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_userG ; *************************** 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。
原创作品，如需转载，请标明出处，谢谢~