前言

在平常开发中，对于 LEFT JOIN 和 JOIN 的用法大部分应该都是同样的，若是有两个表 A，B，若是两个表的数据都想要，就使用 JOIN，若是只想要一个表的所有数据，另外一个表数据无关紧要，就使用 LEFT JOIN。（固然这么描述是不太准确的，可是很符合个人平常业务开发）。mysql

在 MYSQL LEFT JOIN 详解这篇文章中咱们已经知道了，LEFT JOIN 是本身选择驱动表的，而 JOIN 是 MYSQL 优化器选择驱动表的。算法

那么，当咱们写了一条 LEFT JOIN 语句，MYSQL 会将这条语句优化成 JOIN 语句吗？sql

若是会优化的话，那么何时会优化呢？markdown

事实上，这正是我遇到的一个线上问题。咱们一块儿来看一下。post

问题描述

在咱们线上有这么一条慢 SQL（已处理），执行时间超过 0.5 秒。测试

select 
    count(distinct order.order_id) 
from order force index(shop_id) 
left join `order_extend`
on `order`.`order_id` = `order_extend`.`order_id` 
where `order`.`create_time` >= "2020-08-01 00:00:00" 
and `order`.`create_time` <= "2020-08-01 23:59:59" 
and `order`.`shop_id` = 328449726569069326 
and `order`.`status` = 1 
and `order_extend`.`shop_id` = 328449726569069326 
and `order_extend`.`status` = 1
复制代码

explain 结果以下：优化

+----+-------------+--------------+------------+--------+------------------+----------+---------+------------------------+------+-------------+
| id | select_type | table        | partitions | type   | possible_keys    | key      | key_len | ref                    | rows | Extra       |
+----+-------------+--------------+------------+--------+------------------+----------+---------+------------------------+------+-------------+
|  1 | SIMPLE      | order_extend | NULL       | ref    | order_id,shop_id | shop_id  | 8       | const                  | 3892 | Using where |
|  1 | SIMPLE      | order        | NULL       | eq_ref | shop_id          | shop_id  | 16      | example.order.order_id |    1 | Using where |
+----+-------------+--------------+------------+--------+------------------+----------+---------+------------------------+------+-------------+
2 rows in set, 1 warning (0.00 sec)
复制代码

问题分析

经过 explain，再结合咱们以前讲的 MYSQL 链接查询算法，驱动表为 order_extend，循环 3892 次，说多也很少，说少也很多，被驱动表数据查询类型为 eq_ref，因此应该不会太慢，那么问题就出如今 3892 次上面了，想办法将这个数字降下来便可。ui

等等！为何驱动表是 order_extend？我明明使用的是 LEFT JOIN 啊，按理说驱动表应该是 order 表，为何会变成了 order_extend 了。难道是 MYSQL 内部优化了？spa

顺着这个思路，既然驱动表变了，说明这条 SQL 变为 JOIN 语句了。code

咱们顺着分析 JOIN 语句的方式来分析一下这条语句。（ps：须要对 MYSQL JOIN 内部执行过程有必定的理解，若是不太熟悉，请先移步看这篇文章 → MYSQL 链接查询算法）

MYSQL 选择 order_extend 当作驱动表，说明在 where 条件下 order_extend 查询的数据更少，MYSQL 会选择一个小的表当作驱动表。

咱们来分别适用上述的 where 条件单独执行 select count(*) 语句，查看一下大体每一个表都涉及到多少条 SQL 记录。

为了避免影响咱们的分析，咱们使用 explain 语句，这样整个过程就都是估算的结果，模拟一下 MYSQL 分析的过程。

mysql> explain select 
    count(distinct order.order_id) 
from order force index(shop_id) 
where `order`.`create_time` >= "2020-08-01 00:00:00" 
and `order`.`create_time` <= "2020-08-01 23:59:59" 
and `order`.`shop_id` = 328449726569069326 
and `order`.`status` = 1;


