MySQL优化之执行计划
研究SQL性能问题,其实本质就是优化索引,而优化索引,一个非常重要的工具就是执行计划(explain),它可以模拟SQL优化器执行SQL语句,从而让开发人员知道自己编写的SQL的运行情况。
执行计划的语法非常简单,就是在要执行的SQL语句前加上explain
即可。
以我们在上一篇文章中创建的student
表为例:
mysql> explain select * from student where id = 1;
+----+-------------+---------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+---------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
| 1 | SIMPLE | student | NULL | const | PRIMARY | PRIMARY | 4 | const | 1 | 100.00 | NULL |
+----+-------------+---------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
为了更好的讲明白执行计划,我们将新建三张表,一张为employee
表,一张为salary
表,另一张为department
表。其表结构以及数据如下:
employee表
e_id | e_name | d_id |
---|---|---|
1 | zhang | 1 |
2 | wang | 1 |
3 | song | 3 |
4 | liu | 2 |
5 | wang | 2 |
salary表
s_id | s_salary |
---|---|
1 | 11000 |
2 | 8000 |
3 | 6500 |
4 | 5000 |
5 | 7200 |
department 表
d_id | d_name |
---|---|
1 | tech |
2 | HR |
3 | PD |
三张表建表语句如下:
create table employee(
e_id int(4) auto_increment,
e_name varchar(20) default NULL,
d_id int(4),
primary key(e_id)
);
create unique index e_idx1 on employee(e_id);
create index e_idx2 on employee(e_name, d_id);
create index e_idx3 on employee(e_name);
create table salary(
s_id int(4),
s_salary decimal(15,2)
);
create unique index s_idx1 on salary(s_id);
create index s_idx2 on salary(s_salary);
create table department(
d_id int(4),
d_name char(10) not NULL
);
create unique index d_idx1 on department(d_id);
create index d_idx2 on department(d_name);
insert into employee values(1, "zhang", 1);
insert into employee values(2, "wang", 1);
insert into employee values(3, "song", 3);
insert into employee values(4, "liu", 2);
insert into employee values(5, "wang", 2);
insert into salary values(1, 11000);
insert into salary values(2, 8000);
insert into salary values(3, 65000);
insert into salary values(4, 5000);
insert into salary values(5, 7200);
insert into department values(1, "tech");
insert into department values(2, "HR");
insert into department values(3, "PD");
看执行计划,其实就是看explain所展示出来的列的含义。下面我们来逐一分析。
id
id用来表示SQL语句查询的顺序。它遵循三条原则:
id | 值情况 | 执行顺序 | 常见场景 |
---|---|---|---|
1 | id相同 | 按顺序执行,从上往下 | 关联表查询 |
2 | id不同 | id值越大,执行优先级越高 | 子查询 |
3 | NULL | 表示为一个结果集,不需要用它来查询 | union语句 |
为了说明id的情况,不妨做一个如下查询:查询HR部门,工资为5000的员工的名字。
我们很容易就能写出SQL语句:
mysql> select e.e_name from employee e, salary s, department d where e.e_id = s.s_id and e.d_id = d.d_id and s.s_salary = 5000 and d.d_name = "HR";
+--------+
| e_name |
+--------+
| liu |
+--------+
1 row in set (0.01 sec)
以上SQL语句没有问题,但是我们现在要研究的并不是这个语句本身,而是执行计划,所以加上执行计划再执行一遍:
mysql> explain select e.e_name from employee e, salary s, department d where e.e_id = s.s_id and e.d_id = d.d_id and s.s_salary = 5000 and d.d_name = "HR";
+----+-------------+-------+------------+--------+----------------+---------+---------+---------------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+--------+----------------+---------+---------+---------------+------+----------+-------------+
| 1 | SIMPLE | s | NULL | ref | s_idx1,s_idx2 | s_idx2 | 8 | const | 1 | 100.00 | Using where |
| 1 | SIMPLE | e | NULL | eq_ref | PRIMARY,e_idx1 | PRIMARY | 4 | testDB.s.s_id | 1 | 100.00 | Using where |
| 1 | SIMPLE | d | NULL | ref | d_idx1,d_idx2 | d_idx1 | 5 | testDB.e.d_id | 1 | 33.33 | Using where |
+----+-------------+-------+------------+--------+----------------+---------+---------+---------------+------+----------+-------------+
3 rows in set, 1 warning (0.00 sec)
从以上结果可以看到,三张表的id都为1,所以这三张表是按照从上往下的顺序执行的,即 s->e->d的顺序。不难看出,这个顺序和我们编写SQL的表的顺序是无关的。
注意:当id相同时,左连接和右连接可以破坏SQL的执行顺序。
如果id相同,执行顺序靠什么控制的?
