文章目录
Pre
Table Demo
CREATE TABLE `employees` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`name` varchar(24) NOT NULL DEFAULT '' COMMENT '姓名',
`age` int(11) NOT NULL DEFAULT '0' COMMENT '年龄',
`position` varchar(20) NOT NULL DEFAULT '' COMMENT '职位',
`hire_time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '入职时间',
PRIMARY KEY (`id`),
KEY `idx_name_age_position` (`name`,`age`,`position`) USING BTREE
) ENGINE=InnoDB AUTO_INCREMENT=4 DEFAULT CHARSET=utf8 COMMENT='员工记录表';
INSERT INTO employees(name,age,position,hire_time) VALUES('LiLei',22,'manager',NOW());
INSERT INTO employees(name,age,position,hire_time) VALUES('HanMeimei', 23,'dev',NOW());
INSERT INTO employees(name,age,position,hire_time) VALUES('Lucy',23,'dev',NOW());
DB Version
mysql> select version();
+------------+
| version() |
+------------+
| 5.7.29-log |
+------------+
1 row in set (0.00 sec)
mysql>
Case
KEY `idx_name_age_position` (`name`,`age`,`position`) USING BTREE
联合索引
全值匹配
mysql> explain select * from employees where name = 'LiLei';
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
| 1 | SIMPLE | employees | NULL | ref | idx_name_age_position | idx_name_age_position | 74 | const | 1 | 100.00 | NULL |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
mysql>
算算这个ke_len
key_len ： 显示了mysql在索引里使用的字节数，通过这个值可以算出具体使用了索引中的哪些列。
【字符串】
- char(n)：n字节长度
- varchar(n)：如果是utf-8，则长度 3n + 2 字节，加的2字节用来存储字符串长度
【数值类型】
- tinyint：1字节
- smallint：2字节
- int：4字节
- bigint：8字节
【时间类型】
- date：3字节
- timestamp：4字节
- datetime：8字节
如果字段允许为 NULL，需要1字节记录是否为 NULL
索引最大长度是768字节，当字符串过长时，mysql会做一个类似左前缀索引的处理，将前半部分的字符提取出来做索引
name varchar(24) —> 3 * 24 + 2 = 74 , 用了联合索引中的name .
mysql> explain select * from employees where name = 'LiLei' and age= 22;
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------+------+----------+-------+
| 1 | SIMPLE | employees | NULL | ref | idx_name_age_position | idx_name_age_position | 78 | const,const | 1 | 100.00 | NULL |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
key_len 变成了 78 ？
第二个是int , int 占 4个字节 ， 74 + 4 = 78 ，这个SQL用了联合索引中的 name + age
mysql> explain select * from employees where name = 'LiLei' and age= 22 and position = 'manager';
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
| 1 | SIMPLE | employees | NULL | ref | idx_name_age_position | idx_name_age_position | 140 | const,const,const | 1 | 100.00 | NULL |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
mysql>
key_len = 74 + 4 + 72 = 140
那我们跳过age 呢 ？
mysql> explain select * from employees where name = 'LiLei' and position = 'manager';
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-----------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-----------------------+
| 1 | SIMPLE | employees | NULL | ref | idx_name_age_position | idx_name_age_position | 74 | const | 1 | 33.33 | Using index condition |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-----------------------+
1 row in set, 1 warning (0.00 sec)
mysql>
用了联合所以中的 name
最左前缀
如果索引了多列，要遵守最左前缀法则 , 指的是查询从索引的最左前列开始并且不跳过索引中的列。
mysql> explain select * from employees where name = 'LiLei' and age= 22;
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------+------+----------+-------+
| 1 | SIMPLE | employees | NULL | ref | idx_name_age_position | idx_name_age_position | 78 | const,const | 1 | 100.00 | NULL |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
mysql>
符合最左前缀。
不符合 最左前缀
user where : 使用 where 语句来处理结果，并且查询的列未被索引覆盖
不符合 最左前缀
user where : 使用 where 语句来处理结果，并且查询的列未被索引覆盖
禁止索引列上做任何操作（计算、函数、（自动or手动）类型转换）
会导致索引失效而转向全表扫描
mysql> explain select * from employees where name = 'LiLei';
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
| 1 | SIMPLE | employees | NULL | ref | idx_name_age_position | idx_name_age_position | 74 | const | 1 | 100.00 | NULL |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
mysql>
mysql> explain select * from employees where left(name,2) = 'LiLei';
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| 1 | SIMPLE | employees | NULL | ALL | NULL | NULL | NULL | NULL | 3 | 100.00 | Using where |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)
mysql>
结合索引那个B+Tree , 特征 排好序
left 函数，MYSQL并没有做优化 ，left(name,2) 在那棵B+Tree上并没有，肯定不会走索引。
看看函数的操作
加个索引
alter table employees add index idx_hire_time(hire_time) using btree;
查看目前的索引
mysql> show index from employees ;
+-----------+------------+-----------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment |
+-----------+------------+-----------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
| employees | 0 | PRIMARY | 1 | id | A | 2 | NULL | NULL | | BTREE | | |
| employees | 1 | idx_name_age_position | 1 | name | A | 2 | NULL | NULL | | BTREE | | |
| employees | 1 | idx_name_age_position | 2 | age | A | 2 | NULL | NULL | | BTREE | | |
| employees | 1 | idx_name_age_position | 3 | position | A | 2 | NULL | NULL | | BTREE | | |
| employees | 1 | idx_hire_time | 1 | hire_time | A | 1 | NULL | NULL | | BTREE | | |
+-----------+------------+-----------------------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+---------------+
5 rows in set (0.00 sec)
mysql>
在索引列上使用函数
mysql> explain select * from employees where date(hire_time)='2018-09-30';
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| 1 | SIMPLE | employees | NULL | ALL | NULL | NULL | NULL | NULL | 3 | 100.00 | Using where |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)
mysql>
变幻一下
mysql> explain select * from employees where hire_time>='2018-09-30 00:00:00' and hire_time<='2018-09-30 23:59:59';
+----+-------------+-----------+------------+-------+---------------+---------------+---------+------+------+----------+-----------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+-------+---------------+---------------+---------+------+------+----------+-----------------------+
| 1 | SIMPLE | employees | NULL | range | idx_hire_time | idx_hire_time | 4 | NULL | 1 | 100.00 | Using index condition |
+----+-------------+-----------+------------+-------+---------------+---------------+---------+------+------+----------+-----------------------+
1 row in set, 1 warning (0.00 sec)
mysql>
好了 ，实验完毕
移除索引
alter table employees drop index idx_hire_time;
存储引擎不能使用索引中范围条件右边的列
比对一下
mysql> explain select * from employees where name = 'LiLei' and age= 22 and position = 'manager';
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
| 1 | SIMPLE | employees | NULL | ref | idx_name_age_position | idx_name_age_position | 140 | const,const,const | 1 | 100.00 | NULL |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
mysql>
key_len = 140 （74 + 4 + 78） 全部走了 idx_name_age_position (name,age,position)
mysql> explain select * from employees where name = 'LiLei' and age> 22 and position = 'manager';
+----+-------------+-----------+------------+-------+-----------------------+-----------------------+---------+------+------+----------+-----------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+-------+-----------------------+-----------------------+---------+------+------+----------+-----------------------+
| 1 | SIMPLE | employees | NULL | range | idx_name_age_position | idx_name_age_position | 78 | NULL | 1 | 33.33 | Using index condition |
+----+-------------+-----------+------------+-------+-----------------------+-----------------------+---------+------+------+----------+-----------------------+
1 row in set, 1 warning (0.00 sec)
mysql>
key_len = 78 （74 + 4 ） 走了 idx_name_age_position (name,age,position) 中的 name 和 age
为什么呢？
脑海中找到那个B+Tree
name 是相同的， 所以第二列 age 肯定是有序的， 而age这里取的是大于， age是大于， 第三列没办法保证有序。 如果age是等于，那可以，第三列有序。 上面这个图不是很合适，不要被误导了，放上去仅仅是为了让读者对B+树有个轮廓。
尽量使用覆盖索引（只访问索引的查询（索引列包含查询列）），减少 select * 语句
mysql> explain select * from employees where name = 'LiLei' and age= 22 and position = 'manager';
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
| 1 | SIMPLE | employees | NULL | ref | idx_name_age_position | idx_name_age_position | 140 | const,const,const | 1 | 100.00 | NULL |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
mysql> explain select name , age from employees where name = 'LiLei' and age= 22 and position = 'manager';
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------------+
| 1 | SIMPLE | employees | NULL | ref | idx_name_age_position | idx_name_age_position | 140 | const,const,const | 1 | 100.00 | Using index |
+----+-------------+-----------+------------+------+-----------------------+-----------------------+---------+-------------------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)
mysql>
看到第二个的 Extra ： Using Index 使用了覆盖索引
mysql在使用不等于（！=或者<>）的时候无法使用索引会导致全表扫描
mysql>
mysql> explain select * from employees where name != 'LiLei' ;
+----+-------------+-----------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
| 1 | SIMPLE | employees | NULL | ALL | idx_name_age_position | NULL | NULL | NULL | 3 | 66.67 | Using where |
