我有三张桌子。
一张表格包含大约75,000行的提交
一张表格包含提交评分，并且只有一张表包含提交=>竞争映射，而对于我的测试数据，该表也有大约75,000行。
我想做的是
在一轮比赛中获得前50名参赛者。
最高分为最高平均评分，其次是最高票数
这是我正在使用的查询，它有效，但是问题是需要45秒钟才能完成！我对查询进行了概要分析（结果位于底部），并且瓶颈将数据复制到tmp表中，然后对其进行排序，因此如何加快速度？
SELECT `submission_submissions`.*
FROM `submission_submissions`
JOIN `competition_submissions`
ON `competition_submissions`.`submission_id` = `submission_submissions`.`id`
LEFT JOIN `submission_ratings`
ON `submission_submissions`.`id` = `submission_ratings`.`submission_id`
WHERE `top_round` = 1
AND `competition_id` = '2'
AND `submission_submissions`.`date_deleted` IS NULL
GROUP BY submission_submissions.id
ORDER BY AVG(submission_ratings.`stars`) DESC,
COUNT(submission_ratings.`id`) DESC
LIMIT 50
Submitting_submissions
CREATE TABLE `submission_submissions` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`account_id` int(11) NOT NULL,
`title` varchar(255) NOT NULL,
`description` varchar(255) DEFAULT NULL,
`genre` int(11) NOT NULL,
`goals` text,
`submission` text NOT NULL,
`date_created` datetime DEFAULT NULL,
`date_modified` datetime DEFAULT NULL,
`date_deleted` datetime DEFAULT NULL,
`cover_image` varchar(255) DEFAULT NULL,
PRIMARY KEY (`id`),
KEY `genre` (`genre`),
KEY `account_id` (`account_id`),
KEY `date_created` (`date_created`)
) ENGINE=InnoDB AUTO_INCREMENT=115037 DEFAULT CHARSET=latin1;
Submitting_ratings
CREATE TABLE `submission_ratings` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`account_id` int(11) NOT NULL,
`submission_id` int(11) NOT NULL,
`stars` tinyint(1) NOT NULL,
`date_created` datetime DEFAULT NULL,
PRIMARY KEY (`id`),
KEY `submission_id` (`submission_id`),
KEY `account_id` (`account_id`),
KEY `stars` (`stars`)
) ENGINE=InnoDB AUTO_INCREMENT=7 DEFAULT CHARSET=latin1;
比赛提交
CREATE TABLE `competition_submissions` (
`competition_id` int(11) NOT NULL,
`submission_id` int(11) NOT NULL,
`top_round` int(11) DEFAULT '1',
PRIMARY KEY (`submission_id`),
KEY `competition_id` (`competition_id`),
KEY `top_round` (`top_round`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1;
显示配置文件结果（按持续时间排序）
state duration (summed) in sec percentage
Copying to tmp table 33.15621 68.46924
Sorting result 11.83148 24.43260
removing tmp table 3.06054 6.32017
Sending data 0.37560 0.77563
... insignificant amounts removed ...
Total 48.42497 100.00000
说明
id select_type table type possible_keys key key_len ref rows Extra
1 SIMPLE competition_submissions index_merge PRIMARY,competition_id,top_round competition_id,top_round 4,5 18596 Using intersect(competition_id,top_round); Using where; Using index; Using temporary; Using filesort
1 SIMPLE submission_submissions eq_ref PRIMARY PRIMARY 4 inkstakes.competition_submissions.submission_id 1 Using where
1 SIMPLE submission_ratings ALL submission_id 5 Using where; Using join buffer (flat, BNL join)
最佳答案
假设实际上您不会对未分级提交感兴趣，并且对于给定的匹配项和top_round，给定的提交仅具有一个competition_submissions条目，我建议：
SELECT s.*
FROM (SELECT `submission_id`,
AVG(`stars`) AvgStars,
COUNT(`id`) CountId
FROM `submission_ratings`
GROUP BY `submission_id`
ORDER BY AVG(`stars`) DESC, COUNT(`id`) DESC
LIMIT 50) r
JOIN `submission_submissions` s
ON r.`submission_id` = s.`id` AND
s.`date_deleted` IS NULL
JOIN `competition_submissions` c
ON c.`submission_id` = s.`id` AND
c.`top_round` = 1 AND
c.`competition_id` = '2'
ORDER BY r.AvgStars DESC,
r.CountId DESC
（如果对于给定的匹配项和top_round，每个提交中有多个
competition_submissions条目，则可以将GROUP BY子句重新添加到主查询中。）如果您确实希望查看未评级的提交，则可以将该查询的结果合并到LEFT JOIN ... WHERE NULL查询中。