答:如果id相同,和表中的数据条数有关。
如果我要查PD部门所有人的薪水情况,这次改用子查询的方式:
mysql> select s.* from salary s where s.s_id = (select e.e_id from employee e where e.d_id = (select d.d_id from department d where d.d_name = "PD"));
+------+----------+
| s_id | s_salary |
+------+----------+
| 3 | 65000.00 |
+------+----------+
1 row in set (0.00 sec)
其执行计划如下所示:
mysql> explain select s.* from salary s where s.s_id = (select e.e_id from employee e where e.d_id = (select d.d_id from department d where d.d_name = "PD"));
+----+-------------+-------+------------+-------+---------------+--------+---------+-------+------+----------+--------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+-------+---------------+--------+---------+-------+------+----------+--------------------------+
| 1 | PRIMARY | s | NULL | const | s_idx1 | s_idx1 | 5 | const | 1 | 100.00 | NULL |
| 2 | SUBQUERY | e | NULL | index | NULL | e_idx2 | 68 | NULL | 5 | 20.00 | Using where; Using index |
| 3 | SUBQUERY | d | NULL | ref | d_idx2 | d_idx2 | 30 | const | 1 | 100.00 | NULL |
+----+-------------+-------+------------+-------+---------------+--------+---------+-------+------+----------+--------------------------+
3 rows in set, 1 warning (0.00 sec)
可以看到,id为1,2,3,分别对应的表为s,e,d,根据id越大,执行优先级越高的原则,执行顺序应该是d->e->s。至于原因,其实很好理解,按照常规思维,要查salary表,首先要从查employee表查出员工id,而要查employee表,则要先从department表查出部门id,因此,查询顺序就是先查department,再查employee,最后查salary。
接下来演示一个union查询的例子,如:查询employee表中id为1和5的员工信息:
mysql> select * from employee where e_id = 1 union select * from employee where e_id = 5;
+------+--------+------+
| e_id | e_name | d_id |
+------+--------+------+
| 1 | zhang | 1 |
| 5 | wang | 2 |
+------+--------+------+
2 rows in set (0.01 sec)
其执行计划如下:
mysql> explain select * from employee where e_id = 1 union select * from employee where e_id = 5;
+----+--------------+------------+------------+-------+----------------+---------+---------+-------+------+----------+-----------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+--------------+------------+------------+-------+----------------+---------+---------+-------+------+----------+-----------------+
| 1 | PRIMARY | employee | NULL | const | PRIMARY,e_idx1 | PRIMARY | 4 | const | 1 | 100.00 | NULL |
| 2 | UNION | employee | NULL | const | PRIMARY,e_idx1 | PRIMARY | 4 | const | 1 | 100.00 | NULL |
| NULL | UNION RESULT | | NULL | ALL | NULL | NULL | NULL | NULL | NULL | NULL | Using temporary |
+----+--------------+------------+------------+-------+----------------+---------+---------+-------+------+----------+-----------------+
3 rows in set, 1 warning (0.01 sec)
上例很好的说明了这个问题,从id的值,很直观就能看出SQL执行的顺序,先执行union的表,再执行前面的表,结果集通过UNION RESULT
显示出来。
select_type
select_type
按字面意思,就是查询类型。常见的查询类型有以下几种:
id | select_type | 描述 | 常见场景 |
---|---|---|---|
1 | SIMPLE | 不包含任何子查询或union查询 | 简单的单表查询 |
2 | PRIMARY | 包含子查询的最外层就是PRIMARY,意思为主查询语句 | 子查询 |
3 | SUBQUERY | select 或where 中包含的子查询语句 |
子查询 |
4 | DERIVED | from语句中包含的查询(衍生查询) | 临时表 |
5 | UNION | union 查询的后一条查询语句 |
union查询 |
6 | UNION RESULT | union查询的的结果集 | union查询 |
SIMPLE
这个比较好举例,如下面的SQL语句,查询employee表中id为1的员工信息:
mysql> explain select * from employee where e_id = 1;
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
| 1 | SIMPLE | employee | NULL | const | PRIMARY,e_idx1 | PRIMARY | 4 | const | 1 | 100.00 | NULL |
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
出现SIMPLE的关键是,只能有当前一张表单表查询,且不涉及任何子查询、union查询、临时表查询。
PRIMARY 和 SUBQUERY
这两个都是子查询中会出现的,仍然以上面那条子查询的SQL拿来分析:
mysql> explain select s.* from salary s where s.s_id = (select e.e_id from employee e where e.d_id = (select d.d_id from department d where d.d_name = "PD"));
+----+-------------+-------+------------+-------+---------------+--------+---------+-------+------+----------+--------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+-------+---------------+--------+---------+-------+------+----------+--------------------------+
| 1 | PRIMARY | s | NULL | const | s_idx1 | s_idx1 | 5 | const | 1 | 100.00 | NULL |
| 2 | SUBQUERY | e | NULL | index | NULL | e_idx2 | 68 | NULL | 5 | 20.00 | Using where; Using index |
| 3 | SUBQUERY | d | NULL | ref | d_idx2 | d_idx2 | 30 | const | 1 | 100.00 | NULL |
+----+-------------+-------+------------+-------+---------------+--------+---------+-------+------+----------+--------------------------+
3 rows in set, 1 warning (0.00 sec)
e表和d表都是SUBQUERY
,因为它们是子查询语句,而s表则是PRIMARY
,则是因为s表示select要输出的表,所以属于主查询。
DERIVED
DERIVED
一般出现在临时表中。一般分两种情况:
- 当from子查询的衍生查询只有一张表时,该临时表就是
DERIVED
; - 当from子查询的衍生查询中,有union查询时,一般union的第一个查询为
DERIVED
.