+----+-------------+-----------+------------+------+-----------------------+------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)
is null,is not null 一般情况下也无法使用索引
mysql> explain select * from employees where name is null ;
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------+
| 1 | SIMPLE | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | NULL | Impossible WHERE |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+------------------+
1 row in set, 1 warning (0.00 sec)
mysql>
null 值在树中会放到一起和其他节点搞个双向指针
like以通配符开头（’$abc…’）mysql索引失效会变成全表扫描操作
mysql> explain select * from employees where name like '%Lei';
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| 1 | SIMPLE | employees | NULL | ALL | NULL | NULL | NULL | NULL | 3 | 33.33 | Using where |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)
%在前
还是要回想那个索引B+Tree , % 在前面 意味着前面可能还有其他的字符串， 那在树中的有序性没法保证啊
mysql> explain select * from employees where name like 'Lei%';
+----+-------------+-----------+------------+-------+-----------------------+-----------------------+---------+------+------+----------+-----------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+-------+-----------------------+-----------------------+---------+------+------+----------+-----------------------+
| 1 | SIMPLE | employees | NULL | range | idx_name_age_position | idx_name_age_position | 74 | NULL | 1 | 100.00 | Using index condition |
+----+-------------+-----------+------------+-------+-----------------------+-----------------------+---------+------+------+----------+-----------------------+
1 row in set, 1 warning (0.00 sec)
mysql>
继续回想那个索引B+Tree , % 不在前面 意味着%前面的字符串固定， 那在树中的就是有序的，当然可以走索引
key_len = 74 ,可以推导出 走了 联合索引中的name
like 的优化
【问题：解决like’%字符串%'索引不被使用的方法？】
A： 使用覆盖索引，查询字段必须是建立覆盖索引字段
mysql> explain select * from employees where name like '%Lei';
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| 1 | SIMPLE | employees | NULL | ALL | NULL | NULL | NULL | NULL | 3 | 33.33 | Using where |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)
mysql>
mysql>
mysql> explain select name ,age position from employees where name like '%Lei';
+----+-------------+-----------+------------+-------+---------------+-----------------------+---------+------+------+----------+--------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+-------+---------------+-----------------------+---------+------+------+----------+--------------------------+
| 1 | SIMPLE | employees | NULL | index | NULL | idx_name_age_position | 140 | NULL | 3 | 33.33 | Using where; Using index |
+----+-------------+-----------+------------+-------+---------------+-----------------------+---------+------+------+----------+--------------------------+
1 row in set, 1 warning (0.00 sec)
mysql>
不敢说好太多， index 总比 all 好吧 。
B： 如果不能使用覆盖索引则可能需要借助搜索引擎 ，Es等
字符串不加单引号索引失效
少用or或in
用它查询时，mysql不一定使用索引，mysql内部优化器会根据检索比例、表大小等多个因素整体评 估是否使用索引，详见范围查询优化
范围查询优化
增加索引
alter table employees add index idx_age(age) using BTREE;
mysql> explain select * from employees where age>=1 and age<=2000;
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
| 1 | SIMPLE | employees | NULL | ALL | idx_age | NULL | NULL | NULL | 3 | 100.00 | Using where |
+----+-------------+-----------+------------+------+---------------+------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)
mysql>
没走索引原因：mysql内部优化器会根据检索比例、表大小等多个因素整体评估是否使用索引。比如这个例子，可能是由于单次数据量查询过大导致优化器最终选择不走索引
优化方法： 可以将大的范围拆分成多个小范围
mysql> explain select * from employees where age>=1 and age<=10;
+----+-------------+-----------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+
| 1 | SIMPLE | employees | NULL | range | idx_age | idx_age | 4 | NULL | 1 | 100.00 | Using index condition |
+----+-------------+-----------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+
1 row in set, 1 warning (0.00 sec)
mysql> explain select * from employees where age>=11 and age<=20;
+----+-------------+-----------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-----------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+
| 1 | SIMPLE | employees | NULL | range | idx_age | idx_age | 4 | NULL | 1 | 100.00 | Using index condition |
+----+-------------+-----------+------------+-------+---------------+---------+---------+------+------+----------+-----------------------+
1 row in set, 1 warning (0.00 sec)
mysql>
还原索引
alter table employees drop index idx_age ;
索引总结
like KK%相当于=常量，%KK和%KK% 相当于范围