对于MySQL执行计划的获取，我们可以通过explain方式来查看，explain方式看似简单，实际上包含的内容很多，尤其是输出结果中的type类型列。理解这些不同的类型，对于我们SQL优化举足轻重，本文仅描述explian输出结果中的type列，同时给出其演示。
有关explian输出的全描述，可以参考：MySQL EXPLAIN SQL 输出信息描述
一、EXPLAIN 语句中type列的值
type：
连接类型
system 表只有一行 const 表最多只有一行匹配，通用用于主键或者唯一索引比较时
eq_ref 每次与之前的表合并行都只在该表读取一行，这是除了system，const之外最好的一种，
特点是使用=，而且索引的所有部分都参与join且索引是主键或非空唯一键的索引
ref 如果每次只匹配少数行，那就是比较好的一种，使用=或<=>，可以是左覆盖索引或非主键或非唯一键
fulltext 全文搜索
ref_or_null 与ref类似，但包括NULL
index_merge 表示出现了索引合并优化(包括交集，并集以及交集之间的并集)，但不包括跨表和全文索引。
这个比较复杂，目前的理解是合并单表的范围索引扫描（如果成本估算比普通的range要更优的话）
unique_subquery 在in子查询中，就是value in (select...)把形如“select unique_key_column”的子查询替换。
PS：所以不一定in子句中使用子查询就是低效的！
index_subquery 同上，但把形如”select non_unique_key_column“的子查询替换
range 常数值的范围 index a.当查询是索引覆盖的，即所有数据均可从索引树获取的时候（Extra中有Using Index）；
b.以索引顺序从索引中查找数据行的全表扫描（无 Using Index）；
c.如果Extra中Using Index与Using Where同时出现的话，则是利用索引查找键值的意思；
d.如单独出现，则是用读索引来代替读行，但不用于查找
all 全表扫描二、连接类型部分示例
1、all-- 环境描述
(root@localhost) [sakila]> show variables like 'version';
+---------------+--------+
| Variable_name | Value |
+---------------+--------+
| version | 5.6.26 |
+---------------+--------+
MySQL采取全表遍历的方式来返回数据行，等同于Oracle的full table scan
(root@localhost) [sakila]> explain select count(description) from film;
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
| 1 | SIMPLE | film | ALL | NULL | NULL | NULL | NULL | 1000 | NULL |
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
2、index
MySQL采取索引全扫描的方式来返回数据行，等同于Oracle的full index scan
(root@localhost) [sakila]> explain select title from film G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: film
type: indexpossible_keys: NULL
key: idx_title
key_len: 767
ref: NULL
rows: 1000
Extra: Using index1 row in set (0.00 sec)
3、 range
索引范围扫描，对索引的扫描开始于某一点，返回匹配值域的行，常见于between、<、>等的查询
等同于Oracle的index range scan
(root@localhost) [sakila]> explain select * from payment where customer_id>300 and customer_id<400G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: payment
type: rangepossible_keys: idx_fk_customer_id
key: idx_fk_customer_id
key_len: 2
ref: NULL
rows: 2637
Extra: Using where1 row in set (0.00 sec)
(root@localhost) [sakila]> explain select * from payment where customer_id in (200,300,400)G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: payment
type: rangepossible_keys: idx_fk_customer_id
key: idx_fk_customer_id
key_len: 2
ref: NULL
rows: 86
Extra: Using index condition1 row in set (0.00 sec)
4、ref
非唯一性索引扫描或者，返回匹配某个单独值的所有行。常见于使用非唯一索引即唯一索引的非唯一前缀进行的查找
(root@localhost) [sakila]> explain select * from payment where customer_id=305G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: payment
type: refpossible_keys: idx_fk_customer_id
key: idx_fk_customer_id
key_len: 2
ref: const
rows: 25
Extra: 1 row in set (0.00 sec)
idx_fk_customer_id为表payment上的外键索引，且存在多个不不唯一的值，如下查询
(root@localhost) [sakila]> select customer_id,count(*) from payment group by customer_id
-> limit 2;
+-------------+----------+
| customer_id | count(*) |+-------------+----------+
| 1 | 32 || 2 | 27 |
+-------------+----------+-- 下面是非唯一前缀索引使用ref的示例
(root@localhost) [sakila]> create index idx_fisrt_last_name on customer(first_name,last_name);
Query OK, 599 rows affected (0.09 sec)
Records: 599 Duplicates: 0 Warnings: 0(root@localhost) [sakila]> select first_name,count(*) from customer group by first_name
-> having count(*)>1 limit 2;
+------------+----------+| first_name | count(*) |
+------------+----------+| JAMIE | 2 || JESSIE | 2 |
+------------+----------+2 rows in set (0.00 sec)
(root@localhost) [sakila]> explain select first_name from customer where first_name='JESSIE'G
