MySQL查询优化-内部查询

Question

这是整个查询。。。

SELECT s.*, (SELECT url FROM show_medias WHERE show_id = s.id AND is_primary = 1) AS media_url
FROM (shows As s)
WHERE `s`.`id` IN (
 SELECT DISTINCT st.show_id
 FROM show_time_schedules AS sts
 LEFT JOIN show_times AS st ON st.id = sts.show_time_id
 WHERE sts.schedule_date BETWEEN CAST('2012-01-10' AS date) AND CAST('2012-01-14' AS date)
 )
AND `s`.`is_active` = 1
ORDER BY s.name asc 

如果。。。

SELECT url FROM show_medias WHERE show_id = s.id AND is_primary = 1
(0.0004 sec)

而且。。。

 SELECT DISTINCT st.show_id
 FROM show_time_schedules AS sts
 LEFT JOIN show_times AS st ON st.id = sts.show_time_id
 WHERE sts.schedule_date BETWEEN CAST('2012-01-10' AS date) AND CAST('2012-01-14' AS date)
(0.0061 sec)

有明显的原因吗。。。。

SELECT s.*, (inner query 1) AS media_url
FROM (shows As s)
WHERE `s`.`id` IN ( inner query 2 )
AND `s`.`is_active` = 1
ORDER BY s.name asc

正在服用5.7245 sec？

解释扩展

id  select_type         table       type    possible_keys   key     key_len ref                     rows    filtered    Extra
1   PRIMARY             s           ALL     NULL            NULL    NULL    NULL                    151     100.00      Using where; Using filesort
3   DEPENDENT SUBQUERY  sts         ALL     NULL            NULL    NULL    NULL                    26290   100.00      Using where; Using temporary
3   DEPENDENT SUBQUERY  st          eq_ref  PRIMARY         PRIMARY 4       bvcdb.sts.show_time_id  1       100.00      Using where
2   DEPENDENT SUBQUERY  show_medias ALL     NULL            NULL    NULL    NULL                    159     100.00      Using where

Answer 1

您可以始终使用EXPLAIN或EXPLAIN EXTENDED来查看MySql对查询所做的操作

您也可以用稍微不同的方式编写查询，您尝试过以下方法吗？

SELECT        s.*, 
              sm.url AS media_url 
FROM          shows AS s
INNER JOIN    show_medias AS sm ON s.id = SM.show_id
WHERE `s`.`id` IN ( 
                        SELECT DISTINCT st.show_id 
                        FROM show_time_schedules AS sts 
                        LEFT JOIN show_times AS st ON st.id = sts.show_time_id 
                        WHERE sts.schedule_date BETWEEN CAST('2012-01-10' AS date) AND CAST('2012-01-14' AS date) 
                        ) 
AND            `s`.`is_active` = 1 
AND            sm.is_primary = 1
ORDER BY       s.name asc 

看看它的效果会很有趣。我希望它会更快，因为目前，我认为MySql将为您的每个节目运行内部查询1（这样一个查询将运行多次。联接应该更高效。）

如果您想要所有在show_medias中没有行的节目，请将INNER JOIN替换为LEFT JOIN。

编辑：

我很快就会看看你的EXPLAIN EXTENDED，我也不知道你是否想尝试以下内容；它删除了所有的子查询：

SELECT        DISTINCT s.*,  
                       sm.url AS media_url  
FROM                   shows AS s 
INNER JOIN             show_medias AS sm ON s.id = SM.show_id
INNER JOIN             show_times AS st ON (s.id = st.show_id)
RIGHT JOIN             show_time_schedules AS sts ON (st.id = sts.show_time_id)
WHERE                  `s`.`is_active` = 1  
AND                    sm.is_primary = 1 
AND                    sts.schedule_date BETWEEN CAST('2012-01-10' AS date) AND CAST('2012-01-14' AS date)  
ORDER BY               s.name asc 

（如果能看到EXPLAIN EXTENDED也很好——你可以把它添加到这篇文章的评论中）。

进一步编辑：

在您的EXPLAIN EXTENDED（如何阅读这些内容的良好开端在这里）

USING FILESORT和USING TEMPORARY都是关键指标。希望我推荐的第二个查询应该删除（子查询中的）任何TEMPORARY表。然后尝试关闭ORDER BY，看看这是否有影响（我们可以将其添加到目前的发现中：-）

