众所周知，在mysql里的后通配符可以使用索引查找，前通配查询却无法使用到索引，即使是使用到了索引，也是使用了索引全扫描，效率依然不高，再MySQL5.7之前，一直都没有好的办法解决，但是到了MySQL5.7，自从有了虚拟列，这个问题就好办多了，能够已空间换时间。

创建测试表

root@localhost [zeno]>show create tabletest_user\G ;*************************** 1. row ***************************

Table: test_userCreate Table: CREATE TABLE`test_user` (

`uid`int(11) NOT NULLAUTO_INCREMENT,

`name`varchar(32) DEFAULT NULL,

`add_time`datetime DEFAULT NULL,PRIMARY KEY(`uid`),KEY`ix_name` (`name`)

) ENGINE=InnoDB AUTO_INCREMENT=6037060 DEFAULT CHARSET=utf81 row in set (0.00sec)

ERROR:

No query specified

使用python插入测试数据

#!/usr/bin/python

importstringimportrandomimportMySQLdbimporttime

conn= MySQLdb.connect(host='IPAddr',

port=3306,

user='zeno',

passwd='zeno',

db='zeno')definsert(para):

i= 11

whileTrue:

r_name= ''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(random.randint(10, 30)))printr_name

cursor=conn.cursor()

cursor.execute("INSERT INTO test_user (name,add_time) VALUES ('%s', now())" %str(r_name))

i= i + 1conn.commit()#time.sleep(0.1)

printi

insert(conn)

查看插入的数据量

root@localhost [zeno]>show table status like 'test_user'\G ;*************************** 1. row ***************************Name: test_user

Engine: InnoDB

Version:10Row_format: Dynamic

Rows:6002441Avg_row_length:51Data_length:310165504Max_data_length:0Index_length:0Data_free:5242880Auto_increment:6037060Create_time:2017-11-23 16:25:15Update_time:2017-11-23 16:23:29Check_time:NULLCollation: utf8_general_ci

Checksum:NULLCreate_options:

Comment:1 row in set (0.00sec)

ERROR:

No query specified

root@localhost [zeno]>select * from test_user limit 10;+-----+-------------------------------+---------------------+

| uid | name | add_time |

+-----+-------------------------------+---------------------+

| 1 | U0WUJ3JJ81IRP27BSA4471 | 2017-11-23 15:37:49 |

| 2 | SOLYNM9Q9A5Y94YG | 2017-11-23 15:37:49 |

| 3 | ONNU5PPKXC3GBR | 2017-11-23 15:37:49 |

| 4 | WVC6GOJ29C | 2017-11-23 15:37:49 |

| 5 | Z653X99ZZI | 2017-11-23 15:37:49 |

| 6 | YP92P02DIKQ8O66K | 2017-11-23 15:37:49 |

| 7 | 2X3G6H8849SDP | 2017-11-23 15:37:49 |

| 8 | 9N9F668XQMTRQSCNE0FWJBMMJEFC0 | 2017-11-23 15:37:50 |

| 9 | 15XAHWZ1IJBP6P4EKCH | 2017-11-23 15:37:50 |

| 10 | VHQJQGQC7U | 2017-11-23 15:37:50 |

+-----+-------------------------------+---------------------+

10 rows in set (0.00 sec)

开始测试

一、验证查询条件中使用后通配符的情况

root@localhost [zeno]>select * from test_user where name like '9N9F668XQ%';+-----+-------------------------------+---------------------+

| uid | name | add_time |

+-----+-------------------------------+---------------------+

| 8 | 9N9F668XQMTRQSCNE0FWJBMMJEFC0 | 2017-11-23 15:37:50 |

+-----+-------------------------------+---------------------+

1 row in set (0.00sec)

root@localhost [zeno]>explain select * from test_user where name like '9N9F668XQ%';+----+-------------+-----------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+

| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |

+----+-------------+-----------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+

| 1 | SIMPLE | test_user | NULL | range | ix_name | ix_name | 99 | NULL | 1 | 100.00 | Using index condition |

+----+-------------+-----------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+

1 row in set, 1 warning (0.00 sec)