*************************** 1. row ***************************
id: 1 select_type: SIMPLE
table: customer
type: refpossible_keys: idx_fisrt_last_name
key: idx_fisrt_last_name
key_len: 137
ref: const
rows: 2
Extra: Using where; Using index1 row in set (0.00 sec)
(root@localhost) [sakila]> alter table customer drop index idx_fisrt_last_name;
Query OK, 599 rows affected (0.03 sec)
Records: 599 Duplicates: 0 Warnings: 0--下面演示出现在join是ref的示例
(root@localhost) [sakila]> explain select b.*,a.* from payment a inner join -> customer b on a.customer_id=b.customer_idG
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: b
type: ALLpossible_keys: PRIMARY
key: NULL
key_len: NULL
ref: NULL
rows: 599
Extra: NULL
*************************** 2. row ***************************
id: 1
select_type: SIMPLE
table: a
type: refpossible_keys: idx_fk_customer_id
key: idx_fk_customer_id
key_len: 2
ref: sakila.b.customer_id
rows: 13
Extra: NULL2 rows in set (0.01 sec)
5、eq_ref
类似于ref，其差别在于使用的索引为唯一索引，对于每个索引键值，表中只有一条记录与之匹配。
多见于主键扫描或者索引唯一扫描。
(root@localhost) [sakila]> explain select * from film a join film_text b
-> on a.film_id=b.film_id;
+----+-------------+-------+--------+---------------+---------+---------+------------------+------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+--------+---------------+---------+---------+------------------+------+-------------+
| 1 | SIMPLE | b | ALL | PRIMARY | NULL | NULL | NULL | 1000 | NULL |
| 1 | SIMPLE | a | eq_ref | PRIMARY | PRIMARY | 2 | sakila.b.film_id | 1 | Using where |
+----+-------------+-------+--------+---------------+---------+---------+------------------+------+-------------+
(root@localhost) [sakila]> explain select title from film where film_id=5;
+----+-------------+-------+-------+---------------+---------+---------+-------+------+-------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------+---------------+---------+---------+-------+------+-------+| 1 | SIMPLE
| film | const | PRIMAR | PRIMARY | 2 | const | 1 | NULL |
+----+-------------+-------+-------+---------------+---------+---------+-------+------+-------+6、const、system：
当MySQL对查询某部分进行优化，这个匹配的行的其他列值可以转换为一个常量来处理。
如将主键或者唯一索引置于where列表中，MySQL就能将该查询转换为一个常量
(root@localhost) [sakila]> create table t1(id int,ename varchar(20) unique);
Query OK, 0 rows affected (0.05 sec)
(root@localhost) [sakila]> insert into t1 values(1,'robin'),(2,'jack'),(3,'henry');
Query OK, 3 rows affected (0.00 sec)
Records: 3 Duplicates: 0 Warnings: 0
(root@localhost) [sakila]> explain select * from (select * from t1 where ename='robin')x;
+----+-------------+------------+--------+---------------+-------+---------+-------+------+-------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+------------+--------+---------------+-------+---------+-------+------+-------+
| 1 | PRIMARY | <derived2> | system | NULL | NULL | NULL | NULL | 1 | NULL |
| 2 | DERIVED | t1 | const | ename | ename | 23 | const | 1 | NULL |
+----+-------------+------------+--------+---------------+-------+---------+-------+------+-------+
2 rows in set (0.00 sec)
7、type=NULL
MySQL不用访问表或者索引就可以直接得到结果
(root@localhost) [sakila]> explain select sysdate();+----+-------------+-------+------+---------------+------+---------+------+------+----------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+------+---------------+------+---------+------+------+----------------+
| 1 | SIMPLE | NULL | NULL | NULL | NULL | NULL | NULL | NULL | No tables used |
+----+-------------+-------+------+---------------+------+---------+------+------+----------------+
1 row in set (0.00 sec)
