前言

在平常開發中，對於 LEFT JOIN 和 JOIN 的用法大部分應該都是同樣的，若是有兩個表 A，B，若是兩個表的數據都想要，就使用 JOIN，若是隻想要一個表的所有數據，另外一個表數據無關緊要，就使用 LEFT JOIN。（固然這麼描述是不太準確的，可是很符合個人平常業務開發）。mysql

在 MYSQL LEFT JOIN 詳解這篇文章中咱們已經知道了，LEFT JOIN 是本身選擇驅動表的，而 JOIN 是 MYSQL 優化器選擇驅動表的。算法

那麼，當咱們寫了一條 LEFT JOIN 語句，MYSQL 會將這條語句優化成 JOIN 語句嗎？sql

若是會優化的話，那麼何時會優化呢？markdown

事實上，這正是我遇到的一個線上問題。咱們一塊兒來看一下。post

問題描述

在咱們線上有這麼一條慢 SQL（已處理），執行時間超過 0.5 秒。測試

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
複製代碼

explain 結果以下：優化

+----+-------------+--------------+------------+--------+------------------+----------+---------+------------------------+------+-------------+
| 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)
複製代碼

問題分析

經過 explain，再結合咱們以前講的 MYSQL 鏈接查詢算法，驅動表爲 order_extend，循環 3892 次，說多也很少，說少也很多，被驅動表數據查詢類型爲 eq_ref，因此應該不會太慢，那麼問題就出如今 3892 次上面了，想辦法將這個數字降下來便可。ui

等等！爲何驅動表是 order_extend？我明明使用的是 LEFT JOIN 啊，按理說驅動表應該是 order 表，爲何會變成了 order_extend 了。難道是 MYSQL 內部優化了？spa

順着這個思路，既然驅動表變了，說明這條 SQL 變爲 JOIN 語句了。code

咱們順着分析 JOIN 語句的方式來分析一下這條語句。（ps：須要對 MYSQL JOIN 內部執行過程有必定的理解，若是不太熟悉，請先移步看這篇文章 → MYSQL 鏈接查詢算法）

MYSQL 選擇 order_extend 當作驅動表，說明在 where 條件下 order_extend 查詢的數據更少，MYSQL 會選擇一個小的表當作驅動表。

咱們來分別適用上述的 where 條件單獨執行 select count(*) 語句，查看一下大體每一個表都涉及到多少條 SQL 記錄。

爲了避免影響咱們的分析，咱們使用 explain 語句，這樣整個過程就都是估算的結果，模擬一下 MYSQL 分析的過程。

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)
複製代碼

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)
複製代碼

能夠看到，在上述 where 條件下，order_extend 表只會查詢 3892 條數據，而 order 表會查詢 320372 條數據，因此 order_extend 表當驅動表是徹底沒有問題的。

那麼咱們再來看看爲何 order 表會掃描這麼多數據呢？在 2020-08-01 這一天可能也沒有這麼多數據啊。那麼這個時候咱們應該會很容易的想到，是強制走索引的問題，由於在上述查詢語句中，咱們強制走了 shop_id 索引，這個索引可能不是最優索引，咱們把 force index(shop_id) 去掉再試試看

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)
複製代碼

能夠看到，若是不強制走 shop_id 索引的話，走 create_time 索引的話，掃描的行數會更少，假設說 100 行，只會循環 100 次，掃描 100 x 3892 行數據，而以前的總共要循環 3892 次，掃描 3892 x 300000 行數據。

問題結論

因此最終的這條慢 SQL 的緣由肯定了，是由於咱們強制走 shop_id 索引，致使 MYSQL 掃描的行數更多了，咱們只須要去掉強制走索引便可，大多數時間 MYSQL 都會選擇正確的索引，因此強制使用索引的時候必定要當心謹慎。

問題延伸

SQL 慢的問題咱們已經解決了，咱們再來回顧一下文章開頭的問題：LEFT JOIN 會被優化爲 JOIN 嗎？

答案是會的。那麼何時會出現這種狀況呢？

咱們再來回顧一下 MYSQL LEFT JOIN 詳解文章中的內容。

爲了方便閱讀，咱們將部份內容粘貼出來。

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 | 羽絨服        |
|        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)
複製代碼

咱們能夠看到，當 where 條件中有被驅動表的條件時，查詢結果是和 JOIN 的結果是一致的，無 NULL 值的出現。

因此，咱們能夠想到，LEFT JOIN 優化爲 JOIN 的條件爲：where 條件中有被驅動表的非空條件時，LEFT JOIN 等價於 JOIN。

這不難理解，LEFT JOIN 會返回驅動表全部數據，當有被驅動表的 where 條件時，會過濾掉 NULL 的值，此時和 JOIN 的結果一致了，那麼 MYSQL 會選擇將 LEFT JOIN 優化爲 JOIN，這樣就能夠本身選擇驅動表了。

實例測試

咱們再來編寫一個測試用例來驗證一下咱們的結論。

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();
複製代碼

咱們建立了兩張如出一轍的表，每一個表中有 100 條數據，而後咱們執行一下 LEFT JOIN 語句。

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)
複製代碼

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)
複製代碼

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)
複製代碼

從上面看，給 B 表增長了 where 條件以後，若是 B 表掃描的行數更少，那麼是有可能換驅動表的，這也說明了，LEFT JOIN 語句被優化成了 JOIN 語句。

總結

上面咱們分析了一條慢 SQL 的問題，分析的過程涉及到了不少知識點，但願你們能夠認真研究一下。

同時咱們得出了一條結論：當有被驅動表的非空 where 條件時，MYSQL 會將 LEFT JOIN 語句優化爲 JOIN 語句。

什麼，LEFT JOIN 會變成 JOIN？

前言

問題描述

問題分析

問題結論

問題延伸

實例測試

總結