MySQL优化(2)--------常用优化

前言

　　之前已经简单介绍了MySQL的优化步骤，那么接下来自然而是就是常用的SQL优化，比如inseer、group by等常用SQL的优化，会涉及SQL语句内部细节（这正是我缺乏的）。最后希望自己能记录完成的一套MySQL优化博文！

　　注：其中部分我并没有全部实验（并不代表是错的），这里只相当于记录下，接下来会慢慢补充！

　　参考资料：《深入浅出MySQL》（有需要PDF电子书的伙伴可以评论或者私信我）

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1、大批量插入数据优化

（1）对于MyISAM存储引擎的表，可以使用：DISABLE KEYS 和 ENABLE KEYS 用来打开或者关闭 MyISAM 表非唯一索引的更新。

ALTER TABLE tbl_name DISABLE KEYS;
loading the data
ALTER TABLE tbl_name ENABLE KEYS;

（2）对于InnoDB引擎，有以下几种优化措施：

　　① 导入的数据按照主键的顺序保存：这是因为InnoDB引擎表示按照主键顺序保存的，如果能将插入的数据提前按照排序好自然能省去很多时间。

　　比如bulk_insert.txt文件是以表user主键的顺序存储的，导入的时间为15.23秒

mysql> load data infile 'mysql/bulk_insert.txt' into table user;
Query OK, 126732 rows affected (15.23 sec)
Records: 126732 Deleted: 0 Skipped: 0 Warnings: 0

　　没有按照主键排序的话，时间为：26.54秒

mysql> load data infile 'mysql/bulk_insert.txt' into table user;
Query OK, 126732 rows affected (26.54 sec)
Records: 126732 Deleted: 0 Skipped: 0 Warnings: 0

　　② 导入数据前执行SET UNIQUE_CHECKS=0，关闭唯一性校验，带导入之后再打开设置为1：校验会消耗时间，在数据量大的情况下需要考虑。

　　③ 导入前设置SET AUTOCOMMIT=0，关闭自动提交，导入后结束再设置为1：这是因为自动提交会消耗部分时间与资源，虽然消耗不是很大，但是在数据量大的情况下还是得考虑。

2、INSERT的优化

（1）尽量使用多个值表的 INSERT 语句，这种方式将大大缩减客户端与数据库之间的连接、关闭等消耗。（同一客户的情况下），即：

　INSERT INTO tablename values(1,2),(1,3),(1,4)

实验：插入8条数据到user表中（使用navicat客户端工具）

insert into user values(1,'test',replace(uuid(),'-',''));
insert into user values(2,'test',replace(uuid(),'-',''));
insert into user values(3,'test',replace(uuid(),'-',''));
insert into user values(4,'test',replace(uuid(),'-',''));
insert into user values(5,'test',replace(uuid(),'-',''));
insert into user values(6,'test',replace(uuid(),'-',''));
insert into user values(7,'test',replace(uuid(),'-',''));
insert into user values(8,'test',replace(uuid(),'-',''));

得到反馈：

[SQL] insert into user values(1,'test',replace(uuid(),'-',''));
受影响的行: 1
时间: 0.033s
[SQL]
insert into user values(2,'test',replace(uuid(),'-',''));
受影响的行: 1
时间: 0.034s
[SQL]
insert into user values(3,'test',replace(uuid(),'-',''));
受影响的行: 1
时间: 0.056s
[SQL]
insert into user values(4,'test',replace(uuid(),'-',''));
受影响的行: 1
时间: 0.008s
[SQL]
insert into user values(5,'test',replace(uuid(),'-',''));
受影响的行: 1
时间: 0.008s
[SQL]
insert into user values(6,'test',replace(uuid(),'-',''));
受影响的行: 1
时间: 0.024s
[SQL]
insert into user values(7,'test',replace(uuid(),'-',''));
受影响的行: 1
时间: 0.004s
[SQL]
insert into user values(8,'test',replace(uuid(),'-',''));
受影响的行: 1
时间: 0.004s

总共的时间为0.171秒，接下来使用多值表形式：

insert into user values
(9,'test',replace(uuid(),'-','')),
(10,'test',replace(uuid(),'-','')),
(11,'test',replace(uuid(),'-','')),
(12,'test',replace(uuid(),'-','')),
(13,'test',replace(uuid(),'-','')),
(14,'test',replace(uuid(),'-','')),
(15,'test',replace(uuid(),'-','')),
(16,'test',replace(uuid(),'-',''));

得到反馈：

[SQL] insert into user values
(9,'test',replace(uuid(),'-','')),
(10,'test',replace(uuid(),'-','')),
(11,'test',replace(uuid(),'-','')),
(12,'test',replace(uuid(),'-','')),
(13,'test',replace(uuid(),'-','')),
(14,'test',replace(uuid(),'-','')),
(15,'test',replace(uuid(),'-','')),
(16,'test',replace(uuid(),'-',''));
受影响的行: 8
时间: 0.038s

得到时间为0.038，这样一来可以很明显节约时间优化SQL

（2）如果在不同客户端插入很多行，可使用INSERT DELAYED语句得到更高的速度，DELLAYED含义是让INSERT语句马上执行，其实数据都被放在内存的队列中。并没有真正写入磁盘。LOW_PRIORITY刚好相反。

