这几种SQL错误用法，你中招了吗
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2021-09-12 21:29
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语句分页查询是最常用的场景之一，但也通常也是最容易出问题的地方。比如对于下面简单的语句，一般 DBA 想到的办法是在 type, name, create_time 字段上加组合索引。这样条件排序都能有效的利用到索引，性能迅速提升。
SELECT * FROM operation WHERE type = \'SQLStats\' AND name = \'SlowLog\' ORDER BY create_time LIMIT 1000, 10;
好吧，可能90%以上的 DBA 解决该问题就到此为止。但当 LIMIT 子句变成 “LIMIT 1000000,10” 时，程序员仍然会抱怨：我只取10条记录为什么还是慢？要知道数据库也并不知道第1000000条记录从什么地方开始，即使有索引也需要从头计算一次。出现这种性能问题，多数情形下是程序员偷懒了。在前端数据浏览翻页，或者大数据分批导出等场景下，是可以将上一页的最大值当成参数作为查询条件的。SQL 重新设计如下：
SELECT * FROM operation WHERE type = \'SQLStats\' AND name = \'SlowLog\' AND create_time > \'2017-03-16 14:00:00\' ORDER BY create_time limit 10;
在新设计下查询时间基本固定，不会随着数据量的增长而发生变化。
SQL语句中查询变量和字段定义类型不匹配是另一个常见的错误。比如下面的语句：
mysql> explain extended SELECT * > FROM my_balance b > WHERE b.bpn = 14000000123 > AND b.isverified IS NULL ;mysql> show warnings;| Warning | 1739 | Cannot use ref access on index \'bpn\' due to type or collation conversion on field \'bpn\'
其中字段 bpn 的定义为 varchar(20)，MySQL 的策略是将字符串转换为数字之后再比较。函数作用于表字段，索引失效。上述情况可能是应用程序框架自动填入的参数，而不是程序员的原意。现在应用框架很多很繁杂，使用方便的同时也小心它可能给自己挖坑。
虽然 MySQL5.6 引入了物化特性，但需要特别注意它目前仅仅针对查询语句的优化。对于更新或删除需要手工重写成 JOIN。比如下面 UPDATE 语句，MySQL 实际执行的是循环/嵌套子查询（DEPENDENT SUBQUERY)，其执行时间可想而知。
UPDATE operation o SET status = \'applying\' WHERE o.id IN (SELECT id FROM (SELECT o.id, o.status FROM operation o WHERE o.group = 123 AND o.status NOT IN ( \'done\' ) ORDER BY o.parent, o.id LIMIT 1) t);
执行计划：
+----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+| 1 | PRIMARY | o | index | | PRIMARY | 8 | | 24 | Using where; Using temporary || 2 | DEPENDENT SUBQUERY | | | | | | | | Impossible WHERE noticed after reading const tables || 3 | DERIVED | o | ref | idx_2,idx_5 | idx_5 | 8 | const | 1 | Using where; Using filesort |+----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+
重写为 JOIN 之后，子查询的选择模式从 DEPENDENT SUBQUERY 变成 DERIVED，执行速度大大加快，从7秒降低到2毫秒
UPDATE operation o JOIN (SELECT o.id, o.status FROM operation o WHERE o.group = 123 AND o.status NOT IN ( \'done\' ) ORDER BY o.parent, o.id LIMIT 1) t ON o.id = t.id SET status = \'applying\'
执行计划简化为：
+----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+| 1 | PRIMARY | | | | | | | | Impossible WHERE noticed after reading const tables || 2 | DERIVED | o | ref | idx_2,idx_5 | idx_5 | 8 | const | 1 | Using where; Using filesort |+----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+
MySQL 不能利用索引进行混合排序。但在某些场景，还是有机会使用特殊方法提升性能的。
SELECT * FROM my_order o INNER JOIN my_appraise a ON a.orderid = o.id ORDER BY a.is_reply ASC, a.appraise_time DESC LIMIT 0, 20
执行计划显示为全表扫描：
+----+-------------+-------+--------+-------------+---------+---------+---------------+---------+-+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra +----+-------------+-------+--------+-------------+---------+---------+---------------+---------+-+| 1 | SIMPLE | a | ALL | idx_orderid | NULL | NULL | NULL | 1967647 | Using filesort || 1 | SIMPLE | o | eq_ref | PRIMARY | PRIMARY | 122 | a.orderid | 1 | NULL |+----+-------------+-------+--------+---------+---------+---------+-----------------+---------+-+