+----+-------------+-------+------------+------+--------------------------------+---------+---------+-------+--------+-------------+
| id | select_type | table | partitions | type | possible_keys                  | key     | key_len | ref   | rows   | Extra       |
+----+-------------+-------+------------+------+--------------------------------+---------+---------+-------+--------+-------------+
|  1 | SIMPLE      | order | NULL       | ref  | PRIMARY,shop_id,create_time... | shop_id | 8       | const | 320372 | Using where |
+----+-------------+-------+------------+------+--------------------------------+---------+---------+-------+--------+-------------+
1 row in set, 1 warning (0.00 sec)
复制代码

select 
    count(distinct order_extend.order_id) 
and `order_extend`.`shop_id` = 328449726569069326 
and `order_extend`.`status` = 1

+----+-------------+--------------+------------+------+------------------+---------+---------+-------+------+----------+-------------+
| id | select_type | table        | partitions | type | possible_keys    | key     | key_len | ref   | rows | filtered | Extra       |
+----+-------------+--------------+------------+------+------------------+---------+---------+-------+------+----------+-------------+
|  1 | SIMPLE      | order_extend | NULL       | ref  | order_id,shop_id | shop_id | 8       | const | 3892 |    10.00 | Using where |
+----+-------------+--------------+------------+------+------------------+---------+---------+-------+------+----------+-------------+
1 row in set, 1 warning (0.00 sec)
复制代码

能够看到，在上述 where 条件下，order_extend 表只会查询 3892 条数据，而 order 表会查询 320372 条数据，因此 order_extend 表当驱动表是彻底没有问题的。

那么咱们再来看看为何 order 表会扫描这么多数据呢？在 2020-08-01 这一天可能也没有这么多数据啊。那么这个时候咱们应该会很容易的想到，是强制走索引的问题，由于在上述查询语句中，咱们强制走了 shop_id 索引，这个索引可能不是最优索引，咱们把 force index(shop_id) 去掉再试试看

mysql> explain select 
    count(distinct order.order_id) 
where `order`.`create_time` >= "2020-08-01 00:00:00" 
and `order`.`create_time` <= "2020-08-01 23:59:59" 
and `order`.`shop_id` = 328449726569069326 
and `order`.`status` = 1;


+----+-------------+-------+------------+------+---------------+-------------+---------+-------+-------+----------+--------------------------+
| id | select_type | table | partitions | type | possible_keys | key         | key_len | ref   | rows  | filtered | Extra                    |
+----+-------------+-------+------------+------+---------------+-------------+---------+-------+-------+----------+--------------------------+
|  1 | SIMPLE      | order | NULL       | ref  | create_time   | create_time | 8       | const | <3892 |    10.00 | Using where; Using index |
+----+-------------+-------+------------+------+---------------+-------------+---------+-------+-------+----------+--------------------------+
1 row in set, 1 warning (0.00 sec)
复制代码

能够看到，若是不强制走 shop_id 索引的话，走 create_time 索引的话，扫描的行数会更少，假设说 100 行，只会循环 100 次，扫描 100 x 3892 行数据，而以前的总共要循环 3892 次，扫描 3892 x 300000 行数据。

问题结论

因此最终的这条慢 SQL 的缘由肯定了，是由于咱们强制走 shop_id 索引，致使 MYSQL 扫描的行数更多了，咱们只须要去掉强制走索引便可，大多数时间 MYSQL 都会选择正确的索引，因此强制使用索引的时候必定要当心谨慎。

问题延伸

SQL 慢的问题咱们已经解决了，咱们再来回顾一下文章开头的问题：LEFT JOIN 会被优化为 JOIN 吗？

答案是会的。那么何时会出现这种状况呢？

咱们再来回顾一下 MYSQL LEFT JOIN 详解文章中的内容。

为了方便阅读，咱们将部份内容粘贴出来。

mysql> select * from goods left join goods_category on goods.category_id = goods_category.category_id;
+----------+------------+-------------+-------------+---------------+
| goods_id | goods_name | category_id | category_id | category_name |
+----------+------------+-------------+-------------+---------------+
|        1 | 男鞋1      |           1 |           1 | 鞋            |
|        2 | 男鞋2      |           1 |           1 | 鞋            |
|        3 | 男鞋3      |           3 |           3 | 羽绒服        |
|        4 | T恤1       |           2 |           2 | T恤           |
|        5 | T恤2       |           2 |           2 | T恤           |
+----------+------------+-------------+-------------+---------------+
5 rows in set (0.00 sec)

