MySQL版本:5.5.28-0ubuntu0.12.04.2-log

在我的印象中，JOIN总是比MySQL中的子查询更好，但EXPLAIN是更好的判断方式。下面是一个子查询比join更好的例子。

这是我的查询与3个子查询:

EXPLAIN SELECT vrl.list_id,vrl.ontology_id,vrl.position,l.name AS list_name, vrlih.position AS previous_position, vrl.moved_date 
FROM `vote-ranked-listory` vrl 
INNER JOIN lists l ON l.list_id = vrl.list_id 
INNER JOIN `vote-ranked-list-item-history` vrlih ON vrl.list_id = vrlih.list_id AND vrl.ontology_id=vrlih.ontology_id AND vrlih.type='PREVIOUS_POSITION' 
INNER JOIN list_burial_state lbs ON lbs.list_id = vrl.list_id AND lbs.burial_score < 0.5 
WHERE vrl.position <= 15 AND l.status='ACTIVE' AND l.is_public=1 AND vrl.ontology_id < 1000000000 
 AND (SELECT list_id FROM list_tag WHERE list_id=l.list_id AND tag_id=43) IS NULL 
 AND (SELECT list_id FROM list_tag WHERE list_id=l.list_id AND tag_id=55) IS NULL 
 AND (SELECT list_id FROM list_tag WHERE list_id=l.list_id AND tag_id=246403) IS NOT NULL 
ORDER BY vrl.moved_date DESC LIMIT 200;

解释说明:

+----+--------------------+----------+--------+-----------------------------------------------------+--------------+---------+-------------------------------------------------+------+--------------------------+
| id | select_type        | table    | type   | possible_keys                                       | key          | key_len | ref                                             | rows | Extra                    |
+----+--------------------+----------+--------+-----------------------------------------------------+--------------+---------+-------------------------------------------------+------+--------------------------+
|  1 | PRIMARY            | vrl      | index  | PRIMARY                                             | moved_date   | 8       | NULL                                            |  200 | Using where              |
|  1 | PRIMARY            | l        | eq_ref | PRIMARY,status,ispublic,idx_lookup,is_public_status | PRIMARY      | 4       | ranker.vrl.list_id                              |    1 | Using where              |
|  1 | PRIMARY            | vrlih    | eq_ref | PRIMARY                                             | PRIMARY      | 9       | ranker.vrl.list_id,ranker.vrl.ontology_id,const |    1 | Using where              |
|  1 | PRIMARY            | lbs      | eq_ref | PRIMARY,idx_list_burial_state,burial_score          | PRIMARY      | 4       | ranker.vrl.list_id                              |    1 | Using where              |
|  4 | DEPENDENT SUBQUERY | list_tag | ref    | list_tag_key,list_id,tag_id                         | list_tag_key | 9       | ranker.l.list_id,const                          |    1 | Using where; Using index |
|  3 | DEPENDENT SUBQUERY | list_tag | ref    | list_tag_key,list_id,tag_id                         | list_tag_key | 9       | ranker.l.list_id,const                          |    1 | Using where; Using index |
|  2 | DEPENDENT SUBQUERY | list_tag | ref    | list_tag_key,list_id,tag_id                         | list_tag_key | 9       | ranker.l.list_id,const                          |    1 | Using where; Using index |
+----+--------------------+----------+--------+-----------------------------------------------------+--------------+---------+-------------------------------------------------+------+--------------------------+

使用join的相同查询是:

EXPLAIN SELECT vrl.list_id,vrl.ontology_id,vrl.position,l.name AS list_name, vrlih.position AS previous_position, vrl.moved_date 
FROM `vote-ranked-listory` vrl 
INNER JOIN lists l ON l.list_id = vrl.list_id 
INNER JOIN `vote-ranked-list-item-history` vrlih ON vrl.list_id = vrlih.list_id AND vrl.ontology_id=vrlih.ontology_id AND vrlih.type='PREVIOUS_POSITION' 
INNER JOIN list_burial_state lbs ON lbs.list_id = vrl.list_id AND lbs.burial_score < 0.5 
LEFT JOIN list_tag lt1 ON lt1.list_id = vrl.list_id AND lt1.tag_id = 43 
LEFT JOIN list_tag lt2 ON lt2.list_id = vrl.list_id AND lt2.tag_id = 55 
INNER JOIN list_tag lt3 ON lt3.list_id = vrl.list_id AND lt3.tag_id = 246403 
WHERE vrl.position <= 15 AND l.status='ACTIVE' AND l.is_public=1 AND vrl.ontology_id < 1000000000 
AND lt1.list_id IS NULL AND lt2.tag_id IS NULL 
ORDER BY vrl.moved_date DESC LIMIT 200;

输出为:

