以下查询在1.6秒内执行
SET @num :=0, @current_shop_id := NULL, @current_product_id := NULL;
#this query limits the results of the query within it by row number (so that only 250 products get displayed per store)
SELECT * FROM (
#this query adds row numbers to the query within it
SELECT *, @num := IF( @current_shop_id = shop_id, IF(@current_product_id=product_id,@num,@num+1), 0) AS row_number, @current_shop_id := shop_id AS shop_dummy, @current_product_id := product_id AS product_dummy FROM (
SELECT shop, shops.shop_id AS
shop_id, p1.product_id AS
product_id
FROM products p1 LEFT JOIN #this LEFT JOIN gets the favorites count for each product
(
SELECT fav3.product_id AS product_id, SUM(CASE
WHEN fav3.current = 1 AND fav3.closeted = 1 THEN 1
WHEN fav3.current = 1 AND fav3.closeted = 0 THEN -1
ELSE 0
END) AS favorites_count
FROM favorites fav3
GROUP BY fav3.product_id
) AS fav4 ON p1.product_id=fav4.product_id
INNER JOIN sex ON sex.product_id=p1.product_id AND
sex.sex=0 AND
sex.date >= SUBDATE(NOW(),INTERVAL 1 DAY)
INNER JOIN shops ON shops.shop_id = p1.shop_id
ORDER BY shop, sex.DATE, product_id
) AS testtable
) AS rowed_results WHERE
rowed_results.row_number>=0 AND
rowed_results.row_number<(7)
将AND shops.shop_id=86添加到最终的WHERE子句会导致查询在292秒内执行：
SET @num :=0, @current_shop_id := NULL, @current_product_id := NULL;
#this query limits the results of the query within it by row number (so that only 250 products get displayed per store)
SELECT * FROM (
#this query adds row numbers to the query within it
SELECT *, @num := IF( @current_shop_id = shop_id, IF(@current_product_id=product_id,@num,@num+1), 0) AS row_number, @current_shop_id := shop_id AS shop_dummy, @current_product_id := product_id AS product_dummy FROM (
SELECT shop, shops.shop_id AS
shop_id, p1.product_id AS
product_id
FROM products p1 LEFT JOIN #this LEFT JOIN gets the favorites count for each product
(
SELECT fav3.product_id AS product_id, SUM(CASE
WHEN fav3.current = 1 AND fav3.closeted = 1 THEN 1
WHEN fav3.current = 1 AND fav3.closeted = 0 THEN -1
ELSE 0
END) AS favorites_count
FROM favorites fav3
GROUP BY fav3.product_id
) AS fav4 ON p1.product_id=fav4.product_id
INNER JOIN sex ON sex.product_id=p1.product_id AND
sex.sex=0 AND
sex.date >= SUBDATE(NOW(),INTERVAL 1 DAY)
INNER JOIN shops ON shops.shop_id = p1.shop_id AND
shops.shop_id=86
ORDER BY shop, sex.DATE, product_id
) AS testtable
) AS rowed_results WHERE
rowed_results.row_number>=0 AND
rowed_results.row_number<(7)
我认为用AND shops.shop_id=86限制商店表可以减少执行时间。相反，执行时间似乎取决于products表中的行数，products.shop_id等于指定的shops.shop_id。 products表中有大约34K行，products.shop_id = 86，执行时间为292秒。对于products.shop_id = 50，大约有28K行，执行时间是210秒。对于products.shop_id = 175，大约有2K行，执行时间是2.8秒。发生了什么事？
1.6秒查询的EXPLAIN EXTENDED为：
id select_type table type possible_keys key key_len ref rows filtered Extra
1 PRIMARY <derived2> ALL NULL NULL NULL NULL 1203 100.00 Using where
2 DERIVED <derived3> ALL NULL NULL NULL NULL 1203 100.00