（3）将索引文件和数据文件分在不同的磁盘上存放（InnoDB引擎是在同一个表空间的）。

（4）如果批量插入，则可以增加bluk_insert_buffer_size变量值提供速度（只对MyISAM有用）

（5）当从一个文本文件装载一个表时，使用LOAD DATA INFILE，通常比INSERT语句快20倍。

3、GROUP BY的优化

　　在默认情况下，MySQL中的GROUP BY语句会对其后出现的字段进行默认排序（非主键情况），就好比我们使用ORDER BY col1,col2,col3...所以我们在后面跟上具有相同列（与GROUP BY后出现的col1,col2,col3...相同）ORDER BY子句并没有影响该SQL的实际执行性能。

　　那么就会有这样的情况出现，我们对查询到的结果是否已经排序不在乎时，可以使用ORDER BY NULL禁止排序达到优化目的。下面使用EXPLAIN命令分析SQL。

　　在user_1中执行select id, sum(money) form user_1 group by name时，会默认排序（注意group by后的column是非index才会体现group by的排序，如果是primary key，那之前说过了InnoDB默认是按照主键index排好序的）

mysql> select*from user_1;
+----+----------+-------+
| id | name     | money |
+----+----------+-------+
|  1 | Zhangsan |    32 |
|  2 | Lisi     |    65 |
|  3 | Wangwu   |    44 |
|  4 | Lijian   |   100 |
+----+----------+-------+
4 rows in set

不禁止排序，即不使用ORDER BY NULL时：有明显的Using filesort。

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" alt="" width="624" height="258" />　　

当使用ORDER BY NULL禁止排序后，Using filesort不存在

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" 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4、ORDER BY 的优化　　

MySQL可以使用一个索引来满足ORDER BY 子句的排序，而不需要额外的排序，但是需要满足以下几个条件：

（1）WHERE 条件和OREDR BY 使用相同的索引：即key_part1与key_part2是复合索引，where中使用复合索引中的key_part1

SELECT*FROM user WHERE key_part1=1 ORDER BY key_part1 DESC, key_part2 DESC;

（2）而且ORDER BY顺序和索引顺序相同：

SELECT*FROM user ORDER BY key_part1, key_part2;

（3）并且要么都是升序要么都是降序：

SELECT*FROM user ORDER BY key_part1 DESC, key_part2 DESC;

但以下几种情况则不使用索引：

（1）ORDER BY中混合ASC和DESC：

SELECT*FROM user ORDER BY key_part1 DESC, key_part2 ASC;

（2）查询行的关键字与ORDER BY所使用的不相同，即WHERE 后的字段与ORDER BY 后的字段是不一样的

SELECT*FROM user WHERE key2 = ‘xxx’ ORDER BY key1;

（3）ORDER BY对不同的关键字使用，即ORDER BY后的关键字不相同

SELECT*FROM user ORDER BY key1, key2;

5、OR的优化

当MySQL使用OR查询时，如果要利用索引的话，必须每个条件列都使独立索引，而不是复合索引（多列索引），才能保证使用到查询的时候使用到索引。

比如我们新建一张用户信息表user_info

mysql> select*from user_info;
+---------+--------+----------+-----------+
| user_id | idcard | name     | address    |
+---------+--------+----------+-----------+
|       1 | 111111 | Zhangsan | Kunming   |
|       2 | 222222 | Lisi     | Beijing   |
|       3 | 333333 | Wangwu   | Shanghai  |
|       4 | 444444 | Lijian   | Guangzhou |
+---------+--------+----------+-----------+
4 rows in set

之后创建ind_name_id(user_id, name)复合索引、id_index(id_index)独立索引，idcard主键索引三个索引。

mysql> show index from user_info;
+-----------+------------+-------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table     | Non_unique | Key_name    | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+-----------+------------+-------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| user_info |          0 | PRIMARY     |            1 | idcard      | A         |           4 | NULL     | NULL   |      | BTREE      |         |               |
| user_info |          1 | ind_name_id |            1 | user_id     | A         |           4 | NULL     | NULL   |      | BTREE      |         |               |
| user_info |          1 | ind_name_id |            2 | name        | A         |           4 | NULL     | NULL   | YES  | BTREE      |         |               |
| user_info |          1 | id_index    |            1 | user_id     | A         |           4 | NULL     | NULL   |      | BTREE      |         |               |
+-----------+------------+-------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
4 rows in set

测试一：OR连接两个有单独索引的字段，整个SQL查询才会用到索引(index_merge)，并且我们知道OR实际上是把每个结果最后UNION一起的。

mysql> explain select*from user_info where user_id=1 or idcard='';
+----+-------------+-----------+------------+-------------+------------------------------+---------------------+---------+------+------+----------+----------------------------------------------------+
| id | select_type | table     | partitions | type        | possible_keys                | key                 | key_len | ref  | rows | filtered | Extra                                              |
+----+-------------+-----------+------------+-------------+------------------------------+---------------------+---------+------+------+----------+----------------------------------------------------+
|  1 | SIMPLE      | user_info | NULL       | index_merge | PRIMARY,ind_name_id,id_index | ind_name_id,PRIMARY | 4,62    | NULL |    2 |      100 | Using sort_union(ind_name_id,PRIMARY); Using where |
+----+-------------+-----------+------------+-------------+------------------------------+---------------------+---------+------+------+----------+----------------------------------------------------+
1 row in set