由于 is_reply 只有0和1两种状态，我们按照下面的方法重写后，执行时间从1.58秒降低到2毫秒。
SELECT * FROM ((SELECT * FROM my_order o INNER JOIN my_appraise a ON a.orderid = o.id AND is_reply = 0 ORDER BY appraise_time DESC LIMIT 0, 20) UNION ALL (SELECT * FROM my_order o INNER JOIN my_appraise a ON a.orderid = o.id AND is_reply = 1 ORDER BY appraise_time DESC LIMIT 0, 20)) t ORDER BY is_reply ASC, appraisetime DESC LIMIT 20;
MySQL 对待 EXISTS 子句时，仍然采用嵌套子查询的执行方式。如下面的 SQL 语句：
SELECT *FROM my_neighbor n LEFT JOIN my_neighbor_apply sra ON n.id = sra.neighbor_id AND sra.user_id = \'xxx\' WHERE n.topic_status < 4 AND EXISTS(SELECT 1 FROM message_info m WHERE n.id = m.neighbor_id AND m.inuser = \'xxx\') AND n.topic_type <> 5
执行计划为：
+----+--------------------+-------+------+-----+------------------------------------------+---------+-------+---------+ -----+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+--------------------+-------+------+ -----+------------------------------------------+---------+-------+---------+ -----+| 1 | PRIMARY | n | ALL | | NULL | NULL | NULL | 1086041 | Using where || 1 | PRIMARY | sra | ref | | idx_user_id | 123 | const | 1 | Using where || 2 | DEPENDENT SUBQUERY | m | ref | | idx_message_info | 122 | const | 1 | Using index condition; Using where |+----+--------------------+-------+------+ -----+------------------------------------------+---------+-------+---------+ -----+
去掉 exists 更改为 join，能够避免嵌套子查询，将执行时间从1.93秒降低为1毫秒。
SELECT *FROM my_neighbor n INNER JOIN message_info m ON n.id = m.neighbor_id AND m.inuser = \'xxx\' LEFT JOIN my_neighbor_apply sra ON n.id = sra.neighbor_id AND sra.user_id = \'xxx\' WHERE n.topic_status < 4 AND n.topic_type <> 5
新的执行计划：
+----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+| 1 | SIMPLE | m | ref | | idx_message_info | 122 | const | 1 | Using index condition || 1 | SIMPLE | n | eq_ref | | PRIMARY | 122 | ighbor_id | 1 | Using where || 1 | SIMPLE | sra | ref | | idx_user_id | 123 | const | 1 | Using where |+----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+
外部查询条件不能够下推到复杂的视图或子查询的情况有：聚合子查询；含有 LIMIT 的子查询；UNION 或 UNION ALL 子查询；输出字段中的子查询；如下面的语句，从执行计划可以看出其条件作用于聚合子查询之后 ：
SELECT * FROM (SELECT target, Count(*) FROM operation GROUP BY target) t WHERE target = \'rm-xxxx\' +----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+| 1 | PRIMARY | | ref | | | 514 | const | 2 | Using where || 2 | DERIVED | operation | index | idx_4 | idx_4 | 519 | NULL | 20 | Using index |+----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+
确定从语义上查询条件可以直接下推后，重写如下：
SELECT target, Count(*) FROM operation WHERE target = \'rm-xxxx\' GROUP BY target
执行计划变为：
