真的希望某种性能高手可以向我解释为什么单个连接导致查询速度变慢 10 倍。 (另外，请不要 mock 这个查询的大小!我想用一个查询输出我数据库中的整个目录。我不确定将它分解成更小的查询是否会更快但是好像不太对。)
SELECT `c`.`categoryID`,
`cl`.`name` AS `category_name`,
`v`.*,
TRUE AS `categoried`,
GROUP_CONCAT(DISTINCT t_v.iso_3166_1_alpha_2) AS `video_territories`,
GROUP_CONCAT(DISTINCT t_c.iso_3166_1_alpha_2) AS `category_territories`,
`vl`.*,
GROUP_CONCAT(DISTINCT kl.name) AS `keywords`
FROM `tblCategories` AS `c`
INNER JOIN `tblCategoryLocalisedData` AS `cl` ON c.categoryID = cl.categoryID
LEFT JOIN `tblCategoryDurations` AS `cd` ON c.categoryID = cd.categoryID
LEFT JOIN `tblCategoryRules` AS `cr` ON c.categoryID = cr.categoryID
LEFT JOIN `tblCategoryVideos` AS `cv` ON c.categoryID = cv.categoryID
LEFT JOIN `tblVideos` AS `v` ON cv.videoID = v.videoID
LEFT JOIN `tblVideoTerritories` AS `vt` ON vt.videoID = v.videoID
LEFT JOIN `tblCategoryTerritories` AS `ct` ON ct.categoryID = c.categoryID
INNER JOIN `tblTerritories` AS `t_v` ON t_v.territoryID = vt.territoryID
INNER JOIN `tblTerritories` AS `t_c` ON t_c.territoryID = ct.territoryID
INNER JOIN `tblVideoLocalisedData` AS `vl` ON vl.videoID = v.videoID
LEFT JOIN `tblVideoKeywords` AS `vk` ON v.videoID = vk.videoID
LEFT JOIN `tblKeywords` AS `k` ON vk.keywordID = k.keywordID
LEFT JOIN `tblKeywordLocalisedData` AS `kl` ON kl.keywordID = k.keywordID
INNER JOIN `tblLanguages` AS `l`
WHERE (cv.disabled IS NULL)
AND (cd.start_date < NOW() OR cd.start_date IS NULL)
AND (cd.end_date > NOW() OR cd.end_date IS NULL)
AND (cr.name IS NULL)
AND (l.languageID = cl.languageID OR cl.languageID IS NULL)
AND (l.languageID = kl.languageID OR kl.languageID IS NULL)
AND (l.languageID = vl.languageID OR vl.languageID IS NULL)
AND (l.iso_639_1 = 'en')
GROUP BY `v`.`videoID`, `c`.`categoryID`
ORDER BY `c`.`categoryID` ASC
当我运行上面的查询时，它需要整整 1 秒才能完成。我试着在上面运行 EXPLAIN，它给了我这个:
+----+-------------+-------+--------+--------------------------------------------------------------------------------------+-----------------------------------------+---------+------------------------+------+----------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+--------+--------------------------------------------------------------------------------------+-----------------------------------------+---------+------------------------+------+----------------------------------------------+
| 1 | SIMPLE | cv | ALL | fk_tblCategoryVideos_tblCategories1,fk_tblCategoryVideos_tblVideos1 | NULL | NULL | NULL | 2 | Using where; Using temporary; Using filesort |