600W的数据，执行时间0.00sec，已经是毫秒级查询了

从执行计划中可以看出，type=range， key = 'ix_name'，证明是对索引ix_name进行了范围查找，所以，能很快地得到结果

二、验证查询条件中使用前通配符的情况

root@localhost [zeno]>select * from test_user where name like '%WJBMMJEFC0';+-----+-------------------------------+---------------------+

| uid | name | add_time |

+-----+-------------------------------+---------------------+

| 8 | 9N9F668XQMTRQSCNE0FWJBMMJEFC0 | 2017-11-23 15:37:50 |

+-----+-------------------------------+---------------------+

1 row in set (3.84sec)

root@localhost [zeno]>explain select * from test_user where name like '%WJBMMJEFC0';+----+-------------+-----------+------------+------+---------------+------+---------+------+---------+----------+-------------+

| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |

+----+-------------+-----------+------------+------+---------------+------+---------+------+---------+----------+-------------+

| 1 | SIMPLE | test_user | NULL | ALL | NULL | NULL | NULL | NULL | 6002441 | 11.11 | Using where |

+----+-------------+-----------+------------+------+---------------+------+---------+------+---------+----------+-------------+

1 row in set, 1 warning (0.00 sec)

600万的数据，运行了3.84sec，速度非常慢

从执行计划中type=‘ALL’可以看出是进行了全表扫描，扫描完之后，再根据where条件找出合适的数据

在MySQL5.7之前，对于这种条件中使用了前通配符的查询，几乎就是束手无策，但是，MySQL5.7中增加了一项新功能，可以用较小的代价实现快速查询

创建虚拟列

root@localhost [zeno]>alter table test_user add r_name varchar(32) generated always as (reverse(`name`));

Query OK,0 rows affected (0.44sec)

Records:0 Duplicates: 0 Warnings: 0

在虚拟列上创建索引(跟一般创建索引无异)

root@localhost [zeno]>create index ix_r_name ontest_user(r_name) ;

Query OK,0 rows affected (41.90sec)

Records:0 Duplicates: 0 Warnings: 0

问题来了，已经创建了虚拟列，也创建了所以，怎么实现对前通配符的快速查询呢？

先用一个简短的数字来说明一下思路：假设要查询的列的最终值为‘0123456789’，前通配查询的时候，条件是 name like '%6789'，但是已经创建了虚拟列，虚拟列的效果是把原来的数据反转，也就是变成了‘9876543210’，那么，查询的条件变成了name like '9876%'，但是，不可能是每次都要自己计算一下，把'6789'换成‘9876’

因此，在查询的时候，还要取巧的一步，条件中再次把输入的值反转，结果如下

root@localhost [zeno]>select * from test_user where r_name like concat(reverse('WJBMMJEFC0'),'%');+-----+-------------------------------+---------------------+-------------------------------+

| uid | name | add_time | r_name |

+-----+-------------------------------+---------------------+-------------------------------+

| 8 | 9N9F668XQMTRQSCNE0FWJBMMJEFC0 | 2017-11-23 15:37:50 | 0CFEJMMBJWF0ENCSQRTMQX866F9N9 |

+-----+-------------------------------+---------------------+-------------------------------+

1 row in set (0.00sec)

root@localhost [zeno]>explain select * from test_user where r_name like concat(reverse('WJBMMJEFC0'),'%');+----+-------------+-----------+------------+-------+---------------+-----------+---------+------+------+----------+-------------+

| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |

+----+-------------+-----------+------------+-------+---------------+-----------+---------+------+------+----------+-------------+

| 1 | SIMPLE | test_user | NULL | range | ix_r_name | ix_r_name | 99 | NULL | 1 | 100.00 | Using where |

+----+-------------+-----------+------------+-------+---------------+-----------+---------+------+------+----------+-------------+

1 row in set, 1 warning (0.00 sec)

从执行结果来看，效果已经达到了，600W的数据也只是执行了0.00sec

三、在条件中同时使用了前通配符和后通配符的情况，暂时没有好的解决办法

参考文档：

MySQL官方介绍虚拟列：https://dev.mysql.com/doc/refman/5.7/en/create-table-generated-columns.html

以上，如有错谬，请不吝指正。

原创作品，如需转载，请标明出处，谢谢~