测试二：OR使用复合索引的字段name，与没有索引的address，整个SQL都是ALL全表扫描的

mysql> explain select*from user_info where name='Zhangsan' or address='Beijing';
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | user_info | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    4 |    43.75 | Using where |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set

交换OR位置并且使用另外的复合索引的列，也是ALL全表扫描：

mysql> explain select*from user_info where address='Beijing' or user_id=1;
+----+-------------+-----------+------------+------+----------------------+------+---------+------+------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys        | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-----------+------------+------+----------------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | user_info | NULL       | ALL  | ind_name_id,id_index | NULL | NULL    | NULL |    4 |    43.75 | Using where |
+----+-------------+-----------+------------+------+----------------------+------+---------+------+------+----------+-------------+
1 row in set

6、优化嵌套查询

使用嵌套查询有时候可以使用更有效的JOIN连接代替，这是因为MySQL中不需要在内存中创建临时表完成SELECT子查询与主查询两部分查询工作。但是并不是所有的时候都成立，最好是在on关键字后面的列有索引的话，效果会更好！

比如在表major中major_id是有索引的：

select * from student u left join major m on u.major_id=m.major_id where m.major_id is null;

而通过嵌套查询时，在内存中创建临时表完成SELECT子查询与主查询两部分查询工作，会有一定的消耗

select * from student u where major_id not in (select major_id from major);

7、使用SQL提示

SQL提示（SQL HINT）是优化数据库的一个重要手段，就是往SQL语句中加入一些人为的提示来达到优化目的。下面是一些常用的SQL提示：

（1）USE INDEX：使用USE INDEX是希望MySQL去参考索引列表，就可以让MySQL不需要考虑其他可用索引，其实也就是possible_keys属性下参考的索引值

mysql> explain select* from user_info use index(id_index,ind_name_id) where user_id>0;
+----+-------------+-----------+------------+------+----------------------+------+---------+------+------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys        | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-----------+------------+------+----------------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | user_info | NULL       | ALL  | ind_name_id,id_index | NULL | NULL    | NULL |    4 |      100 | Using where |
+----+-------------+-----------+------------+------+----------------------+------+---------+------+------+----------+-------------+
1 row in set

mysql> explain select* from user_info use index(id_index) where user_id>0;
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | user_info | NULL       | ALL  | id_index      | NULL | NULL    | NULL |    4 |      100 | Using where |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set

（2）IGNORE INDEX忽略索引

我们使用user_id判断，用不到其他索引时，可以忽略索引。即与USE INDEX相反，从possible_keys中减去不需要的索引，但是实际环境中很少使用。

mysql> explain select* from user_info ignore index(primary,ind_name_id,id_index) where user_id>0;
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | user_info | NULL       | ALL  | NULL          | NULL | NULL    | NULL |    4 |    33.33 | Using where |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set

（3）FORCE INDEX强制索引

比如where user_id > 0，但是user_id在表中都是大于0的，自然就会进行ALL全表搜索，但是使用FORCE INDEX虽然执行效率不是最高（where user_id > 0条件决定的）但MySQL还是使用索引。

mysql> explain select* from user_info where user_id>0;
+----+-------------+-----------+------------+------+----------------------+------+---------+------+------+----------+-------------+
| id | select_type | table     | partitions | type | possible_keys        | key  | key_len | ref  | rows | filtered | Extra       |
+----+-------------+-----------+------------+------+----------------------+------+---------+------+------+----------+-------------+
|  1 | SIMPLE      | user_info | NULL       | ALL  | ind_name_id,id_index | NULL | NULL    | NULL |    4 |      100 | Using where |
+----+-------------+-----------+------------+------+----------------------+------+---------+------+------+----------+-------------+
1 row in set

之后强制使用独立索引id_index(user_id)：

mysql> explain select* from user_info force index(id_index) where user_id>0;
+----+-------------+-----------+------------+-------+---------------+----------+---------+------+------+----------+-----------------------+
| id | select_type | table     | partitions | type  | possible_keys | key      | key_len | ref  | rows | filtered | Extra                 |
+----+-------------+-----------+------------+-------+---------------+----------+---------+------+------+----------+-----------------------+
|  1 | SIMPLE      | user_info | NULL       | range | id_index      | id_index | 4       | NULL |    4 |      100 | Using index condition |
+----+-------------+-----------+------------+-------+---------------+----------+---------+------+------+----------+-----------------------+
1 row in set

---

总结

　　（1）很多时候数据库的性能是由于不合适（是指效率不高，可能会导致锁表等）的SQL语句造成，本篇博文只是介绍简单的SQL优化

　　（2）其中有些优化在真正开发中是用不到的，但是一旦出问题性能下降的时候需要去一一分析。