3 DERIVED sex ALL product_id_2,product_id NULL NULL NULL 526846 75.00 Using where; Using temporary; Using filesort
3 DERIVED p1 eq_ref PRIMARY,shop_id,shop_id_2,product_id,shop_id_3 PRIMARY 4 mydatabase.sex.product_id 1 100.00
3 DERIVED <derived4> ALL NULL NULL NULL NULL 14752 100.00
3 DERIVED shops eq_ref PRIMARY PRIMARY 4 mydatabase.p1.shop_id 1 100.00
4 DERIVED fav3 ALL NULL NULL NULL NULL 15356 100.00 Using temporary; Using filesort
此EXPLAIN EXTENDED的显示警告
-----+
| Note | 1003 | select `rowed_results`.`shop` AS `shop`,`rowed_results`.`shop_id` AS `shop_id`,`rowed_results`.`product_id` AS `product_id`,`rowed_results`.`row_number` AS `row_number`,`rowed_results`.`shop_dummy` AS `shop_dummy`,`rowed_results`.`product_dummy` AS `product_dummy` from (select `testtable`.`shop` AS `shop`,`testtable`.`shop_id` AS `shop_id`,`testtable`.`product_id` AS `product_id`,(@num:=if(((@current_shop_id) = `testtable`.`shop_id`),if(((@current_product_id) = `testtable`.`product_id`),(@num),((@num) + 1)),0)) AS `row_number`,(@current_shop_id:=`testtable`.`shop_id`) AS `shop_dummy`,(@current_product_id:=`testtable`.`product_id`) AS `product_dummy` from (select `mydatabase`.`shops`.`shop` AS `shop`,`mydatabase`.`shops`.`shop_id` AS `shop_id`,`mydatabase`.`p1`.`product_id` AS `product_id` from `mydatabase`.`products` `p1` left join (select `mydatabase`.`fav3`.`product_id` AS `product_id`,sum((case when ((`mydatabase`.`fav3`.`current` = 1) and (`mydatabase`.`fav3`.`closeted` = 1)) then 1 when ((`mydatabase`.`fav3`.`current` = 1) and (`mydatabase`.`fav3`.`closeted` = 0)) then -(1) else 0 end)) AS `favorites_count` from `mydatabase`.`favorites` `fav3` group by `mydatabase`.`fav3`.`product_id`) `fav4` on(((`mydatabase`.`p1`.`product_id` = `mydatabase`.`sex`.`product_id`) and (`fav4`.`product_id` = `mydatabase`.`sex`.`product_id`))) join `mydatabase`.`sex` join `mydatabase`.`shops` where ((`mydatabase`.`sex`.`sex` = 0) and (`mydatabase`.`p1`.`product_id` = `mydatabase`.`sex`.`product_id`) and (`mydatabase`.`shops`.`shop_id` = `mydatabase`.`p1`.`shop_id`) and (`mydatabase`.`sex`.`date` >= (now() - interval 1 day))) order by `mydatabase`.`shops`.`shop`,`mydatabase`.`sex`.`date`,`mydatabase`.`p1`.`product_id`) `testtable`) `rowed_results` where ((`rowed_results`.`row_number` >= 0) and (`rowed_results`.`row_number` < 7)) |
+------
EXPLAIN EXTENDED为：
id select_type table type possible_keys key key_len ref rows filtered Extra
1 PRIMARY <derived2> ALL NULL NULL NULL NULL 36 100.00 Using where
2 DERIVED <derived3> ALL NULL NULL NULL NULL 36 100.00
3 DERIVED shops const PRIMARY PRIMARY 4 1 100.00 Using temporary; Using filesort
3 DERIVED p1 ref PRIMARY,shop_id,shop_id_2,product_id,shop_id_3 shop_id 4 11799 100.00
3 DERIVED <derived4> ALL NULL NULL NULL NULL 14752 100.00
3 DERIVED sex eq_ref product_id_2,product_id product_id_2 5 mydatabase.p1.product_id 1 100.00 Using where
4 DERIVED fav3 ALL NULL NULL NULL NULL 15356 100.00 Using temporary; Using filesort
