使用mysql5.7新特性解决前通配符查询性能问题

　　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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