+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+| 1 | SIMPLE | operation | ref | idx_4 | idx_4 | 514 | const | 1 | Using where; Using index |+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+
先上初始 SQL 语句：
SELECT * FROM my_order o LEFT JOIN my_userinfo u ON o.uid = u.uid LEFT JOIN my_productinfo p ON o.pid = p.pid WHERE ( o.display = 0 ) AND ( o.ostaus = 1 ) ORDER BY o.selltime DESC LIMIT 0, 15
该SQL语句原意是：先做一系列的左连接，然后排序取前15条记录。从执行计划也可以看出，最后一步估算排序记录数为90万，时间消耗为12秒。
+----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+| 1 | SIMPLE | o | ALL | NULL | NULL | NULL | NULL | 909119 | Using where; Using temporary; Using filesort || 1 | SIMPLE | u | eq_ref | PRIMARY | PRIMARY | 4 | o.uid | 1 | NULL || 1 | SIMPLE | p | ALL | PRIMARY | NULL | NULL | NULL | 6 | Using where; Using join buffer (Block Nested Loop) |+----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+
由于最后 WHERE 条件以及排序均针对最左主表，因此可以先对 my_order 排序提前缩小数据量再做左连接。SQL 重写后如下，执行时间缩小为1毫秒左右。
SELECT * FROM (SELECT * FROM my_order o WHERE ( o.display = 0 ) AND ( o.ostaus = 1 ) ORDER BY o.selltime DESC LIMIT 0, 15) o LEFT JOIN my_userinfo u ON o.uid = u.uid LEFT JOIN my_productinfo p ON o.pid = p.pid ORDER BY o.selltime DESClimit 0, 15
再检查执行计划：子查询物化后（select_type=DERIVED)参与 JOIN。虽然估算行扫描仍然为90万，但是利用了索引以及 LIMIT 子句后，实际执行时间变得很小。
+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+| 1 | PRIMARY | | ALL | NULL | NULL | NULL | NULL | 15 | Using temporary; Using filesort || 1 | PRIMARY | u | eq_ref | PRIMARY | PRIMARY | 4 | o.uid | 1 | NULL || 1 | PRIMARY | p | ALL | PRIMARY | NULL | NULL | NULL | 6 | Using where; Using join buffer (Block Nested Loop) || 2 | DERIVED | o | index | NULL | idx_1 | 5 | NULL | 909112 | Using where |+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+
再来看下面这个已经初步优化过的例子(左连接中的主表优先作用查询条件)：
SELECT a.*, c.allocated FROM ( SELECT resourceid FROM my_distribute d WHERE isdelete = 0 AND cusmanagercode = \'1234567\' ORDER BY salecode limit 20) a LEFT JOIN ( SELECT resourcesid， sum(ifnull(allocation, 0) * 12345) allocated FROM my_resources GROUP BY resourcesid) c ON a.resourceid = c.resourcesid
那么该语句还存在其它问题吗？不难看出子查询 c 是全表聚合查询，在表数量特别大的情况下会导致整个语句的性能下降。其实对于子查询 c，左连接最后结果集只关心能和主表 resourceid 能匹配的数据。因此我们可以重写语句如下，执行时间从原来的2秒下降到2毫秒。
SELECT a.*, c.allocated FROM ( SELECT resourceid FROM my_distribute d WHERE isdelete = 0 AND cusmanagercode = \'1234567\' ORDER BY salecode limit 20) a LEFT JOIN ( SELECT resourcesid， sum(ifnull(allocation, 0) * 12345) allocated FROM my_resources r, ( SELECT resourceid FROM my_distribute d WHERE isdelete = 0 AND cusmanagercode = \'1234567\' ORDER BY salecode limit 20) a WHERE r.resourcesid = a.resourcesid GROUP BY resourcesid) c ON a.resourceid = c.resourcesid
但是子查询 a 在我们的SQL语句中出现了多次。这种写法不仅存在额外的开销，还使得整个语句显的繁杂。使用 WITH 语句再次重写：
总结数据库编译器产生执行计划，决定着SQL的实际执行方式。但是编译器只是尽力服务，所有数据库的编译器都不是尽善尽美的。上述提到的多数场景，在其它数据库中也存在性能问题。了解数据库编译器的特性，才能避规其短处，写出高性能的SQL语句。程序员在设计数据模型以及编写SQL语句时，要把算法的思想或意识带进来。编写复杂SQL语句要养成使用 WITH 语句的习惯。简洁且思路清晰的SQL语句也能减小数据库的负担 。
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