对于MySQL执行计划的获取，我们可以通过explain方式来查看，explain方式看似简单，实际上包含的内容很多，尤其是输出结果中的type类型列。理解这些不同的类型，对于我们SQL优化举足轻重，本文仅描述explian输出结果中的type列，同时给出其演示。
有关explian输出的全描述，可以参考：MySQL EXPLAIN SQL 输出信息描述
一、EXPLAIN 语句中type列的值
type：
连接类型
system 表只有一行 const 表最多只有一行匹配，通用用于主键或者唯一索引比较时
eq_ref 每次与之前的表合并行都只在该表读取一行，这是除了system，const之外最好的一种，
特点是使用=，而且索引的所有部分都参与join且索引是主键或非空唯一键的索引
ref 如果每次只匹配少数行，那就是比较好的一种，使用=或<=>，可以是左覆盖索引或非主键或非唯一键
fulltext 全文搜索
ref_or_null 与ref类似，但包括NULL
index_merge 表示出现了索引合并优化(包括交集，并集以及交集之间的并集)，但不包括跨表和全文索引。
这个比较复杂，目前的理解是合并单表的范围索引扫描（如果成本估算比普通的range要更优的话）
unique_subquery 在in子查询中，就是value in (select...)把形如“select unique_key_column”的子查询替换。
PS：所以不一定in子句中使用子查询就是低效的！
index_subquery 同上，但把形如”select non_unique_key_column“的子查询替换
range 常数值的范围 index a.当查询是索引覆盖的，即所有数据均可从索引树获取的时候（Extra中有Using Index）；
b.以索引顺序从索引中查找数据行的全表扫描（无 Using Index）；
c.如果Extra中Using Index与Using Where同时出现的话，则是利用索引查找键值的意思；
d.如单独出现，则是用读索引来代替读行，但不用于查找
all 全表扫描二、连接类型部分示例
1、all-- 环境描述
(root@localhost) [sakila]> show variables like 'version';
+---------------+--------+
| Variable_name | Value |
+---------------+--------+
| version | 5.6.26 |
+---------------+--------+MySQL采取全表遍历的方式来返回数据行，等同于Oracle的full table scan
(root@localhost) [sakila]> explain select count(description) from film;
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
| 1 | SIMPLE | film | ALL | NULL | NULL | NULL | NULL | 1000 | NULL |
+----+-------------+-------+------+---------------+------+---------+------+------+-------+
2、index
MySQL采取索引全扫描的方式来返回数据行，等同于Oracle的full index scan
(root@localhost) [sakila]> explain select title from film G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: film
type: indexpossible_keys: NULL
key: idx_title
key_len: 767
ref: NULL
rows: 1000
Extra: Using index1 row in set (0.00 sec)
3、 range
索引范围扫描，对索引的扫描开始于某一点，返回匹配值域的行，常见于between、<、>等的查询
等同于Oracle的index range scan
(root@localhost) [sakila]> explain select * from payment where customer_id>300 and customer_id<400G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: payment
type: rangepossible_keys: idx_fk_customer_id
key: idx_fk_customer_id
key_len: 2
ref: NULL
rows: 2637
Extra: Using where1 row in set (0.00 sec)
(root@localhost) [sakila]> explain select * from payment where customer_id in (200,300,400)G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: payment
type: rangepossible_keys: idx_fk_customer_id
key: idx_fk_customer_id
key_len: 2
ref: NULL
rows: 86
Extra: Using index condition1 row in set (0.00 sec)
4、ref
非唯一性索引扫描或者，返回匹配某个单独值的所有行。常见于使用非唯一索引即唯一索引的非唯一前缀进行的查找
(root@localhost) [sakila]> explain select * from payment where customer_id=305G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: payment
type: refpossible_keys: idx_fk_customer_id
key: idx_fk_customer_id
key_len: 2
ref: const
rows: 25
Extra: 1 row in set (0.00 sec)
idx_fk_customer_id为表payment上的外键索引，且存在多个不不唯一的值，如下查询
(root@localhost) [sakila]> select customer_id,count(*) from payment group by customer_id
-> limit 2;
+-------------+----------+
| customer_id | count(*) |+-------------+----------+
| 1 | 32 || 2 | 27 |
+-------------+----------+-- 下面是非唯一前缀索引使用ref的示例
(root@localhost) [sakila]> create index idx_fisrt_last_name on customer(first_name,last_name);
Query OK, 599 rows affected (0.09 sec)
Records: 599 Duplicates: 0 Warnings: 0(root@localhost) [sakila]> select first_name,count(*) from customer group by first_name
-> having count(*)>1 limit 2;
+------------+----------+| first_name | count(*) |
+------------+----------+| JAMIE | 2 || JESSIE | 2 |
+------------+----------+2 rows in set (0.00 sec)
(root@localhost) [sakila]> explain select first_name from customer where first_name='JESSIE'G
*************************** 1. row ***************************
id: 1
