql.com/doc/refman/8.0/en/statement-optimization.html

一、查看SQL执行频率

　　使用show [session|gobal] status命令了解SQL执行频率、线程缓存内的线程的数量、当前打开的连接的数量、获得的表的锁的次数等。

比如执行show status like 'Com_%'查看每个语句执行的次数即频率，其中Com_xxx中xxx表示就是语句，比如Com_select：执行select操作的次数。

 1 mysql> use test;
 2 Database changed
 3 mysql> show status like 'Com_%';
 4 +-----------------------------+-------+
 5 | Variable_name               | Value |
 6 +-----------------------------+-------+
 7 | Com_admin_commands          | 0     |
 8 | Com_assign_to_keycache      | 0     |
 9 | Com_alter_db                | 0     |
10 | Com_alter_db_upgrade        | 0     |
11 | Com_alter_event             | 0     |
12 | Com_alter_function          | 0     |
13 | Com_alter_instance          | 0     |
14 | Com_alter_procedure         | 0     |
15 | Com_alter_server            | 0     |
16 | Com_alter_table             | 0     |
17 | Com_alter_tablespace        | 0     |
18 | Com_alter_user              | 0     |
19 | Com_analyze                 | 0     |
20 | Com_begin                   | 0     |
21 | Com_binlog                  | 0     |
22 | Com_call_procedure          | 0     |
23 | Com_change_db               | 2     |
24 | Com_change_master           | 0     |
25 | Com_change_repl_filter      | 0     |
26 | Com_check                   | 0     |
27 | Com_checksum                | 0     |
28 | Com_commit                  | 0     |
29 | Com_create_db               | 0     |
30 | Com_create_event            | 0     |
31 | Com_create_function         | 0     |
32 | Com_create_index            | 0     |
　　..............................

比如执行show status like 'slow_queries'查看慢查询次数（黑人问号？？什么是慢查询呢？就是通过设置查询时间阈值long_query_time（0-10s）并打开开关show_query_log（1=OFF/0=ON），当超过这个阈值的查询都称之为慢查询,通常用来划分执行SQL效率）

mysql> show status like 'slow_queries';
+---------------+-------+
| Variable_name | Value |
+---------------+-------+
| Slow_queries  | 0     |
+---------------+-------+
1 row in set

比如执行show status like 'uptime'查看服务工作时间（即运行时间）：

mysql> show status like 'uptime';
+---------------+-------+
| Variable_name | Value |
+---------------+-------+
| Uptime        | 21645 |
+---------------+-------+
1 row in set

比如执行show status like 'connections'查看MySQL连接数：

mysql> show status like 'connections';
+---------------+-------+
| Variable_name | Value |
+---------------+-------+
| Connections   | 6     |
+---------------+-------+
1 row in set

　　通过show [session|gobal] status命令很清楚地看到哪些SQL执行效率不如人意，但是具体是怎么个不如意法，还得继续往下看，使用EXPLAIN命令分析具体的SQL语句

二、定位效率低的SQL

　　上面也提到过慢查询这个概念主要是用来划分效率低的SQL，但是慢查询是在整个查询结束后才记录的，所以光是靠慢查询日志是跟踪不了效率低的SQL。一般有两种方式定位效率低的SQL：

　　1、通过慢查询日志查看效率低的SQL语句，慢查询日志是通过show_query_log_file指定存储路径的，里面记录所有超过long_query_time的SQL语句（关于日志的查看，日后再一步研究学习），但是需要慢查询日志的产生是在查询结束后才有的。

　　2、通过show processlist命令查看当前MySQL进行的线程，可以看到线程的状态信息

mysql> show processlist;
+----+------+-----------------+------+---------+------+----------+------------------+
| Id | User | Host            | db   | Command | Time | State    | Info             |
+----+------+-----------------+------+---------+------+----------+------------------+
|  2 | root | localhost:58377 | NULL | Sleep   | 2091 |          | NULL             |
|  3 | root | localhost:58382 | test | Sleep   | 2083 |          | NULL             |
|  4 | root | localhost:58386 | test | Sleep   | 2082 |          | NULL             |
|  5 | root | localhost:59092 | test | Query   |    0 | starting | show processlist |
+----+------+-----------------+------+---------+------+----------+------------------+
4 rows in set