| 1 | SIMPLE | c | eq_ref | PRIMARY | PRIMARY | 4 | db.cv.categoryID | 1 | Using index |
| 1 | SIMPLE | cd | ref | fk_tblCategoryDurations_tblCategories | fk_tblCategoryDurations_tblCategories | 4 | db.cv.categoryID | 1 | Using where |
| 1 | SIMPLE | cr | ref | fk_tblCategoryRules_tblCategories1 | fk_tblCategoryRules_tblCategories1 | 4 | db.cv.categoryID | 1 | Using where; Not exists |
| 1 | SIMPLE | vt | ref | fk_tblVideoTerritories_tblVideos1,fk_tblVideoTerritories_tblTerritories1 | fk_tblVideoTerritories_tblVideos1 | 4 | db.cv.videoID | 1 | Using where |
| 1 | SIMPLE | t_v | eq_ref | PRIMARY | PRIMARY | 4 | db.vt.territoryID | 1 | |
| 1 | SIMPLE | v | eq_ref | PRIMARY | PRIMARY | 4 | db.vt.videoID | 1 | Using where |
| 1 | SIMPLE | vk | ref | fk_tblVideoKeywords_tblVideos1 | fk_tblVideoKeywords_tblVideos1 | 4 | db.cv.videoID | 6 | |
| 1 | SIMPLE | k | eq_ref | PRIMARY | PRIMARY | 4 | db.vk.keywordID | 1 | Using index |
| 1 | SIMPLE | kl | ref | fk_tblKeywordLocalisedData_tblKeywords1 | fk_tblKeywordLocalisedData_tblKeywords1 | 4 | db.k.keywordID | 1 | |
| 1 | SIMPLE | cl | ALL | fk_tblCategoryLocalisedData_tblCategories1,fk_tblCategoryLocalisedData_tblLanguages1 | NULL | NULL | NULL | 5 | Using where; Using join buffer |
| 1 | SIMPLE | l | eq_ref | PRIMARY | PRIMARY | 4 | db.cl.languageID | 1 | Using where |
| 1 | SIMPLE | ct | ALL | fk_tblCategoryTerritories_tblCategories1,fk_tblCategoryTerritories_tblTerritories1 | NULL | NULL | NULL | 2 | Using where; Using join buffer |
| 1 | SIMPLE | vl | ALL | fk_tblVideoLocalisedData_tblLanguages1,fk_tblVideoLocalisedData_tblVideos1 | NULL | NULL | NULL | 9 | Using where; Using join buffer |
| 1 | SIMPLE | t_c | eq_ref | PRIMARY | PRIMARY | 4 | db.ct.territoryID | 1 | |
+----+-------------+-------+--------+--------------------------------------------------------------------------------------+-----------------------------------------+---------+------------------------+------+----------------------------------------------+
但是我不知道那是什么意思。我该如何解决这个问题？值得庆幸的是，我确实知道查询的哪些部分导致了大规模的减速。如果我删除从 tblVideoTerritories (vt) 到 tblTerritories (t_v) 或 tblCategoryTerritories (ct) 到 tblTerritories (t_c) 的连接，那么一切都会大大加快。我认为开始可能是因为 GROUP_CONCAT 或 DISTINCT 但我尝试删除它们并且它几乎没有任何改变。似乎性能问题是由两次连接到同一个表'tblTerritories'引起的。如果我只有其中一个连接，则查询只需要 0.1 秒或 0.2 秒即可运行——这仍然是很长的时间，但这是一个更好的开始!
我想知道的是如何解决这个性能问题？ 为什么加入同一个表两次会导致查询花费 10 倍的时间？!
感谢您的帮助!