+----+-------------+-------+--------+-----------------------------------------------------+--------------+---------+---------------------------------------------+------+----------------------------------------------+
| id | select_type | table | type   | possible_keys                                       | key          | key_len | ref                                         | rows | Extra                                        |
+----+-------------+-------+--------+-----------------------------------------------------+--------------+---------+---------------------------------------------+------+----------------------------------------------+
|  1 | SIMPLE      | lt3   | ref    | list_tag_key,list_id,tag_id                         | tag_id       | 5       | const                                       | 2386 | Using where; Using temporary; Using filesort |
|  1 | SIMPLE      | l     | eq_ref | PRIMARY,status,ispublic,idx_lookup,is_public_status | PRIMARY      | 4       | ranker.lt3.list_id                          |    1 | Using where                                  |
|  1 | SIMPLE      | vrlih | ref    | PRIMARY                                             | PRIMARY      | 4       | ranker.lt3.list_id                          |  103 | Using where                                  |
|  1 | SIMPLE      | vrl   | ref    | PRIMARY                                             | PRIMARY      | 8       | ranker.lt3.list_id,ranker.vrlih.ontology_id |   65 | Using where                                  |
|  1 | SIMPLE      | lt1   | ref    | list_tag_key,list_id,tag_id                         | list_tag_key | 9       | ranker.lt3.list_id,const                    |    1 | Using where; Using index; Not exists         |
|  1 | SIMPLE      | lbs   | eq_ref | PRIMARY,idx_list_burial_state,burial_score          | PRIMARY      | 4       | ranker.vrl.list_id                          |    1 | Using where                                  |
|  1 | SIMPLE      | lt2   | ref    | list_tag_key,list_id,tag_id                         | list_tag_key | 9       | ranker.lt3.list_id,const                    |    1 | Using where; Using index                     |
+----+-------------+-------+--------+-----------------------------------------------------+--------------+---------+---------------------------------------------+------+----------------------------------------------+

rows列的比较表明了差异，使用join的查询使用的是using temporary;使用filesort。

当然，当我运行这两个查询时，第一个查询在0.02秒内完成，第二个查询甚至在1分钟后都没有完成，所以EXPLAIN正确地解释了这些查询。

如果我在list_tag表上没有INNER JOIN，即如果我删除

AND (SELECT list_id FROM list_tag WHERE list_id=l.list_id AND tag_id=246403) IS NOT NULL  

从第一个查询和相应的:

INNER JOIN list_tag lt3 ON lt3.list_id = vrl.list_id AND lt3.tag_id = 246403

从第二个查询开始，那么EXPLAIN为两个查询返回相同的行数，并且这两个查询的运行速度相同。

根据我的观察，就像两种情况，如果一个表的记录少于10万条，那么连接将工作得很快。

但是如果一个表有超过100,000条记录，那么子查询是最好的结果。

我有一个表，其中有500,000条记录，我在查询下面创建了它，它的结果时间是

SELECT * 
FROM crv.workorder_details wd 
inner join  crv.workorder wr on wr.workorder_id = wd.workorder_id;

结果:13.3秒

select * 
from crv.workorder_details 
where workorder_id in (select workorder_id from crv.workorder)

结果:1.65秒

子查询是解决“从A获取事实，以B的事实为条件”这种形式的问题的逻辑正确方法。在这种情况下，在子查询中插入B比进行连接更具逻辑意义。从实际意义上讲，它也更安全，因为您不必担心由于与B的多个匹配而从a获得重复的事实。

然而，实际上，答案通常归结于性能。当给出连接和子查询时，一些优化器会很糟糕，而另一些则相反，这是特定于优化器、特定于dbms版本和特定于查询的。

从历史上看，显式连接通常会胜出，因此已经建立的智慧是连接更好，但优化器一直在变得更好，因此我更喜欢先以逻辑一致的方式编写查询，然后在性能限制的情况下重新构造查询。

子查询通常用于将单行作为原子值返回，不过它们也可以用于用IN关键字比较多行之间的值。在SQL语句中几乎任何有意义的地方都允许使用它们，包括目标列表、WHERE子句等等。一个简单的子查询可以用作搜索条件。例如，在一对表之间:

SELECT title 
FROM books 
WHERE author_id = (
    SELECT id 
    FROM authors 
    WHERE last_name = 'Bar' AND first_name = 'Foo'
);

注意，在子查询的结果上使用普通值操作符要求只返回一个字段。如果你想检查一个值是否存在于一组其他值中，请使用in:

SELECT title 
FROM books 
WHERE author_id IN (
    SELECT id FROM authors WHERE last_name ~ '^[A-E]'
);

这显然不同于LEFT-JOIN，你只是想连接表a和表B的东西，即使连接条件在表B中没有找到任何匹配的记录，等等。

如果你只是担心速度，你必须检查你的数据库，写一个好的查询，看看是否有显著的性能差异。

摘自MySQL手册(13.2.10.11将子查询重写为连接):

LEFT [OUTER] JOIN可以比等效的子查询更快，因为服务器可以更好地优化它——这不是MySQL服务器独有的事实。

所以子查询可能比LEFT [OUTER] JOIN慢，但在我看来，它们的优势是可读性略高。

子查询能够动态地计算聚合函数。 例如，找到这本书的最低价格，并得到所有以这个价格出售的书。 1)使用子查询:

SELECT titles, price
FROM Books, Orders
WHERE price = 
(SELECT MIN(price)
 FROM Orders) AND (Books.ID=Orders.ID);

2)使用join

SELECT MIN(price)
     FROM Orders;
-----------------
2.99

SELECT titles, price
FROM Books b
INNER JOIN  Orders o
ON b.ID = o.ID
WHERE o.price = 2.99;