　　其中主要的是state字段，表示当前SQL语句线程的状态，如Sleeping 表示正在等待客户端发送新请求，Sending data把查询到的data结果发送给客户端等等，具体请看https://dev.mysql.com/doc/refman/8.0/en/general-thread-states.html

三、查看分析效率低的SQL

　　MYSQL 5.6.3以前只能EXPLAIN SELECT; MYSQL5.6.3以后就可以EXPLAIN SELECT,UPDATE,DELETE，现在我们先创建一个user_table的表，之后分析select* from user where name=''语句

mysql> create table user(id int, name varchar(10),password varchar(32),primary key(id))engine=InnoDB;
Query OK, 0 rows affected

之后插入三条数据：

mysql> insert into user values(1,'Zhangsan',replace(UUID(),'-','')),(2,'Lisi',replace(UUID(),'-','')),(3,'Wangwu',replace(UUID(),'-',''));
Query OK, 3 rows affected
Records: 3  Duplicates: 0  Warnings: 0
mysql> select* from user;
+----+----------+----------------------------------+
| id | name     | password                         |
+----+----------+----------------------------------+
|  1 | Zhangsan | 2d7284808e5111e8af74201a060059ce |
|  2 | Lisi     | 2d73641c8e5111e8af74201a060059ce |
|  3 | Wangwu   | 2d73670c8e5111e8af74201a060059ce |
+----+----------+----------------------------------+
3 rows in set

下面以分析select*from user where name='Lisi'语句为例：

mysql> explain select*from user where name='Lisi';
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | user  | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    3 |    33.33 | Using where |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set

下面讲解select_type等常见列的含义的：

（1）select_type：表示SELECT的类型，主要有：

SIMPLE：简单表，没有表连接或者子查询
PRIMARY：主查询，即最外城的查询
UNION：UNION中的第二个或者后面的语句
SUBQUERY：子查询中的第一个SELECT

（2）table：结果输出的表

（3）type：表示表的连接类型，性能由好到差为：

system：常量表
const：单表中最多有一行匹配，比如primary key，unique index
eq_ref：多表连接中使用primary key，unique index
ref：使用普通索引
ref_or_null：与ref类似，但是包含了NULL查询
index_merge：索引合并优化
unique_subquery：in后面是一个查询主键字段的子查询
index_subquery：in后面是非唯一索引字段的子查询
range：单表中范围查看，使用like模糊查询
index：对于后面每一行都通过查询索引得到数据
all：表示全表查询

（3）possible_key：查询时可能使用的索引

（4）key：表示实际使用的索引

（5）key_len：索引字段的长度

（6）rows：查询时实际扫描的行数

（7）Extra：执行情况的说明和描述

（8）partitions：分区数目

（9）filtered：查询过滤的表占的百分比，比如这里查询的记录是name=Lisi的记录，占三条记录的33.3%

四、关于索引的优化

1、使用索引优化的举例

　　上个例子我们看到到执行explain select*from user where name='Lisi'，扫描了3行（全部行数）使用了全表搜索all。如果实际业务中name是经常用到查询的字段（是指经常跟在where后的字段，不是select后的字段）并且数据量很大的情况呢？这时候就需要索引了（索引经常用到where后面的字段比select后面的字段效果更好，或者说就是要使用在where后面的字段上）

增加name前缀索引（这里只是举例，并没有选择最合适的前缀）：

mysql> create index index_name on user(name(2));
Query OK, 0 rows affected
Records: 0  Duplicates: 0  Warnings: 0

执行explain分析

mysql> explain select*from user where name = 'Lisi';
+----+-------------+-------+------------+------+---------------+------------+---------+-------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key        | key_len | ref   | rows | filtered | Extra       |
+----+-------------+-------+------------+------+---------------+------------+---------+-------+------+----------+-------------+
|  1 | SIMPLE      | user  | NULL       | ref  | index_name    | index_name | 9       | const |    1 |      100 | Using where |
+----+-------------+-------+------------+------+---------------+------------+---------+-------+------+----------+-------------+
1 row in set

　　可以看到type变为ref、rows降为1（实际上只要使用了索引都是1），filtered过滤百分比为100%，实际用到的索引为index_name。如果数据量很大的话使用索引就是很好的优化措施，对于如何选择索引，什么时候用索引，我做出了如下总结：