编辑: tblVideoTerritories 上的 SHOW CREATE TABLE 给了我这个:
CREATE TABLE `tblVideoTerritories` (
`videoTerritoryID` int(10) unsigned NOT NULL AUTO_INCREMENT,
`videoID` int(10) unsigned NOT NULL,
`territoryID` int(10) unsigned NOT NULL,
PRIMARY KEY (`videoTerritoryID`),
KEY `fk_tblVideoTerritories_tblVideos1` (`videoID`),
KEY `fk_tblVideoTerritories_tblTerritories1` (`territoryID`),
CONSTRAINT `fk_tblVideoTerritories_tblTerritories1` FOREIGN KEY (`territoryID`) REFERENCES `tblTerritories` (`territoryID`) ON DELETE NO ACTION ON UPDATE NO ACTION,
CONSTRAINT `fk_tblVideoTerritories_tblVideos1` FOREIGN KEY (`videoID`) REFERENCES `tblVideos` (`videoID`) ON DELETE NO ACTION ON UPDATE NO ACTION
) ENGINE=InnoDB AUTO_INCREMENT=8 DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci
tblCategoryTerritories 上的 SHOW CREATE TABLE 给了我这个:
CREATE TABLE `tblCategoryTerritories` (
`categoryTerritoryID` int(10) unsigned NOT NULL AUTO_INCREMENT,
`categoryID` int(10) unsigned NOT NULL,
`territoryID` int(10) unsigned NOT NULL,
PRIMARY KEY (`categoryTerritoryID`),
KEY `fk_tblCategoryTerritories_tblCategories1` (`categoryID`),
KEY `fk_tblCategoryTerritories_tblTerritories1` (`territoryID`),
CONSTRAINT `fk_tblCategoryTerritories_tblCategories1` FOREIGN KEY (`categoryID`) REFERENCES `tblCategories` (`categoryID`) ON DELETE NO ACTION ON UPDATE NO ACTION,
CONSTRAINT `fk_tblCategoryTerritories_tblTerritories1` FOREIGN KEY (`territoryID`) REFERENCES `tblTerritories` (`territoryID`) ON DELETE NO ACTION ON UPDATE NO ACTION
) ENGINE=InnoDB AUTO_INCREMENT=6 DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci
在 tblTerritories 上的 SHOW CREATE TABLE 给我这个:
CREATE TABLE `tblTerritories` (
`territoryID` int(10) unsigned NOT NULL AUTO_INCREMENT,
`iso_3166_1_alpha_2` char(2) COLLATE utf8_unicode_ci DEFAULT NULL,
`iso_3166_1_alpha_3` char(3) COLLATE utf8_unicode_ci DEFAULT NULL,
`defaultLanguageID` int(10) unsigned DEFAULT NULL,
PRIMARY KEY (`territoryID`),
KEY `fk_tblTerritories_tblLanguages1` (`defaultLanguageID`),
KEY `iso_3166_1_alpha_2` (`iso_3166_1_alpha_2`),
CONSTRAINT `fk_tblTerritories_tblLanguages1` FOREIGN KEY (`defaultLanguageID`) REFERENCES `tblLanguages` (`languageID`) ON DELETE NO ACTION ON UPDATE NO ACTION
) ENGINE=InnoDB AUTO_INCREMENT=8 DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci
编辑2: 两次加入同一地区的原因是我需要在查询顶部使用 GROUP_CONCAT 生成两个单独的地区列表。我需要一个用于视频，一个用于它所属的类别。
编辑3: 有趣的是，如果我将查询缩减到最基本的程度，那么它会非常快(0.00 秒)，即使两次连接到同一个表也是如此:
SELECT `c`.`categoryID`,
`v`.`videoID`,
GROUP_CONCAT(DISTINCT t_v.iso_3166_1_alpha_2) AS `video_territories`,
GROUP_CONCAT(DISTINCT t_c.iso_3166_1_alpha_2) AS `category_territories`
FROM `tblCategories` AS `c`
LEFT JOIN `tblCategoryVideos` AS `cv` ON c.categoryID = cv.categoryID
LEFT JOIN `tblVideos` AS `v` ON cv.videoID = v.videoID
