为什么mySQL查询,左连接'相当'比我的内连接快

Question

我研究了这个,但我仍然无法解释原因:

SELECT cl.`cl_boolean`, l.`l_name`
FROM `card_legality` cl
INNER JOIN `legality` l ON l.`legality_id` = cl.`legality_id`
WHERE cl.`card_id` = 23155

明显慢于:

SELECT cl.`cl_boolean`, l.`l_name`
FROM `card_legality` cl
LEFT JOIN `legality` l ON l.`legality_id` = cl.`legality_id`
WHERE cl.`card_id` = 23155

115毫秒对478毫秒.他们都使用InnoDB并且定义了关系.'card_legality'包含大约200k行,而'legality'表包含11行.以下是每个的结构:

CREATE TABLE `card_legality` (
  `card_id` varchar(8) NOT NULL DEFAULT '',
  `legality_id` int(3) NOT NULL,
  `cl_boolean` tinyint(1) NOT NULL,
  PRIMARY KEY (`card_id`,`legality_id`),
  KEY `legality_id` (`legality_id`),
  CONSTRAINT `card_legality_ibfk_2` FOREIGN KEY (`legality_id`) REFERENCES `legality` (`legality_id`),
  CONSTRAINT `card_legality_ibfk_1` FOREIGN KEY (`card_id`) REFERENCES `card` (`card_id`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1;

和:

CREATE TABLE `legality` (
  `legality_id` int(3) NOT NULL AUTO_INCREMENT,
  `l_name` varchar(16) NOT NULL DEFAULT '',
  PRIMARY KEY (`legality_id`)
) ENGINE=InnoDB AUTO_INCREMENT=12 DEFAULT CHARSET=latin1;

我可以简单地使用LEFT-JOIN,但它似乎不太正确......请问有什么想法吗？

更新: 根据要求,我已经包括每个解释的结果.我以前跑了它,但我不假装对它有透彻的了解..

id  select_type table   type    possible_keys   key key_len ref rows    Extra
1   SIMPLE  cl  ALL PRIMARY NULL    NULL    NULL    199747  Using where
1   SIMPLE  l   eq_ref  PRIMARY PRIMARY 4   hexproof.co.uk.cl.legality_id   1   

AND,内连接:

id  select_type table   type    possible_keys   key key_len         ref                         rows    Extra
1   SIMPLE  l   ALL PRIMARY NULL    NULL    NULL    11  
1   SIMPLE  cl  ref PRIMARY,legality_id legality_id 4   hexproof.co.uk.l.legality_id    33799   Using where

Answer 1

这是因为card_id上的varchar.MySQL不能使用card_id上的索引作为card_id,如此处所述的mysql类型转换.重要的是

为了比较字符串列和数字,MySQL不能使用列上的索引来快速查找值.如果str_col是索引字符串列,则在以下语句中执行查找时,不能使用索引:

SELECT*FROM tbl_name WHERE str_col = 1;

这样做的原因是有许多不同的字符串可以转换为值1,例如"1","1"或"1a".

如果您将查询更改为

SELECT cl.`cl_boolean`, l.`l_name`
FROM `card_legality` cl
INNER JOIN `legality` l ON l.`legality_id` = cl.`legality_id`
WHERE cl.`card_id` = '23155'

和

SELECT cl.`cl_boolean`, l.`l_name`
FROM `card_legality` cl
LEFT JOIN `legality` l ON l.`legality_id` = cl.`legality_id`
WHERE cl.`card_id` = '23155'

您应该看到速度的巨大提升,并且还会看到不同的EXPLAIN.

以下是一个类似(但更简单)的测试来显示:

> desc id_test;
+-------+------------+------+-----+---------+-------+
| Field | Type       | Null | Key | Default | Extra |
+-------+------------+------+-----+---------+-------+
| id    | varchar(8) | NO   | PRI | NULL    |       |
+-------+------------+------+-----+---------+-------+
1 row in set (0.17 sec)

> select * from id_test;
+----+
| id |
+----+
| 1  |
| 2  |
| 3  |
| 4  |
| 5  |
| 6  |
| 7  |
| 8  |
| 9  |
+----+
9 rows in set (0.00 sec)

> explain select * from id_test where id = 1;
+----+-------------+---------+-------+---------------+---------+---------+------+------+--------------------------+
| id | select_type | table   | type  | possible_keys | key     | key_len | ref  | rows | Extra                    |
+----+-------------+---------+-------+---------------+---------+---------+------+------+--------------------------+
|  1 | SIMPLE      | id_test | index | PRIMARY       | PRIMARY | 10      | NULL |    9 | Using where; Using index |
+----+-------------+---------+-------+---------------+---------+---------+------+------+--------------------------+
1 row in set (0.00 sec)


> explain select * from id_test where id = '1';
+----+-------------+---------+-------+---------------+---------+---------+-------+------+-------------+
| id | select_type | table   | type  | possible_keys | key     | key_len | ref   | rows | Extra       |
+----+-------------+---------+-------+---------------+---------+---------+-------+------+-------------+
|  1 | SIMPLE      | id_test | const | PRIMARY       | PRIMARY | 10      | const |    1 | Using index |
+----+-------------+---------+-------+---------------+---------+---------+-------+------+-------------+
1 row in set (0.00 sec)

在第一种情况下Using where; Using index,第二种情况是Using index.ref也是NULL或者CONST.不用说,第二个更好.