2、如何高效使用索引？

　　(1) 创建多列索引时，只要查询条件中用到最左边的列，索引一般都会被用到

　　我们创建一张没有索引的表user_1:

mysql> show create table 
user_1;
+--------+--------------------------------------------------------------------------------------------------------------------------+
| Table  | Create Table                                                                                                             |
+--------+--------------------------------------------------------------------------------------------------------------------------+
| user_1 | CREATE TABLE `user_1` (
  `id` int(11) DEFAULT NULL,
  `name` varchar(10) DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8 |
+--------+--------------------------------------------------------------------------------------------------------------------------+
　1 row in set

　之后同样插入数据：

mysql> select *from user_1;
+----+----------+
| id | name     |
+----+----------+
|  1 | Zhangsan |
|  2 | Lisi     |
+----+----------+
2 rows in set

创建多列索引index_id_name

mysql> create index index_id_name on user_1(id,name);
Query OK, 0 rows affected
Records: 0  Duplicates: 0  Warnings: 0

　实验查询explain分析name与id

mysql> explain select * from user_1 where id=1;
+----+-------------+--------+------------+------+---------------+---------------+---------+-------+------+----------+-------------+
| id | select_type | table  | partitions | type | possible_keys | key           | key_len | ref   | rows | filtered | Extra       |
+----+-------------+--------+------------+------+---------------+---------------+---------+-------+------+----------+-------------+
|  1 | SIMPLE      | user_1 | NULL       | ref  | index_id_name | index_id_name | 5       | const |    1 |      100 | Using index |
+----+-------------+--------+------------+------+---------------+---------------+---------+-------+------+----------+-------------+
1 row in set

mysql> explain select * from user_1 where name='Lisi';
+----+-------------+--------+------------+-------+---------------+---------------+---------+------+------+----------+--------------------------+
| id | select_type | table  | partitions | type  | possible_keys | key           | key_len | ref  | rows | filtered | Extra                    |
+----+-------------+--------+------------+-------+---------------+---------------+---------+------+------+----------+--------------------------+
|  1 | SIMPLE      | user_1 | NULL       | index | NULL          | index_id_name | 38      | NULL |    2 |       50 | Using where; Using index |
+----+-------------+--------+------------+-------+---------------+---------------+---------+------+------+----------+--------------------------+
1 row in set

　　可以看到使用最左列id的时候，rows为1，并且Extra明确使用了index，key的值为id_name_index，type的值为ref，而where不用到id，而是name的话，rows的值为2。filtered为50%，虽然key是index_id_name，但是表明是索引（个人理解，应该不太准确）

　　(2) 使用like的查询，只有%不是第一个字符并且%后面是常量的情况下，索引才可能会被使用。

　　执行explain select *from user where name like ‘%Li’后type为ALL且key的值为NULL，执行explain select *from user where name like ‘Li%’后key值不为空为index_name。

mysql> explain select*from user where name like '%Li';
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | user  | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    3 |    33.33 | Using where |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set
mysql> explain select*from user where name like 'Li%';
+----+-------------+-------+------------+-------+---------------+------------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type  | possible_keys | key        | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-------+------------+-------+---------------+------------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | user  | NULL       | range | index_name    | index_name | 9       | NULL |    1 |      100 | Using where |
+----+-------------+-------+------------+-------+---------------+------------+---------+------+------+----------+-------------+
1 row in set

　　(3) 如果对打的文本进行搜索，使用全文索引而不是用like ‘%...%’（只有MyISAM支持全文索引）。

　　(4) 如果列名是索引，使用column_name is null将使用索引。

mysql> explain select*from user where name is null;
+----+-------------+-------+------------+------+---------------+------------+---------+-------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key        | key_len | ref   | rows | filtered | Extra       |
+----+-------------+-------+------------+------+---------------+------------+---------+-------+------+----------+-------------+
|  1 | SIMPLE      | user  | NULL       | ref  | index_name    | index_name | 9       | const |    1 |      100 | Using where |
+----+-------------+-------+------------+------+---------------+------------+---------+-------+------+----------+-------------+
1 row in set

mysql> explain select*from user where password
 is null;
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | user  | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    3 |    33.33 | Using where |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set

3、哪些情况下即使有索引也用不到？

　　(1) MySQL使用MEMORY/HEAP引擎（使用的HASH索引），并且WHERE条件中不会使用”=”,in等进行索引列，那么不会用到索引（这是关于引擎部分特点，之后会介绍）。