LEFT JOIN `tblVideoTerritories` AS `vt` ON vt.videoID = v.videoID
LEFT JOIN `tblCategoryTerritories` AS `ct` ON ct.categoryID = c.categoryID
INNER JOIN `tblTerritories` AS `t_v` ON t_v.territoryID = vt.territoryID
INNER JOIN `tblTerritories` AS `t_c` ON t_c.territoryID = ct.territoryID
GROUP BY `v`.`videoID`, `c`.`categoryID`
编辑4: 如果我从使用 WHERE 切换为临时打开，那么我仍然有一个需要 0.98 秒的查询:
SELECT `c`.`categoryID`,
`cl`.`name` AS `category_name`,
`v`.*,
TRUE AS `categoried`,
GROUP_CONCAT(DISTINCT t_v.iso_3166_1_alpha_2) AS `video_territories`,
GROUP_CONCAT(DISTINCT t_c.iso_3166_1_alpha_2) AS `category_territories`,
`vl`.*,
GROUP_CONCAT(DISTINCT kl.name) AS `keywords`
FROM `tblCategories` AS `c`
INNER JOIN `tblCategoryLocalisedData` AS `cl` ON c.categoryID = cl.categoryID
LEFT JOIN `tblCategoryDurations` AS `cd` ON c.categoryID = cd.categoryID
LEFT JOIN `tblCategoryRules` AS `cr` ON c.categoryID = cr.categoryID
LEFT JOIN `tblCategoryVideos` AS `cv` ON c.categoryID = cv.categoryID
LEFT JOIN `tblVideos` AS `v` ON cv.videoID = v.videoID
LEFT JOIN `tblVideoTerritories` AS `vt` ON vt.videoID = v.videoID
LEFT JOIN `tblCategoryTerritories` AS `ct` ON ct.categoryID = c.categoryID
INNER JOIN `tblTerritories` AS `t_v` ON t_v.territoryID = vt.territoryID
INNER JOIN `tblTerritories` AS `t_c` ON t_c.territoryID = ct.territoryID
INNER JOIN `tblVideoLocalisedData` AS `vl` ON vl.videoID = v.videoID
LEFT JOIN `tblVideoKeywords` AS `vk` ON v.videoID = vk.videoID
LEFT JOIN `tblKeywords` AS `k` ON vk.keywordID = k.keywordID
LEFT JOIN `tblKeywordLocalisedData` AS `kl` ON kl.keywordID = k.keywordID
INNER JOIN `tblLanguages` AS `l` ON (l.languageID = cl.languageID OR cl.languageID IS NULL) AND (l.languageID = kl.languageID OR kl.languageID IS NULL) AND (l.languageID = vl.languageID OR vl.languageID IS NULL)
WHERE (cv.disabled IS NULL)
AND (cd.start_date < NOW() OR cd.start_date IS NULL)
AND (cd.end_date > NOW() OR cd.end_date IS NULL)
AND (cr.name IS NULL) AND (l.iso_639_1 = 'en')
GROUP BY `v`.`videoID`, `c`.`categoryID`
ORDER BY `c`.`categoryID` ASC
编辑5: 如果我删除与关键字相关的连接，查询将在 0.09 秒内发生...删除 tblKeyword 和 tblKeywordLocalisedData 但保留 tblVideoKeywords 给我 0.80 秒。删除 tblVideoKeywords 给我 0.09 秒。
但它似乎有索引，所以我还是不明白:
CREATE TABLE `tblVideoKeywords` (
`videoKeywordID` int(10) unsigned NOT NULL AUTO_INCREMENT,
`videoID` int(10) unsigned NOT NULL,
`keywordID` int(10) unsigned NOT NULL,
PRIMARY KEY (`videoKeywordID`),
KEY `fk_tblVideoKeywords_tblVideos1` (`videoID`),
KEY `fk_tblVideoKeywords_tblKeywords1` (`keywordID`),
CONSTRAINT `fk_tblVideoKeywords_tblKeywords1` FOREIGN KEY (`keywordID`) REFERENCES `tblKeywords` (`keywordID`) ON DELETE NO ACTION ON UPDATE NO ACTION,
CONSTRAINT `fk_tblVideoKeywords_tblVideos1` FOREIGN KEY (`videoID`) REFERENCES `tblVideos` (`videoID`) ON DELETE NO ACTION ON UPDATE NO ACTION