如下例所示:
mysql> explain select t.* from (select e_name from employee where e_id = 1 union select e_name from employee where e_id = 5) t;
+----+--------------+------------+------------+-------+----------------+---------+---------+-------+------+----------+-----------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+--------------+------------+------------+-------+----------------+---------+---------+-------+------+----------+-----------------+
| 1 | PRIMARY | | NULL | ALL | NULL | NULL | NULL | NULL | 2 | 100.00 | NULL |
| 2 | DERIVED | employee | NULL | const | PRIMARY,e_idx1 | PRIMARY | 4 | const | 1 | 100.00 | NULL |
| 3 | UNION | employee | NULL | const | PRIMARY,e_idx1 | PRIMARY | 4 | const | 1 | 100.00 | NULL |
| NULL | UNION RESULT | | NULL | ALL | NULL | NULL | NULL | NULL | NULL | NULL | Using temporary |
+----+--------------+------------+------------+-------+----------------+---------+---------+-------+------+----------+-----------------+
4 rows in set, 1 warning (0.00 sec)
UNION 和 UNION RESULT
仍然可以拿上面union查询的例子来分析:
mysql> explain select * from employee where e_id = 1 union select * from employee where e_id = 5;
+----+--------------+------------+------------+-------+----------------+---------+---------+-------+------+----------+-----------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+--------------+------------+------------+-------+----------------+---------+---------+-------+------+----------+-----------------+
| 1 | PRIMARY | employee | NULL | const | PRIMARY,e_idx1 | PRIMARY | 4 | const | 1 | 100.00 | NULL |
| 2 | UNION | employee | NULL | const | PRIMARY,e_idx1 | PRIMARY | 4 | const | 1 | 100.00 | NULL |
| NULL | UNION RESULT | | NULL | ALL | NULL | NULL | NULL | NULL | NULL | NULL | Using temporary |
+----+--------------+------------+------------+-------+----------------+---------+---------+-------+------+----------+-----------------+
3 rows in set, 1 warning (0.01 sec)
前面第一部分查询:select * from employee where e_id = 1
,它给的是PRIMARY
,第二张表的查询select * from employee where e_id = 5
就是UNION
。而它们的结果集则是UNION RESULT
。
table
table就是用到的表名,当有别名的时候,显示的是别名。
id | table | 描述 | 常见场景 |
---|---|---|---|
1 | 原表名 | 当表没有别名时,显示的就是表名本身 | 表没有别名 |
2 | 别名 | 当表有别名时,显示的就是别名 | 表定义有别名 |
3 | union |
UNION查询时id为m和n的联表查询结果集的显示结果,m和n为id值 | UNION查询 |
在前例中可以很明确的看到这点的演示。
如显示原表名:
mysql> explain select * from employee where e_id = 1;
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
| 1 | SIMPLE | employee | NULL | const | PRIMARY,e_idx1 | PRIMARY | 4 | const | 1 | 100.00 | NULL |
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
显示别名:
mysql> explain select e.* from employee e where e.e_id = 1;
+----+-------------+-------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+-------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
| 1 | SIMPLE | e | NULL | const | PRIMARY,e_idx1 | PRIMARY | 4 | const | 1 | 100.00 | NULL |
+----+-------------+-------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
从以上两个例子可以很明显的看出来,SQL语句一模一样,第二个语句只是加了一个别名,所以table
列显示的就变成了别名。
partitions
partions指的是查询涉及到的分区,如果不涉及分区,则显示为NULL;如果有分区,则显示的是分区情况。
要讲这个,需要先说一下表分区的概念。表分区指的是在物理上不是一块内存,但是在逻辑上仍然是一张表。这样的好处是可以合理利用硬盘空间,从而提高效率。
查询mysql服务是否支持表分区:
mysql> show plugins;
创建分区表:
mysql> create table tb_partition(
-> id int(4) auto_increment,
-> name varchar(20),
-> passwd char(20),
-> primary key(id)
-> )PARTITION BY HASH(id)
-> PARTITIONS 4
-> ;
Query OK, 0 rows affected (0.59 sec)
注意,按Hash分区时,分区的字段一定要是int型,且为主键,如果不是,则要将其转为主键才能分区成功。
关于表分区的更多内容,请参考这篇文章:MySQL分区表
partitions字段可以有以下取值:
id | partitions | 描述 |
---|---|---|
1 | NULL | 没有表分区,或有表分区但是查询数据不存在时 |
2 | 所有表分区均显示出来 | 查询所有数据,或所查询出来的数据覆盖到了所有的分区 |
3 | 显示具体表分区 | 表里有数据,显示为当前数据所在的表分区 |
示例1:没有表分区,显示为NULL。
mysql> explain select * from employee where e_id = 1;
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
| 1 | SIMPLE | employee | NULL | const | PRIMARY,e_idx1 | PRIMARY | 4 | const | 1 | 100.00 | NULL |
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
示例2:有表分区,但是查询的结果为空。
mysql> explain select * from tb_partition where id = 10;
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+--------------------------------+
| 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 | no matching row in const table |
+----+-------------+-------+------------+------+---------------+------+---------+------+------+----------+--------------------------------+
1 row in set, 1 warning (0.00 sec)
注意此时,它所展示的table
也为NULL,这点在前文没有讲到,说明当使用到分区表,且查询数据不存在时,table取值为NULL。
示例3:查询表中所有数据,显示所有表分区。
mysql> explain select * from tb_partition;
+----+-------------+--------------+-------------+------+---------------+------+---------+------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+--------------+-------------+------+---------------+------+---------+------+------+----------+-------+
| 1 | SIMPLE | tb_partition | p0,p1,p2,p3 | ALL | NULL | NULL | NULL | NULL | 4 | 100.00 | NULL |
+----+-------------+--------------+-------------+------+---------------+------+---------+------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
示例4:查询结果存在,显示数据所在的分区。
先插入几条数据:
insert into tb_partition values(1,"zhangsan", "123456");
insert into tb_partition values(2,"lisi", "123123");
insert into tb_partition values(3,"mayun", "123321");
insert into tb_partition values(4,"trump", "654321");
再执行查询语句:
mysql> explain select * from tb_partition where id = 1;
+----+-------------+--------------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+--------------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
| 1 | SIMPLE | tb_partition | p1 | const | PRIMARY | PRIMARY | 4 | const | 1 | 100.00 | NULL |
+----+-------------+--------------+------------+-------+---------------+---------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
此时显示的分区是p1,也就是id = 1
那条数据所在的分区。如果查询的结果不止一条,则显示所有数据的分区,这点应该不难想象,就不示例了。
type
type在SQL优化中是一个很重要的概念,SQL语句好不好,和该字段展示的值有很大关系。type的值有很多,常见的有以下这几种:
id | type | 描述 |
---|---|---|
1 | SYSTEM | 连接类型的特例,表中只有一条数据,相当于系统表 |
2 | CONST | 根据主键或唯一索引的主键查询查询结果只有1条记录 |
3 | eq_ref | 唯一索引扫描,对于每个索引键,只有一条记录与之对应 |
4 | ref | 针对非唯一或非主键索引,查询的结果可以有多条或0条 |
5 | range | 使用索引范围查询 |
6 | index | 遍历索引,只查询索引列,无须回表查询 |
7 | ALL | 全局扫描,当表没有索引或没用到索引时会出现,基本上等于没有任何优化 |
以上所列的顺序,基本上就是性能效率从高到低的排列顺序,即SYSTEM>CONST>eq_ref>ref>range>index>ALL。
需要注意的是,type字段针对的是索引列,当表中不存在索引时,此时不管表中有多少数据,type都是ALL。实际的优化过程中,system和const级别都是可遇不可求的,能够达到ref级别,就说明已经达到了优化的效果。
system
这种情况一般很难达到,只有当查询系统表,衍生表只有一条数据的主查询时能够达到这个级别。
const
一般根据主键去做的单表查询,type都是这个级别。
mysql> explain select * from employee where e_id = 1;
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
| 1 | SIMPLE | employee | NULL | const | PRIMARY,e_idx1 | PRIMARY | 4 | const | 1 | 100.00 | NULL |
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
需要注意的是,当使用复合索引作为唯一索引的时候,必须复合索引中所有的列都用到,才能是const。
eq_ref
唯一性索引,对于每个索引键的查询,返回匹配唯一行数据(有且仅有1个,不能多个,不能0个),常见于唯一索引和主键索引。
mysql> explain select e.e_id from employee e, salary s where e.e_id = s.s_id;
+----+-------------+-------+------------+-------+----------------+--------+---------+---------------+------+----------+----------
---+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra
|
+----+-------------+-------+------------+-------+----------------+--------+---------+---------------+------+----------+----------
---+
| 1 | SIMPLE | e | NULL | index | PRIMARY,e_idx1 | e_idx1 | 4 | NULL | 5 | 100.00 | Using ind
ex |
| 1 | SIMPLE | s | NULL | ref | s_idx1 | s_idx1 | 5 | testDB.e.e_id | 1 | 100.00 | Using ind
ex |
+----+-------------+-------+------------+-------+----------------+--------+---------+---------------+------+----------+----------
---+
疑问:为啥出来的不是eq_ref?
ref
ref通常针对普通索引,通过索引查询出多条数据或0条数据。
mysql> explain select * from employee where e_name = "zhangsan";
+----+-------------+----------+------------+------+---------------+--------+---------+-------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+----------+------------+------+---------------+--------+---------+-------+------+----------+-------------+
| 1 | SIMPLE | employee | NULL | ref | e_idx2,e_idx3 | e_idx2 | 63 | const | 1 | 100.00 | Using index |
+----+-------------+----------+------------+------+---------------+--------+---------+-------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)
以上是查询有结果的情况,接下来看查询结果为0条的情况:
mysql> explain select * from employee where e_name = "none";
+----+-------------+----------+------------+------+---------------+--------+---------+-------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+----------+------------+------+---------------+--------+---------+-------+------+----------+-------------+
| 1 | SIMPLE | employee | NULL | ref | e_idx2,e_idx3 | e_idx2 | 63 | const | 1 | 100.00 | Using index |
+----+-------------+----------+------------+------+---------------+--------+---------+-------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)
range
根据索引查询的条件为一个范围,如>,<,between ... and, like等。
我们仍然看以下几个示例:
mysql> explain select * from employee where e_id > 1;
+----+-------------+----------+------------+-------+----------------+---------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+----------+------------+-------+----------------+---------+---------+------+------+----------+-------------+
| 1 | SIMPLE | employee | NULL | range | PRIMARY,e_idx1 | PRIMARY | 4 | NULL | 4 | 100.00 | Using where |
+----+-------------+----------+------------+-------+----------------+---------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)
mysql> explain select * from employee where e_id between 1 and 5;
+----+-------------+----------+------------+-------+----------------+---------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+----------+------------+-------+----------------+---------+---------+------+------+----------+-------------+
| 1 | SIMPLE | employee | NULL | range | PRIMARY,e_idx1 | PRIMARY | 4 | NULL | 5 | 100.00 | Using where |
+----+-------------+----------+------------+-------+----------------+---------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.01 sec)
mysql> explain select * from employee where e_name like "zh%";
+----+-------------+----------+------------+-------+---------------+--------+---------+------+------+----------+--------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra
|
+----+-------------+----------+------------+-------+---------------+--------+---------+------+------+----------+--------------------------+
| 1 | SIMPLE | employee | NULL | range | e_idx2,e_idx3 | e_idx2 | 63 | NULL | 1 | 100.00 | Using where; Using index |
+----+-------------+----------+------------+-------+---------------+--------+---------+------+------+----------+--------------------------+
1 row in set, 1 warning (0.02 sec)