此EXPLAIN EXTENDED的显示警告
----+
| Note | 1003 | select `rowed_results`.`shop` AS `shop`,`rowed_results`.`shop_id` AS `shop_id`,`rowed_results`.`product_id` AS `product_id`,`rowed_results`.`row_number` AS `row_number`,`rowed_results`.`shop_dummy` AS `shop_dummy`,`rowed_results`.`product_dummy` AS `product_dummy` from (select `testtable`.`shop` AS `shop`,`testtable`.`shop_id` AS `shop_id`,`testtable`.`product_id` AS `product_id`,(@num:=if(((@current_shop_id) = `testtable`.`shop_id`),if(((@current_product_id) = `testtable`.`product_id`),(@num),((@num) + 1)),0)) AS `row_number`,(@current_shop_id:=`testtable`.`shop_id`) AS `shop_dummy`,(@current_product_id:=`testtable`.`product_id`) AS `product_dummy` from (select 'shop.nordstrom.com' AS `shop`,'86' AS `shop_id`,`mydatabase`.`p1`.`product_id` AS `product_id` from `mydatabase`.`products` `p1` left join (select `mydatabase`.`fav3`.`product_id` AS `product_id`,sum((case when ((`mydatabase`.`fav3`.`current` = 1) and (`mydatabase`.`fav3`.`closeted` = 1)) then 1 when ((`mydatabase`.`fav3`.`current` = 1) and (`mydatabase`.`fav3`.`closeted` = 0)) then -(1) else 0 end)) AS `favorites_count` from `mydatabase`.`favorites` `fav3` group by `mydatabase`.`fav3`.`product_id`) `fav4` on(((`fav4`.`product_id` = `mydatabase`.`p1`.`product_id`) and (`mydatabase`.`sex`.`product_id` = `mydatabase`.`p1`.`product_id`))) join `mydatabase`.`sex` join `mydatabase`.`shops` where ((`mydatabase`.`sex`.`sex` = 0) and (`mydatabase`.`sex`.`product_id` = `mydatabase`.`p1`.`product_id`) and (`mydatabase`.`p1`.`shop_id` = 86) and (`mydatabase`.`sex`.`date` >= (now() - interval 1 day))) order by 'shop.nordstrom.com',`mydatabase`.`sex`.`date`,`mydatabase`.`p1`.`product_id`) `testtable`) `rowed_results` where ((`rowed_results`.`row_number` >= 0) and (`rowed_results`.`row_number` < 7)) |
+-----
我正在运行MySQL客户端版本：5.1.56。商店表在shop_id上有一个主要索引：
Action Keyname Type Unique Packed Column Cardinality Collation Null Comment
Edit Drop PRIMARY BTREE Yes No shop_id 163 A
我已经分析了商店表，但这没有帮助。
我注意到如果删除LEFT JOIN，执行时间的差异会下降到0.12秒而不是0.28秒。
Cez的解决方案，即使用1.6秒版本的查询并通过将rowed_results.shop_dummy=86添加到外部查询（如下所示）来删除不相关的结果，在1.7秒内执行。这避免了这个问题，但神秘仍然是为什么292秒的查询是如此缓慢。
SET @num :=0, @current_shop_id := NULL, @current_product_id := NULL;
#this query limits the results of the query within it by row number (so that only 250 products get displayed per store)
SELECT * FROM (
#this query adds row numbers to the query within it
SELECT *, @num := IF( @current_shop_id = shop_id, IF(@current_product_id=product_id,@num,@num+1), 0) AS row_number, @current_shop_id := shop_id AS shop_dummy, @current_product_id := product_id AS product_dummy FROM (
SELECT shop, shops.shop_id AS
shop_id, p1.product_id AS
product_id
FROM products p1 LEFT JOIN #this LEFT JOIN gets the favorites count for each product
(
SELECT fav3.product_id AS product_id, SUM(CASE
WHEN fav3.current = 1 AND fav3.closeted = 1 THEN 1