) ENGINE=InnoDB AUTO_INCREMENT=18 DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci
编辑6: 使用 DRapp 提供的查询可以使一切变得更快。他查询的 EXPLAIN 现在给了我:
+----+-------------+---------+--------+--------------------------------------------------------------------------------------+-----------------------------------------+---------+------------------------+------+----------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+---------+--------+--------------------------------------------------------------------------------------+-----------------------------------------+---------+------------------------+------+----------------------------------------------+
| 1 | SIMPLE | c | index | PRIMARY | PRIMARY | 4 | NULL | 3 | Using index; Using temporary; Using filesort |
| 1 | SIMPLE | cl | ALL | fk_tblCategoryLocalisedData_tblCategories1,fk_tblCategoryLocalisedData_tblLanguages1 | NULL | NULL | NULL | 5 | Using where; Using join buffer |
| 1 | SIMPLE | lang_cl | ALL | PRIMARY | NULL | NULL | NULL | 2 | Using where; Using join buffer |
| 1 | SIMPLE | cd | ref | fk_tblCategoryDurations_tblCategories | fk_tblCategoryDurations_tblCategories | 4 | db.c.categoryID | 1 | |
| 1 | SIMPLE | cr | ref | fk_tblCategoryRules_tblCategories1 | fk_tblCategoryRules_tblCategories1 | 4 | db.c.categoryID | 1 | Using where; Not exists |
| 1 | SIMPLE | cv | ALL | fk_tblCategoryVideos_tblCategories1,fk_tblCategoryVideos_tblVideos1 | NULL | NULL | NULL | 2 | Using where; Using join buffer |
| 1 | SIMPLE | ct | ALL | fk_tblCategoryTerritories_tblCategories1,fk_tblCategoryTerritories_tblTerritories1 | NULL | NULL | NULL | 2 | Using where; Using join buffer |
| 1 | SIMPLE | t_c | eq_ref | PRIMARY | PRIMARY | 4 | db.ct.territoryID | 1 | |
| 1 | SIMPLE | v | eq_ref | PRIMARY | PRIMARY | 4 | db.cv.videoID | 1 | Using where |
| 1 | SIMPLE | vt | ref | fk_tblVideoTerritories_tblVideos1,fk_tblVideoTerritories_tblTerritories1 | fk_tblVideoTerritories_tblVideos1 | 4 | db.v.videoID | 1 | Using where |
| 1 | SIMPLE | t_v | eq_ref | PRIMARY | PRIMARY | 4 | db.vt.territoryID | 1 | |
| 1 | SIMPLE | vl | ALL | fk_tblVideoLocalisedData_tblLanguages1,fk_tblVideoLocalisedData_tblVideos1 | NULL | NULL | NULL | 9 | Using where; Using join buffer |
| 1 | SIMPLE | lang_vl | eq_ref | PRIMARY | PRIMARY | 4 | db.vl.languageID | 1 | Using where |
| 1 | SIMPLE | vk | ALL | fk_tblVideoKeywords_tblVideos1,fk_tblVideoKeywords_tblKeywords1 | NULL | NULL | NULL | 15 | Using where; Using join buffer |
| 1 | SIMPLE | k | eq_ref | PRIMARY | PRIMARY | 4 | db.vk.keywordID | 1 | Using where; Using index |
| 1 | SIMPLE | kl | ref | fk_tblKeywordLocalisedData_tblKeywords1,fk_tblKeywordLocalisedData_tblLanguages1 | fk_tblKeywordLocalisedData_tblKeywords1 | 4 | db.k.keywordID | 1 | Using where |