需要注意的是,不等于号<>
(或 !=
),in 语法在实际测试中使用到的是index级别的索引,而非range,说明<> 和in实际上使索引级别下降了,因此,在上一篇文章中,在索引注意事项中,才会有尽量避免使用in和not in的说明。
同样,like 的百分号%最好跟在后面,而不是前面,也是一样的道理,在实际测试中,当前面有%时,索引级别也会降为index。
mysql> explain select * from employee where e_id <> 3;
+----+-------------+----------+------------+-------+----------------+--------+---------+------+------+----------+----------------
----------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra
|
+----+-------------+----------+------------+-------+----------------+--------+---------+------+------+----------+----------------
----------+
| 1 | SIMPLE | employee | NULL | index | PRIMARY,e_idx1 | e_idx2 | 68 | NULL | 5 | 80.00 | Using where; Us
ing index |
+----+-------------+----------+------------+-------+----------------+--------+---------+------+------+----------+----------------
----------+
1 row in set, 1 warning (0.00 sec)
mysql> explain select * from employee where e_id in (1,2,3);
+----+-------------+----------+------------+-------+----------------+--------+---------+------+------+----------+--------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra
|
+----+-------------+----------+------------+-------+----------------+--------+---------+------+------+----------+--------------------------+
| 1 | SIMPLE | employee | NULL | index | PRIMARY,e_idx1 | e_idx2 | 68 | NULL | 5 | 60.00 | Using where; Using index |
+----+-------------+----------+------------+-------+----------------+--------+---------+------+------+----------+--------------------------+
1 row in set, 1 warning (0.00 sec)
mysql> explain select * from employee where e_name like "%san%";
+----+-------------+----------+------------+-------+---------------+--------+---------+------+------+----------+--------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra
|
+----+-------------+----------+------------+-------+---------------+--------+---------+------+------+----------+--------------------------+
| 1 | SIMPLE | employee | NULL | index | NULL | e_idx2 | 68 | NULL | 5 | 20.00 | Using where; Using index |
+----+-------------+----------+------------+-------+---------------+--------+---------+------+------+----------+--------------------------+
1 row in set, 1 warning (0.00 sec)
index
index指的是索引扫描树,只要走到了索引,基本上都是这一级别,该级别仅仅比ALL高一点。
如下面这种情况:
mysql> explain select * from employee where d_id = 3;
+----+-------------+----------+------------+-------+---------------+--------+---------+------+------+----------+-----------------
---------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra
|
+----+-------------+----------+------------+-------+---------------+--------+---------+------+------+----------+-----------------
---------+
| 1 | SIMPLE | employee | NULL | index | NULL | e_idx2 | 68 | NULL | 5 | 20.00 | Using where; Usi
ng index |
+----+-------------+----------+------------+-------+---------------+--------+---------+------+------+----------+-----------------
---------+
1 row in set, 1 warning (0.00 sec)
ALL
ALL就是全表扫描,这是最差的一种情况,等于没有任何优化,一般当所查询的字段没有索引时,使用到的就是该级别。
如:
mysql> explain select * from salary;
+----+-------------+--------+------------+------+---------------+------+---------+------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+--------+------------+------+---------------+------+---------+------+------+----------+-------+
| 1 | SIMPLE | salary | NULL | ALL | NULL | NULL | NULL | NULL | 5 | 100.00 | NULL |
+----+-------------+--------+------------+------+---------------+------+---------+------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
possible_keys 和 key
possible key和key可以放在一起来讲。顾名思义,possible key就是可能用到的索引,而key则是实际用到的索引。这二者并不一定是相同的。举一个例子:
mysql> explain select * from employee where e_id = 1 and e_name = "zhang";
+----+-------------+----------+------------+-------+------------------------------+---------+---------+-------+------+----------+
-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered |
Extra |
+----+-------------+----------+------------+-------+------------------------------+---------+---------+-------+------+----------+
-------+
| 1 | SIMPLE | employee | NULL | const | PRIMARY,e_idx1,e_idx2,e_idx3 | PRIMARY | 4 | const | 1 | 100.00 |
NULL |
+----+-------------+----------+------------+-------+------------------------------+---------+---------+-------+------+----------+
-------+
可以看到,它列举出的可能走到的索引,包括PRIMARY,e_idx1,e_idx2,e_idx3,而实际上,只使用到了PRIMARY。
为什么会这样呢?我们先来看一下employee表的索引:
mysql> show index from employee;
+----------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+-----------
-+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type
| Comment | Index_comment |
+----------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+-----------
-+---------+---------------+
| employee | 0 | PRIMARY | 1 | e_id | A | 5 | NULL | NULL | | BTREE
| | |
| employee | 0 | e_idx1 | 1 | e_id | A | 5 | NULL | NULL | | BTREE
| | |
| employee | 1 | e_idx2 | 1 | e_name | A | 4 | NULL | NULL | YES | BTREE
| | |
| employee | 1 | e_idx2 | 2 | d_id | A | 5 | NULL | NULL | YES | BTREE
| | |
| employee | 1 | e_idx3 | 1 | e_name | A | 4 | NULL | NULL | YES | BTREE
| | |
+----------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+-----------
-+---------+---------------+
5 rows in set (0.00 sec)
