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MySQL优化之执行计划

前言

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。

执行计划语法

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)

代码100分

数据准备

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：

代码100分/* employee表创建 */
create table employee(
    e_id int(4) auto_increment,
    e_name varchar(20) default NULL,
    d_id int(4), 
    primary key(e_id) 
);
/* 创建索引 */
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);

/* salary表创建 */
create table salary(
    s_id int(4),
    s_salary decimal(15,2)
);
/* 创建索引 */
create unique index s_idx1 on salary(s_id);
create index s_idx2 on salary(s_salary);

/* department表创建 */
create table department(
    d_id int(4),
    d_name char(10) not NULL
);
/* 创建索引 */
create unique index d_idx1 on department(d_id);
create index d_idx2 on department(d_name);

/* employee表插入数据 */
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);

/* salary表插入数据 */
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);

/* department 表插入数据 */
insert into department values(1, "tech");
insert into department values(2, "HR");
insert into department values(3, "PD");

如何去看执行计划

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：

代码100分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 | <union1,2> | 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      | <derived2> | 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 | <union2,3> | 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 | <union1,2> | 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<m,n>	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：

/*情形一：使用大于的情况*/
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)

/*情形二： 使用between ... and*/
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)

/*情形三： 使用like*/
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。

/*不等号<>测试*/
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)

/*in 测试*/
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)

/* like 百分号测试 */
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)

/*
* 该条SQL实际用到的是PRIMARY索引，也就是e_id，该字段长度为int(4),要求not null，所以key_len = 4.
*/

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)

/*
*该SQL实际使用到的索引为e_idx2,该索引的字段是e_name,由于该字段数据类型为varchar,且可以为空，所以key_len = 20*3(utf8字符长度) + 2(varchar) + 1(可以为null) = 63。

注意：字符长度关系为：
	utf8每个字符3字节
	gbk每个字符2字节
	latin1每个字符1字节
*/

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。

小结

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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