　　(2) 用OR分隔开的条件，如果OR前面的条件中的列有索引，而后面的列没有索引，那么涉及到的列索引不会被使用。

　　执行命令show index from user可以看出password字段并没有使用任何索引，而id使用了两个索引，但是where id=1 or password='2d7284808e5111e8af74201a060059ce' 导致没有使用id列的primary索引与id_name_index索引

mysql> show index from user;
+-------+------------+---------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name      | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+-------+------------+---------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| user  |          0 | PRIMARY       |            1 | id          | A         |           3 | NULL     | NULL   |      | BTREE      |         |               |
| user  |          1 | index_name    |            1 | name        | A         |           3 |        2 | NULL   | YES  | BTREE      |         |               |
| user  |          1 | id_name_index |            1 | id          | A         |           3 | NULL     | NULL   |      | BTREE      |         |               |
| user  |          1 | id_name_index |            2 | name        | A         |           3 | NULL     | NULL   | YES  | BTREE      |         |               |
+-------+------------+---------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
4 rows in set

mysql> explain select*from user where id=1 or password='2d7284808e5111e8af74201a060059ce';
+----+-------------+-------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys         | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | user  | NULL       | ALL  | PRIMARY,id_name_index | NULL | NULL    | NULL |    3 |    55.56 | Using where |
+----+-------------+-------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
1 row in set

　　(3) 不是用到复合索引中的第一列即最左边的列的话，索引就不起作用（上面已经介绍）。

　　(4) 如果like是以%开头的(上面已经介绍)

　　(5) 如果列类型是字符串，那么where条件中字符常量值不用’’引号引起来的话，那就不会失去索引效果，这是因为MySQL会把输入的常量值进行转换再使用索引。

　　select * from user_1 where name =250，其中name的索引为name_index，并且是varchar字符串类型，但是并没有将250用引号变成’250’，那么explain之后的ref仍然为NULL,rows为3

mysql> show index from user_1;
+--------+------------+---------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table  | Non_unique | Key_name      | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+--------+------------+---------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| user_1 |          1 | index_id_name |            1 | id          | A         |           2 | NULL     | NULL   | YES  | BTREE      |         |               |
| user_1 |          1 | index_id_name |            2 | name        | A         |           2 | NULL     | NULL   | YES  | BTREE      |         |               |
| user_1 |          1 | name_index    |            1 | name        | A         |           3 |        5 | NULL   | YES  | BTREE      |         |               |
+--------+------------+---------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
3 rows in set

mysql> explain select*from user_1 where name=250;
+----+-------------+--------+------------+-------+---------------+---------------+---------+------+------+----------+--------------------------+
| id | select_type | table  | partitions | type  | possible_keys | key           | key_len | ref  | rows | filtered | Extra                    |
+----+-------------+--------+------------+-------+---------------+---------------+---------+------+------+----------+--------------------------+
|  1 | SIMPLE      | user_1 | NULL       | index | name_index    | index_id_name | 38      | NULL |    3 |    33.33 | Using where; Using index |
+----+-------------+--------+------------+-------+---------------+---------------+---------+------+------+----------+--------------------------+
1 row in set

mysql> explain select*from user_1 where name='250';
+----+-------------+--------+------------+------+---------------+------------+---------+-------+------+----------+-------------+
| id | select_type | table  | partitions | type | possible_keys | key        | key_len | ref   | rows | filtered | Extra       |
+----+-------------+--------+------------+------+---------------+------------+---------+-------+------+----------+-------------+
|  1 | SIMPLE      | user_1 | NULL       | ref  | name_index    | name_index | 18      | const |    1 |      100 | Using where |
+----+-------------+--------+------------+------+---------------+------------+---------+-------+------+----------+-------------+
1 row in set

4、查看索引的使用情况

执行show status like ‘Handler_read%’可以看到一个值Handler_read_key，它代表一行被索引值读的次数，如果值很低说明增加索引得到的性能改善不高，因为索引并不经常使用。

mysql> show status like 'Handler_read%' ;
+-----------------------+-------+
| Variable_name         | Value |
+-----------------------+-------+
| Handler_read_first    | 3     |
| Handler_read_key      | 5     |
| Handler_read_last     | 0     |
| Handler_read_next     | 0     |
| Handler_read_prev     | 0     |
| Handler_read_rnd      | 0     |
| Handler_read_rnd_next | 20    |
+-----------------------+-------+
7 rows in set