可以看到,where条件中,e_id字段涉及到了PRIMARY和e_idx1两个索引,e_name涉及到了e_idx2和e_idx3两个索引,所以,由于这两个字段出现在了where条件中,理论上这四个索引都会出现。而事实上,因为根据PRIMARY索引查e_id就直接能查出结果,所以后面的索引自然就用不上了。
key_len
key_len代表的是索引字段的长度,其计算方法是:
key_len = 索引字段实际长度 + (可以为null)1 + (varchar)2
仍然以employee表为例加以说明。先看一下employee表的表结构:
mysql> desc employee;
+--------+-------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+--------+-------------+------+-----+---------+----------------+
| e_id | int(4) | NO | PRI | NULL | auto_increment |
| e_name | varchar(20) | YES | MUL | NULL | |
| d_id | int(4) | YES | | NULL | |
+--------+-------------+------+-----+---------+----------------+
3 rows in set (0.01 sec)
可以看出,e_id要求是非null的,而e_name和d_id都可以是null。
因此,我们查询以下sql语句的执行计划:
mysql> show index from employee;
+----------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+-----------
-+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type
| Comment | Index_comment |
+----------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+-----------
mysql> explain select * from employee where e_id = 1;
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
| 1 | SIMPLE | employee | NULL | const | PRIMARY,e_idx1 | PRIMARY | 4 | const | 1 | 100.00 | NULL |
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
mysql> explain select * from employee where e_name = "zhang";
+----+-------------+----------+------------+------+---------------+--------+---------+-------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+----------+------------+------+---------------+--------+---------+-------+------+----------+-------------+
| 1 | SIMPLE | employee | NULL | ref | e_idx2,e_idx3 | e_idx2 | 63 | const | 1 | 100.00 | Using index |
+----+-------------+----------+------------+------+---------------+--------+---------+-------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)
接下来看一个索引字段数据类型为char的例子:
mysql> show index from department;
+------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+---------
---+---------+---------------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_ty
pe | Comment | Index_comment |
+------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+---------
---+---------+---------------+
| department | 0 | d_idx1 | 1 | d_id | A | 3 | NULL | NULL | YES | BTREE
| | |
| department | 1 | d_idx2 | 1 | d_name | A | 3 | NULL | NULL | | BTREE
| | |
+------------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+---------
---+---------+---------------+
2 rows in set (0.00 sec)
mysql> desc department;
+--------+----------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+--------+----------+------+-----+---------+-------+
| d_id | int(4) | YES | UNI | NULL | |
| d_name | char(10) | NO | MUL | NULL | |
+--------+----------+------+-----+---------+-------+
2 rows in set (0.00 sec)
查询SQL如下:
mysql> explain select * from department where d_name = "HR";
+----+-------------+------------+------------+------+---------------+--------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+------------+------------+------+---------------+--------+---------+-------+------+----------+-------+
| 1 | SIMPLE | department | NULL | ref | d_idx2 | d_idx2 | 30 | const | 1 | 100.00 | NULL |
+----+-------------+------------+------------+------+---------------+--------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
由于d_name字段要求not null,非变长,所以只需要计算字符长度即可,即:key_len = 20*3 = 60.
观察key_len,通常可以用于判断表走到了哪个索引,尤其对于复合索引,可以非常直观的看出其是否走了复合索引的全字段。
为了说明该问题,我们重新建一张表test01:
mysql> create table test01(
-> id int(4),
-> name varchar(20),
-> passwd char(20),
-> inf char(50));
Query OK, 0 rows affected (0.19 sec)
--创建复合索引
mysql> create index t_idx1 on test01(id, name, passwd);
Query OK, 0 rows affected (0.16 sec)
Records: 0 Duplicates: 0 Warnings: 0
--插入1条数据
mysql> insert into test01 values(1,"zz", "123456", "asdfgh");
Query OK, 1 row affected (0.04 sec)
通过观察,我们知道,如果走到该索引的所有字段,该索引长度应为: (4 + 1) + (20 * 3 + 2 + 1) + (20 * 3 + 1) = 129。
我们先来看两个正常走到全索引的例子:
mysql> explain select * from test01 where id = 1 and name = "zz" and passwd = "123";
+----+-------------+--------+------------+------+---------------+--------+---------+-------------------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra
|
+----+-------------+--------+------------+------+---------------+--------+---------+-------------------+------+----------+-------+
| 1 | SIMPLE | test01 | NULL | ref | t_idx1 | t_idx1 | 129 | const,const,const | 1 | 100.00 | NULL
|
+----+-------------+--------+------------+------+---------------+--------+---------+-------------------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
mysql> explain select passwd from test01 where name = "zz" and passwd = "123";
+----+-------------+--------+------------+-------+---------------+--------+---------+------+------+----------+-------------------
-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra
|
+----+-------------+--------+------------+-------+---------------+--------+---------+------+------+----------+-------------------
-------+
| 1 | SIMPLE | test01 | NULL | index | NULL | t_idx1 | 129 | NULL | 1 | 100.00 | Using where; Using
index |
+----+-------------+--------+------------+-------+---------------+--------+---------+------+------+----------+-------------------
-------+
1 row in set, 1 warning (0.00 sec)
mysql> explain select passwd from test01 where passwd = "123";