select_type: SIMPLE
table: customer
type: refpossible_keys: idx_fisrt_last_name
key: idx_fisrt_last_name
key_len: 137
ref: const
rows: 2
Extra: Using where; Using index1 row in set (0.00 sec)
(root@localhost) [sakila]> alter table customer drop index idx_fisrt_last_name;
Query OK, 599 rows affected (0.03 sec)
Records: 599 Duplicates: 0 Warnings: 0--下面演示出现在join是ref的示例
(root@localhost) [sakila]> explain select b.*,a.* from payment a inner join
-> customer b on a.customer_id=b.customer_idG
*************************** 1. row ***************************
id: 1
select_type:
SIMPLE
table: b
type: ALLpossible_keys: PRIMARY
key: NULL
key_len: NULL
ref: NULL
rows: 599
Extra: NULL
*************************** 2. row ***************************
id: 1
select_type: SIMPLE
table: a
type: refpossible_keys: idx_fk_customer_id
key: idx_fk_customer_id
key_len: 2
ref: sakila.b.customer_id
rows: 13
Extra: NULL2 rows in set (0.01 sec)
5、eq_ref
类似于ref，其差别在于使用的索引为唯一索引，对于每个索引键值，表中只有一条记录与之匹配。
多见于主键扫描或者索引唯一扫描。
(root@localhost) [sakila]> explain select * from film a join film_text b
-> on a.film_id=b.film_id;
+----+-------------+-------+--------+---------------+---------+---------+------------------+------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+--------+---------------+---------+---------+------------------+------+-------------+
| 1 | SIMPLE | b | ALL | PRIMARY | NULL | NULL | NULL | 1000 | NULL |
| 1 | SIMPLE | a | eq_ref | PRIMARY | PRIMARY | 2 | sakila.b.film_id | 1 | Using where |
+----+-------------+-------+--------+---------------+---------+---------+------------------+------+-------------+
(root@localhost) [sakila]> explain select title from film where film_id=5;
+----+-------------+-------+-------+---------------+---------+---------+-------+------+-------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------+---------------+---------+---------+-------+------+-------+
| 1 | SIMPLE | film | const | PRIMARY | PRIMARY | 2 | const | 1 | NULL |
+----+-------------+-------+-------+---------------+---------+---------+-------+------+-------+
6、const、system：
当MySQL对查询某部分进行优化，这个匹配的行的其他列值可以转换为一个常量来处理。
如将主键或者唯一索引置于where列表中，MySQL就能将该查询转换为一个常量
(root@localhost) [sakila]> create table t1(id int,ename varchar(20) unique);
Query OK, 0 rows affected (0.05 sec)
(root@localhost) [sakila]> insert into t1 values(1,'robin'),(2,'jack'),(3,'henry');
Query OK, 3 rows affected (0.00 sec)
Records: 3 Duplicates: 0 Warnings: 0
(root@localhost) [sakila]> explain select * from (select * from t1 where ename='robin')x;
+----+-------------+------------+--------+---------------+-------+---------+-------+------+-------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+------------+--------+---------------+-------+---------+-------+------+-------+|
1 | PRIMARY | <derived2> | system | NULL | NULL | NULL | NULL | 1 | NULL ||
2 | DERIVED | t1 | const | ename | ename | 2
3 | const | 1 | NULL |
+----+-------------+------------+--------+---------------+-------+---------+-------+------+-------+
2 rows in set (0.00 sec)
7、type=NULL
MySQL不用访问表或者索引就可以直接得到结果
(root@localhost) [sakila]> explain select sysdate();
+----+-------------+-------+------+---------------+------+---------+------+------+----------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+------+---------------+------+---------+------+------+----------------+
| 1 | SIMPLE | NULL | NULL | NULL | NULL | NULL | NULL | NULL | No tables used |
+----+-------------+-------+------+---------------+------+---------+------+------+----------------+
1 row in set (0.00 sec)
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