| 1 | SIMPLE | lang_kl | eq_ref | PRIMARY | PRIMARY | 4 | db.kl.languageID | 1 | Using where |
+----+-------------+---------+--------+--------------------------------------------------------------------------------------+-----------------------------------------+---------+------------------------+------+----------------------------------------------+
17 rows in set (0.01 sec)
最佳答案
对于我回答过的其他几个类似问题，只需添加“STRAIGHT_JOIN”和轻微的重组就可以提供帮助。查询优化器实际上会尝试为您考虑所有表，尝试找到一个记录较少的表并将其连接到较大的表，从而导致完全困惑。当我对 14+ 百万条记录进行政府数据查询并查找 15+ 个子表时发生了这种情况......与您在这里进行的非常相似。它在专用的独立服务器上运行了 30 多个小时的查询并将其挂起，缩短到不到 2 小时......尝试以下操作:
除了按照我习惯的方式对连接进行一些视觉清理/排序外，我还采用了一些 NOW() 与 NULL 并将它们移到连接中。如果您查询左连接并将日期作为连接限定符的一部分，则这些记录将被排除在外，从而留下 NULL 结果集或有效条目，无需加倍该限定符。
SELECT STRAIGHT_JOIN
c.categoryID,
cl.name AS category_name,
v.*,
TRUE AS categoried,
GROUP_CONCAT(DISTINCT t_v.iso_3166_1_alpha_2) AS video_territories,
GROUP_CONCAT(DISTINCT t_c.iso_3166_1_alpha_2) AS category_territories,
vl.*,
GROUP_CONCAT(DISTINCT kl.name) AS keywords
FROM
tblCategories AS c
INNER JOIN tblCategoryLocalisedData AS cl
ON c.categoryID = cl.categoryID
INNER JOIN tblLanguages AS lang_cl
ON l.languageID = lang_cl.languageID
AND lang_cl.iso_639_1 = 'en'
LEFT JOIN tblCategoryDurations AS cd
ON c.categoryID = cd.categoryID
AND cd.start_date < NOW()
AND cd.end_date > NOW()
LEFT JOIN tblCategoryRules AS cr
ON c.categoryID = cr.categoryID
LEFT JOIN tblCategoryVideos AS cv
ON c.categoryID = cv.categoryID
LEFT JOIN tblCategoryTerritories AS ct
ON c.categoryID = ct.categoryID
INNER JOIN tblTerritories AS t_c
ON ct.territoryID = t_c.territoryID
LEFT JOIN tblVideos AS v
ON cv.videoID = v.videoID
LEFT JOIN tblVideoTerritories AS vt
ON v.videoID = vt.videoID
INNER JOIN tblTerritories AS t_v
ON vt.territoryID = t_v.territoryID
INNER JOIN tblVideoLocalisedData AS vl
ON v.videoID = vl.videoID
INNER JOIN tblLanguages AS lang_vl
ON vl.languageID = lang_vl.languageID
AND lang_vl.iso_639_1 = 'en'
LEFT JOIN tblVideoKeywords AS vk
ON v.videoID = vk.videoID
LEFT JOIN tblKeywords AS k
ON vk.keywordID = k.keywordID
LEFT JOIN tblKeywordLocalisedData AS kl
ON k.keywordID = kl.keywordID
INNER JOIN tblLanguages AS lang_kl
ON kl.languageID = lang_kl.languageID
AND lang_kl.iso_639_1 = 'en'
WHERE
( cv.disabled IS NULL)
AND ( cr.name IS NULL)
GROUP BY
v.videoID,
c.categoryID
ORDER BY
c.categoryID ASC
STRAIGHT_JOIN 正如我在上面解释的，基本上告诉优化器，“不要为我考虑”......按照我告诉你的顺序执行查询。在这种情况下，使用“tblCategories”作为主表并将其他所有内容链接起来。优化器，即使有解释，也可能会尝试变慢，并在您下次运行查询时尝试不同的方法。因此，它可以首先尝试使用 Languages 表，然后通过其他表进行后退并阻塞。此外，通过将诸如日期之类的“AND”部分直接指向那些左连接，这些连接简化了 WHERE，如您所见...就像您在 NULL 的位置或它存在的地方一样，只是应用于该特定连接。 . 保持清洁。
此外，通过保持关系直接并缩进到它们所加入的内容，更容易理解什么链接到哪里...
我还想看看最后的“EXPLAIN”，看看它会带来什么。
关于sql - 慢 SQL 查询 : using the same table in two different joins causes query to become 10x slower!，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/4808050/