+----+-------------+--------+------------+-------+---------------+--------+---------+------+------+----------+-------------------
-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra
|
+----+-------------+--------+------------+-------+---------------+--------+---------+------+------+----------+-------------------
-------+
| 1 | SIMPLE | test01 | NULL | index | NULL | t_idx1 | 129 | NULL | 1 | 100.00 | Using where; Using
index |
+----+-------------+--------+------------+-------+---------------+--------+---------+------+------+----------+-------------------
-------+
1 row in set, 1 warning (0.00 sec)
以上三条SQL,无论是id = 1 and name = "zz" and passwd = "123"
, 还是name = "zz" and passwd = "123"
,或者passwd = "123"
,实际在查询中,都要按顺序将三个字段全部查到,因此都是129。
但是如果把SQL改成如下写法:
mysql> explain select passwd from test01 where id = 1 and name = "zz";
+----+-------------+--------+------------+------+---------------+--------+---------+-------------+------+----------+-------------
+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra
|
+----+-------------+--------+------------+------+---------------+--------+---------+-------------+------+----------+-------------
+
| 1 | SIMPLE | test01 | NULL | ref | t_idx1 | t_idx1 | 68 | const,const | 1 | 100.00 | Using index
|
+----+-------------+--------+------------+------+---------------+--------+---------+-------------+------+----------+-------------
+
1 row in set, 1 warning (0.00 sec)
发现虽然type的级别仍然是ref,走到的索引也仍然是t_idx1,但是key_len 却只有68,也就是id和name的长度,passwd字段虽然也在索引里,但是由于不在条件里,因此就没有走到。
同理,下面的SQL也是一样的道理,因为只用到了id,所以key_len只有5.
mysql> explain select passwd from test01 where id = 1;
+----+-------------+--------+------------+------+---------------+--------+---------+-------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+--------+------------+------+---------------+--------+---------+-------+------+----------+-------------+
| 1 | SIMPLE | test01 | NULL | ref | t_idx1 | t_idx1 | 5 | const | 1 | 100.00 | Using index |
+----+-------------+--------+------------+------+---------------+--------+---------+-------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)
但是我们需要注意的是下面这种情况:
mysql> explain select passwd from test01 where id = 1 and passwd = "123";
+----+-------------+--------+------------+------+---------------+--------+---------+-------+------+----------+-------------------
-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra
|
+----+-------------+--------+------------+------+---------------+--------+---------+-------+------+----------+-------------------
-------+
| 1 | SIMPLE | test01 | NULL | ref | t_idx1 | t_idx1 | 5 | const | 1 | 100.00 | Using where; Using
index |
+----+-------------+--------+------------+------+---------------+--------+---------+-------+------+----------+-------------------
-------+
我们在where条件里带了id和passwd,但并不如我们想象中的key_len = 66,而是等于5,也就是说,它实际只用到了id字段,而并没有用到passwd。
造成这种情况的原因在于,复合索引是严格按照复合索引中字段的先后顺序执行的,因此要求我们写SQL的时候,也要按照复合索引的顺序去书写(参见上一篇文章SQL优化初探-索引)
ref
注意此处的ref和前面type里出现的ref并不是同一个意思。这里的ref代表的是索引关联了哪个字段。
常用取值有:
id | ref | 说明 |
---|---|---|
1 | NULL | 没有用到任何字段 |
2 | const | 某个具体的值 |
3 | 具体某张表的字段值 | 一般用于关联语句中 |
下面仍然以例子来说明:
-- 具体的数值:const
mysql> explain select * from employee where e_id = 1;
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
| 1 | SIMPLE | employee | NULL | const | PRIMARY,e_idx1 | PRIMARY | 4 | const | 1 | 100.00 | NULL |
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
--不等于任何值
mysql> explain select * from employee where e_id < 5;
+----+-------------+----------+------------+-------+----------------+---------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+----------+------------+-------+----------------+---------+---------+------+------+----------+-------------+
| 1 | SIMPLE | employee | NULL | range | PRIMARY,e_idx1 | PRIMARY | 4 | NULL | 4 | 100.00 | Using where |
+----+-------------+----------+------------+-------+----------------+---------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)
--某个具体字段
mysql> explain select * from employee where e_id in (select s_id from salary);
+----+-------------+----------+------------+-------+----------------+--------+---------+----------------------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+----------+------------+-------+----------------+--------+---------+----------------------+------+----------+-------------+
| 1 | SIMPLE | employee | NULL | index | PRIMARY,e_idx1 | e_idx2 | 68 | NULL | 5 | 100.00 | Using index |
| 1 | SIMPLE | salary | NULL | ref | s_idx1 | s_idx1 | 5 | testDB.employee.e_id | 1 | 100.00 | Using index |
+----+-------------+----------+------------+-------+----------------+--------+---------+----------------------+------+----------+-------------+
2 rows in set, 1 warning (0.02 sec)
rows
通过索引返回的数据条数。
filtered
返回结果的行数占读取行数的百分比,该数值越大越好。
如:
mysql> explain select * from employee where e_id = 1;
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
| 1 | SIMPLE | employee | NULL | const | PRIMARY,e_idx1 | PRIMARY | 4 | const | 1 | 100.00 | NULL |
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------+
1 row in set, 1 warning (0.00 sec)
mysql> select * from employee where e_id = 1;
+------+--------+------+
| e_id | e_name | d_id |
+------+--------+------+
| 1 | zhang | 1 |
+------+--------+------+
1 row in set (0.00 sec)
查询结果为1条,而rows也为1条,因此filtered = 1/1 = 100%.
