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 table test_user\G ;
*************************** 1. row ***************************
Table: test_user
Create Table: CREATE TABLE `test_user` (
`uid` int(11) NOT NULL AUTO_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=utf8
1 row in set (0.00 sec) ERROR:
No query specified
使用python插入测试数据
#!/usr/bin/python
import string
import random
import MySQLdb
import time conn = MySQLdb.connect(host='IPAddr',
port=3306,
user='zeno',
passwd='zeno',
db='zeno') def insert(para):
i = 11
while True:
r_name = ''.join(random.choice(string.ascii_uppercase + string.digits) for _ in range(random.randint(10, 30)))
print r_name cursor = conn.cursor()
cursor.execute("INSERT INTO test_user (name,add_time) VALUES ('%s', now())" % str(r_name))
i = i + 1
conn.commit()
#time.sleep(0.1)
print i 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: 10
Row_format: Dynamic
Rows: 6002441
Avg_row_length: 51
Data_length: 310165504
Max_data_length: 0
Index_length: 0
Data_free: 5242880
Auto_increment: 6037060
Create_time: 2017-11-23 16:25:15
Update_time: 2017-11-23 16:23:29
Check_time: NULL
Collation: utf8_general_ci
Checksum: NULL
Create_options:
Comment:
1 row in set (0.00 sec) 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 (0.00 sec) 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 (3.84 sec) 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 (0.44 sec)
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 on test_user(r_name) ;
Query OK, 0 rows affected (41.90 sec)
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 (0.00 sec)
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。
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