mysql> select * from goods left join goods_category on goods.category_id = goods_category.category_id;
+----------+------------+-------------+-------------+---------------+
| goods_id | goods_name | category_id | category_id | category_name |
+----------+------------+-------------+-------------+---------------+
|        1 | 男鞋1      |           1 |           1 | 鞋            |
|        2 | 男鞋2      |           1 |           1 | 鞋            |
|        3 | 男鞋3      |           4 |        NULL | NULL          |
|        4 | T恤1       |           2 |           2 | T恤           |
|        5 | T恤2       |           2 |           2 | T恤           |
+----------+------------+-------------+-------------+---------------+
5 rows in set (0.00 sec)

mysql> select * from goods g left join goods_category c on (g.category_id = c.category_id and g.goods_name = 'T恤1');
+----------+------------+-------------+-------------+---------------+
| goods_id | goods_name | category_id | category_id | category_name |
+----------+------------+-------------+-------------+---------------+
|        1 | 男鞋1      |           1 |        NULL | NULL          |
|        2 | 男鞋2      |           1 |        NULL | NULL          |
|        3 | 男鞋3      |           4 |        NULL | NULL          |
|        4 | T恤1       |           2 |           2 | T恤           |
|        5 | T恤2       |           2 |        NULL | NULL          |
+----------+------------+-------------+-------------+---------------+
5 rows in set (0.00 sec)

mysql> select * from goods g left join goods_category c on (g.category_id = c.category_id and c.category_name = 'T恤');
+----------+------------+-------------+-------------+---------------+
| goods_id | goods_name | category_id | category_id | category_name |
+----------+------------+-------------+-------------+---------------+
|        1 | 男鞋1      |           1 |        NULL | NULL          |
|        2 | 男鞋2      |           1 |        NULL | NULL          |
|        3 | 男鞋3      |           4 |        NULL | NULL          |
|        4 | T恤1       |           2 |           2 | T恤           |
|        5 | T恤2       |           2 |           2 | T恤           |
+----------+------------+-------------+-------------+---------------+
5 rows in set (0.00 sec)

mysql> select * from goods g left join goods_category c on (g.category_id = c.category_id) where c.category_name = '鞋';
+----------+------------+-------------+-------------+---------------+
| goods_id | goods_name | category_id | category_id | category_name |
+----------+------------+-------------+-------------+---------------+
|        1 | 男鞋1      |           1 |           1 | 鞋            |
|        2 | 男鞋2      |           1 |           1 | 鞋            |
+----------+------------+-------------+-------------+---------------+
2 rows in set (0.00 sec)

mysql> select * from goods g left join goods_category c on (g.category_id = c.category_id) where g.goods_name = 'T恤1';
+----------+------------+-------------+-------------+---------------+
| goods_id | goods_name | category_id | category_id | category_name |
+----------+------------+-------------+-------------+---------------+
|        4 | T恤1       |           2 |           2 | T恤           |
+----------+------------+-------------+-------------+---------------+
1 row in set (0.00 sec)

mysql> select * from goods g left join goods_category c on (g.category_id = c.category_id and g.goods_name = 'T恤2') where g.goods_name = 'T恤1';
+----------+------------+-------------+-------------+---------------+
| goods_id | goods_name | category_id | category_id | category_name |
+----------+------------+-------------+-------------+---------------+
|        4 | T恤1       |           2 |        NULL | NULL          |
+----------+------------+-------------+-------------+---------------+
1 row in set (0.00 sec)
复制代码

咱们能够看到，当 where 条件中有被驱动表的条件时，查询结果是和 JOIN 的结果是一致的，无 NULL 值的出现。

因此，咱们能够想到，LEFT JOIN 优化为 JOIN 的条件为：where 条件中有被驱动表的非空条件时，LEFT JOIN 等价于 JOIN。

这不难理解，LEFT JOIN 会返回驱动表全部数据，当有被驱动表的 where 条件时，会过滤掉 NULL 的值，此时和 JOIN 的结果一致了，那么 MYSQL 会选择将 LEFT JOIN 优化为 JOIN，这样就能够本身选择驱动表了。

实例测试

咱们再来编写一个测试用例来验证一下咱们的结论。

CREATE TABLE `A` (
  `id` int(11) auto_increment,
  `a` int(11) DEFAULT NULL,
  PRIMARY KEY (`id`),
  KEY `a` (`a`)
) ENGINE=InnoDB;

delimiter ;;
create procedure idata()
begin
  declare i int;
  set i=1;
  while(i<=100)do
    insert into A (`a`) values(i);
    set i=i+1;
  end while;
end;;
delimiter ;
call idata();