我还可以看到，查询可能会错过许多索引查找；您的所有id列都是索引匹配的主要候选列（通常需要注意索引）。我也会尝试添加这些索引，然后再次运行EXPLAIN EXTENDED，看看现在有什么不同（编辑，我们已经从上面的评论中知道了！）

Answer 2

CTE解决方案来了：（我的错，mysql没有CTE，但问题太普遍了）

WITH RECURSIVE tree AS (
    SELECT t0.id
        , t0.study_start_time
        , t0.study_end_time
    FROM tab t0
    WHERE NOT EXISTS (SELECT * FROM tab nx
           WHERE nx.id=t0.id 
           AND nx.study_end_time = t0.study_start_time
           )
    UNION
    SELECT tt.id
        ,tt.study_start_time
        ,t1.study_end_time
    FROM tab t1
    JOIN tree tt ON t1.id=tt.id
                AND t1.study_start_time = tt.study_end_time
    )
SELECT * FROM tree
WHERE NOT EXISTS (SELECT * FROM tab nx 
                WHERE nx.id=tree.id
                AND tree.study_end_time = nx.study_start_time
                )
ORDER BY id
    ;

结果：

CREATE TABLE
INSERT 0 15
  id  | study_start_time | study_end_time 
------+------------------+----------------
 1234 |              168 |            480
 2345 |              175 |            233
 2345 |              400 |            425
 4567 |              200 |            225
 4567 |              250 |            289
 4567 |              300 |            310
 4567 |              320 |            340
 4567 |              360 |            390
(8 rows)

QUERY计划（添加明显PK和索引后）：

DROP TABLE
NOTICE:  CREATE TABLE / PRIMARY KEY will create implicit index "tab_pkey" for table "tab"
CREATE TABLE
CREATE INDEX
INSERT 0 15
                                                                QUERY PLAN                                                                 
-------------------------------------------------------------------------------------------------------------------------------------------
 Merge Anti Join  (cost=16209.59..16292.13 rows=6386 width=12) (actual time=0.189..0.193 rows=8 loops=1)
   Merge Cond: ((tree.id = nx.id) AND (tree.study_end_time = nx.study_start_time))
   CTE tree
     ->  Recursive Union  (cost=0.00..15348.09 rows=8515 width=12) (actual time=0.022..0.136 rows=15 loops=1)
           ->  Merge Anti Join  (cost=0.00..175.04 rows=1455 width=12) (actual time=0.019..0.041 rows=8 loops=1)
                 Merge Cond: ((t0.id = nx.id) AND (t0.study_start_time = nx.study_end_time))
                 ->  Index Scan using tab_pkey on tab t0  (cost=0.00..77.35 rows=1940 width=12) (actual time=0.010..0.018 rows=15 loops=1)
                 ->  Index Scan using sssss on tab nx  (cost=0.00..77.35 rows=1940 width=8) (actual time=0.003..0.008 rows=14 loops=1)
           ->  Merge Join  (cost=1297.04..1500.28 rows=706 width=12) (actual time=0.010..0.012 rows=1 loops=6)
                 Merge Cond: ((t1.id = tt.id) AND (t1.study_start_time = tt.study_end_time))
                 ->  Index Scan using tab_pkey on tab t1  (cost=0.00..77.35 rows=1940 width=12) (actual time=0.001..0.004 rows=9 loops=6)
                 ->  Sort  (cost=1297.04..1333.42 rows=14550 width=12) (actual time=0.006..0.006 rows=2 loops=6)
                       Sort Key: tt.id, tt.study_end_time
                       Sort Method: quicksort  Memory: 25kB
                       ->  WorkTable Scan on tree tt  (cost=0.00..291.00 rows=14550 width=12) (actual time=0.000..0.001 rows=2 loops=6)
   ->  Sort  (cost=726.15..747.44 rows=8515 width=12) (actual time=0.166..0.169 rows=15 loops=1)
         Sort Key: tree.id, tree.study_end_time
         Sort Method: quicksort  Memory: 25kB
         ->  CTE Scan on tree  (cost=0.00..170.30 rows=8515 width=12) (actual time=0.025..0.149 rows=15 loops=1)
   ->  Sort  (cost=135.34..140.19 rows=1940 width=8) (actual time=0.018..0.018 rows=15 loops=1)
         Sort Key: nx.id, nx.study_start_time
         Sort Method: quicksort  Memory: 25kB
         ->  Seq Scan on tab nx  (cost=0.00..29.40 rows=1940 width=8) (actual time=0.003..0.004 rows=15 loops=1)
 Total runtime: 0.454 ms
(24 rows)