WHEN fav3.current = 1 AND fav3.closeted = 0 THEN -1
ELSE 0
END) AS favorites_count
FROM favorites fav3
GROUP BY fav3.product_id
) AS fav4 ON p1.product_id=fav4.product_id
INNER JOIN sex ON sex.product_id=p1.product_id AND sex.sex=0
INNER JOIN shops ON shops.shop_id = p1.shop_id
WHERE sex.date >= SUBDATE(NOW(),INTERVAL 1 DAY)
ORDER BY shop, sex.DATE, product_id
) AS testtable
) AS rowed_results WHERE
rowed_results.row_number>=0 AND
rowed_results.row_number<(7) AND
rowed_results.shop_dummy=86;
答案 0 :(得分：1)
根据讨论判断，在指定较低级别的商店时，查询计划程序表现不佳。
将rowed_results.shop_dummy=86添加到外部查询以获取您要查找的结果。
答案 1 :(得分：1)
在聊天室之后，实际创建表/列以匹配查询，我提出了以下查询。
我已经开始了我最内心的查询，包括性，产品（对于shop_id）和收藏夹表。由于您在ShopA = Product ID = 1时描述了ProductX，但在ShopB =产品ID = 2（仅示例）时相同的ProductX，每个产品始终是唯一的，并且从不重复。也就是说，我可以在此查询中获取产品和shop_id以及收藏夹数量（如果有的话），但只对product_id进行分组..因为shop_id不会更改我使用MAX（）的每个产品。因为你总是以“昨天”和性别（性别= 0女性）的日期来查看，所以我会在（日期，性别，product_id）索引SEX表...我猜你不是每个都添加1000个项目day ...产品显然会在product_id（主键）上有一个索引，而收藏夹应该在product_id上有一个索引。
根据该结果（别名“sxFav”），我们可以通过“Product_ID”直接加入性和产品表，以获取您可能需要的任何其他信息，例如商店名称，添加的日期产品，产品然后，这个结果由shop_id按产品销售，日期和最终产品ID排序（但您可以考虑在内部查询中抓取描述列并将其用作排序）。这导致别名“PreQuery”。
由于商店的订单完全合适，我们现在可以添加@MySQLVariable引用，以便为每个产品分配一个类似于您最初尝试的行号。但是，只有在商店ID发生变化时才重置为1。
SELECT
PreQuery.*,
@num := IF( @current_shop_id = PreQuery.shop_id, @num +1, 1 ) AS RowPerShop,
@current_shop_id := PreQuery.shop_id AS shop_dummy
from
( SELECT
sxFav.product_id,
sxFav.shop_id,
sxFav.Favorites_Count
from
( SELECT
sex.product_id,
MAX( p.shop_id ) shop_id,
SUM( CASE WHEN F.current = 1 AND F.closeted = 1 THEN 1
WHEN F.current = 1 AND F.closeted = 0 THEN -1
ELSE 0 END ) AS favorites_count
from
sex
JOIN products p
ON sex.Product_ID = p.Product_ID
LEFT JOIN Favorites F
ON sex.product_id = F.product_ID
where
sex.date >= subdate( now(), interval 1 day)
and sex.sex = 0
group by
sex.product_id ) sxFav
JOIN sex
ON sxFav.Product_ID = sex.Product_ID
JOIN products p
ON sxFav.Product_ID = p.Product_ID
order by
sxFav.shop_id,
sex.date,
sxFav.product_id ) PreQuery,
( select @num :=0,
@current_shop_id := 0 ) as SQLVars
现在，如果您正在寻找特定的“分页”信息（例如每个商店7个条目），请将上面的整个查询包装成类似......
select * from ( entire query above ) where RowPerShop between 1 and 7
（或根据需要在8到14,15和21之间等） 甚至
RowPerShop between RowsPerPage*PageYouAreShowing and RowsPerPage*(PageYouAreShowing +1)
答案 2 :(得分：1)
您应该将shops.shop_id = 86移动到商店的JOIN条件。没有理由把它放在JOIN之外，你首先冒着MySQL JOIN的风险，然后过滤。 JOIN可以执行WHERE子句所做的相同工作，特别是如果您没有引用其他表。
....
INNER JOIN shops ON shops.shop_id = p1.shop_id AND shops.shop_id=86
....
性别加入也是如此：
...
INNER JOIN shops ON shops.shop_id = p1.shop_id
AND sex.date >= SUBDATE(NOW(),INTERVAL 1 DAY)
...
派生表很棒，但它们没有索引。通常这没关系，因为它们通常在RAM中。但是在没有索引的过滤和排序之间，事情可能会加起来。
请注意，在需要更长时间的第二个查询中，表处理顺序会更改。商店表位于慢查询的顶部，p1表在快速查询中检索11799行而不是1行。它也不再使用主键。这可能就是你的问题所在。
3 DERIVED p1 eq_ref PRIMARY,shop_id,shop_id_2,product_id,shop_id_3 PRIMARY 4 mydatabase.sex.product_id 1 100.00
3 DERIVED p1 ref PRIMARY,shop_id,shop_id_2,product_id,shop_id_3 shop_id 4 11799 100.00