CREATE TABLE `B` (
  `id` int(11) auto_increment,
  `b` int(11) DEFAULT NULL,
  PRIMARY KEY (`id`),
  KEY `b` (`b`)
) ENGINE=InnoDB;

delimiter ;;
create procedure idata()
begin
  declare i int;
  set i=1;
  while(i<=100)do
    insert into B (`b`) values(i);
    set i=i+1;
  end while;
end;;
delimiter ;
call idata();
复制代码

咱们建立了两张如出一辙的表，每一个表中有 100 条数据，而后咱们执行一下 LEFT JOIN 语句。

mysql> explain select * from A left join B on A.id = B.id where A.a <= 100;
+----+-------------+-------+------------+--------+---------------+---------+---------+---------------+------+----------+--------------------------+
| id | select_type | table | partitions | type   | possible_keys | key     | key_len | ref           | rows | filtered | Extra                    |
+----+-------------+-------+------------+--------+---------------+---------+---------+---------------+------+----------+--------------------------+
|  1 | SIMPLE      | A     | NULL       | index  | a             | a       | 5       | NULL          |  100 |   100.00 | Using where; Using index |
|  1 | SIMPLE      | B     | NULL       | eq_ref | PRIMARY       | PRIMARY | 4       | example2.A.id |    1 |   100.00 | NULL                     |
+----+-------------+-------+------------+--------+---------------+---------+---------+---------------+------+----------+--------------------------+
2 rows in set, 1 warning (0.00 sec)
复制代码

mysql> explain select * from A left join B on A.id = B.id where A.a <= 100 and B.b <= 50;
+----+-------------+-------+------------+--------+---------------+---------+---------+---------------+------+----------+--------------------------+
| id | select_type | table | partitions | type   | possible_keys | key     | key_len | ref           | rows | filtered | Extra                    |
+----+-------------+-------+------------+--------+---------------+---------+---------+---------------+------+----------+--------------------------+
|  1 | SIMPLE      | B     | NULL       | range  | PRIMARY,b     | b       | 5       | NULL          |   50 |   100.00 | Using where; Using index |
|  1 | SIMPLE      | A     | NULL       | eq_ref | PRIMARY,a     | PRIMARY | 4       | example2.B.id |    1 |   100.00 | Using where              |
+----+-------------+-------+------------+--------+---------------+---------+---------+---------------+------+----------+--------------------------+
2 rows in set, 1 warning (0.00 sec)
复制代码

mysql> explain select * from A left join B on A.id = B.id where A.a <= 100 and B.b <= 100;
+----+-------------+-------+------------+--------+---------------+---------+---------+---------------+------+----------+--------------------------+
| id | select_type | table | partitions | type   | possible_keys | key     | key_len | ref           | rows | filtered | Extra                    |
+----+-------------+-------+------------+--------+---------------+---------+---------+---------------+------+----------+--------------------------+
|  1 | SIMPLE      | A     | NULL       | index  | PRIMARY,a     | a       | 5       | NULL          |  100 |   100.00 | Using where; Using index |
|  1 | SIMPLE      | B     | NULL       | eq_ref | PRIMARY,b     | PRIMARY | 4       | example2.A.id |    1 |   100.00 | Using where              |
+----+-------------+-------+------------+--------+---------------+---------+---------+---------------+------+----------+--------------------------+
2 rows in set, 1 warning (0.00 sec)
复制代码

从上面看，给 B 表增长了 where 条件以后，若是 B 表扫描的行数更少，那么是有可能换驱动表的，这也说明了，LEFT JOIN 语句被优化成了 JOIN 语句。

总结

上面咱们分析了一条慢 SQL 的问题，分析的过程涉及到了不少知识点，但愿你们能够认真研究一下。

同时咱们得出了一条结论：当有被驱动表的非空 where 条件时，MYSQL 会将 LEFT JOIN 语句优化为 JOIN 语句。

什么，LEFT JOIN 会变成 JOIN？

前言

问题描述

问题分析

问题结论

问题延伸

实例测试

总结