再看下面这个例子:
mysql> explain select * from employee where e_id < 3;
+----+-------------+----------+------------+-------+----------------+--------+---------+------+------+----------+--------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra
|
+----+-------------+----------+------------+-------+----------------+--------+---------+------+------+----------+--------------------------+
| 1 | SIMPLE | employee | NULL | index | PRIMARY,e_idx1 | e_idx2 | 68 | NULL | 5 | 40.00 | Using where; Using index |
+----+-------------+----------+------------+-------+----------------+--------+---------+------+------+----------+--------------------------+
1 row in set, 1 warning (0.00 sec)
mysql> select * from employee where e_id < 3;
+------+--------+------+
| e_id | e_name | d_id |
+------+--------+------+
| 2 | wang | 1 |
| 1 | zhang | 1 |
+------+--------+------+
2 rows in set (0.00 sec)
实际查询结果为2条,rows = 5条,因此filtered = 2/5 = 40%。
Extra
Extra是额外信息的意思。常见的值如下:
id | Extra | 说明 | 常见场景 |
---|---|---|---|
1 | use filesort | MySQL会对数据使用非索引进行排序 | 通常见于order by |
2 | use temporary | 使用临时中间表保存数据 | 通常见于group by |
3 | use index | select语句中使用了索引覆盖,避免回表访问 | 常见于select的字段只有索引字段 |
4 | use where | 需要回表查询 | 常见于where子句 |
以上四种情形,use filesort 和 use temporary 是比较糟糕的情况,一般出现这两种,意味着SQL需要优化;
而如果出现use index,则说明SQL性能比较好,通常意味着效率比较高。
下面仍然以例子来说明:
mysql> explain select e_id from employee where e_id < 3 order by d_id;
+----+-------------+----------+------------+-------+----------------+--------+---------+------+------+----------+----------------
--------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra
|
+----+-------------+----------+------------+-------+----------------+--------+---------+------+------+----------+----------------
--------------------------+
| 1 | SIMPLE | employee | NULL | index | PRIMARY,e_idx1 | e_idx2 | 68 | NULL | 5 | 40.00 | Using where; Us
ing index; Using filesort |
+----+-------------+----------+------------+-------+----------------+--------+---------+------+------+----------+----------------
--------------------------+
1 row in set, 1 warning (0.00 sec)
以上SQL中出现了Using filesort,探究其原因,是因为查询的where条件是e_id,而order by的字段却是d_id。
在上一篇文章中提到了SQL的解析过程为:
from ... on ... join ... where ... group by ... having ... select [distinct] ... order by ... limit ...;
这就意味着,在根据e_id查询出e_id后,还需要根据d_id进行排序,而d_id是未知的,这也就意味着有另外一次额外的查询。
再来看第二个例子:
mysql> explain select d_id from employee where e_id < 3 group by d_id;
+----+-------------+----------+------------+-------+-----------------------+--------+---------+------+------+----------+-----------------------------------------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra
|
+----+-------------+----------+------------+-------+-----------------------+--------+---------+------+------+----------+-----------------------------------------------------------+
| 1 | SIMPLE | employee | NULL | index | PRIMARY,e_idx1,e_idx2 | e_idx2 | 68 | NULL | 5 | 40.00 | Using where; Using index; Using temporary; Using filesort |
+----+-------------+----------+------------+-------+-----------------------+--------+---------+------+------+----------+-----------------------------------------------------------+
1 row in set, 1 warning (0.01 sec)
上句出现了Using temporary,原因就是因为查询时使用的索引是e_id,但group by分组时,使用的却是d_id,因此,需要额外的临时空间来进行分组操作,所以就出现了Using temporary。
如果把上面语句改一下:
mysql> explain select d_id from employee where e_id < 3 group by e_id;
+----+-------------+----------+------------+-------+------------------------------+---------+---------+------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered |
Extra |
+----+-------------+----------+------------+-------+------------------------------+---------+---------+------+------+----------+-------------+
| 1 | SIMPLE | employee | NULL | index | PRIMARY,e_idx1,e_idx2,e_idx3 | PRIMARY | 4 | NULL | 5 | 40.00 |
Using where |
+----+-------------+----------+------------+-------+------------------------------+---------+---------+------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)
此时出现的是Using where,而没有了之前的Using temporary。正是因为不再使用额外空间了的缘故。
最后来看这样一个例子:
mysql> explain select e_id from employee where e_id = 3;
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------------+
| 1 | SIMPLE | employee | NULL | const | PRIMARY,e_idx1 | PRIMARY | 4 | const | 1 | 100.00 | Using index |
+----+-------------+----------+------------+-------+----------------+---------+---------+-------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)
此时出现的是Using index,说明在索引树里就能查询到所需要的结果,不需要回表查询,效率当然会很高了。
关于执行计划,由于MySQL版本的不同,展示的字段也有所不同,比如MySQL5.5就没有partitions和filtered字段的展示。对于某些字段的含义也不尽相同。如MySQL5.5中,根据唯一索引查询到的记录为0条,type值为ref,但是在MySQL5.7中,type为eq_ref。这些细微的区别其实并不影响对执行计划的解读,只需要在使用的过程中稍加注意就行了。于实际SQL的优化并没有太大的影响。
总之,执行计划只是一个分析性能的工具,掌握该工具并不在于死记硬背,而在于探索和实践。
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