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明天给大家分享几个SQL常见的“坏毛病”及优化技巧。
SQL语句的执行程序：
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1、LIMIT 语句
分页查问是最罕用的场景之一，但也通常也是最容易出问题的中央。比方对于上面简略的语句，个别 DBA 想到的方法是在 type, name, create_time 字段上加组合索引。这样条件排序都能无效的利用到索引，性能迅速晋升。
SELECT *FROM operationWHERE type = 'SQLStats' AND name = 'SlowLog'ORDER BY create_timeLIMIT 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，程序员依然会埋怨：我只取10条记录为什么还是慢？
要晓得数据库也并不知道第1000000条记录从什么中央开始，即便有索引也须要从头计算一次。呈现这种性能问题，少数情景下是程序员偷懒了。
在前端数据浏览翻页，或者大数据分批导出等场景下，是能够将上一页的最大值当成参数作为查问条件的。SQL 从新设计如下：
SELECT *FROM operationWHERE type = 'SQLStats'AND name = 'SlowLog'AND create_time > '2017-03-16 14:00:00'ORDER BY create_time limit 10;在新设计下查问工夫根本固定，不会随着数据量的增长而发生变化。
2、隐式转换
SQL语句中查问变量和字段定义类型不匹配是另一个常见的谬误。比方上面的语句：
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拟。函数作用于表字段，索引生效。
上述情况可能是应用程序框架主动填入的参数，而不是程序员的原意。当初利用框架很多很繁冗，使用方便的同时也小心它可能给本人挖坑。
3、关联更新、删除
尽管 MySQL5.6 引入了物化个性，但须要特地留神它目前仅仅针对查问语句的优化。对于更新或删除须要手工重写成 JOIN。
比方上面 UPDATE 语句，MySQL 理论执行的是循环/嵌套子查问（DEPENDENT SUBQUERY)，其执行工夫可想而知。
UPDATE operation oSET 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);执行打算：
+----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+| 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，子查问的抉择模式从 DEPENDENT SUBQUERY 变成 DERIVED，执行速度大大放慢，从7秒升高到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.idSET status = 'applying'执行打算简化为：
+----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+| 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 |+----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+4、混合排序
MySQL 不能利用索引进行混合排序。但在某些场景，还是有机会应用非凡办法晋升性能的。
SELECT *FROM my_order o INNER JOIN my_appraise a ON a.orderid = o.idORDER BY a.is_reply ASC, a.appraise_time DESCLIMIT 0, 20执行打算显示为全表扫描：
+----+-------------+-------+--------+-------------+---------+---------+---------------+---------+-+| 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 |+----+-------------+-------+--------+---------+---------+---------+-----------------+---------+-+因为 is_reply 只有0和1两种状态，咱们依照上面的办法重写后，执行工夫从1.58秒升高到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)) tORDER BY is_reply ASC, appraisetime DESCLIMIT 20;5、EXISTS语句
MySQL 看待 EXISTS 子句时，依然采纳嵌套子查问的执行形式。如上面的 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执行打算为：
+----+--------------------+-------+------+-----+------------------------------------------+---------+-------+---------+ -----+| 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，可能防止嵌套子查问，将执行工夫从1.93秒升高为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新的执行打算：
+----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+| 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 |+----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+6、条件下推
内部查问条件不可能下推到简单的视图或子查问的状况有：
1、聚合子查问；
2、含有 LIMIT 的子查问；
3、UNION 或 UNION ALL 子查问；
4、输入字段中的子查问；
如上面的语句，从执行打算能够看出其条件作用于聚合子查问之后：
SELECT *FROM (SELECT target, Count(*) FROM operation GROUP BY target) tWHERE target = 'rm-xxxx'+----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+| 1 | PRIMARY | <derived2> | ref | <auto_key0> | <auto_key0> | 514 | const | 2 | Using where || 2 | DERIVED | operation | index | idx_4 | idx_4 | 519 | NULL | 20 | Using index |+----+-------------+------------+-------+---------------+-------------+---------+-------+------+-------------+确定从语义上查问条件能够间接下推后，重写如下：
SELECT target, Count(*)FROM operationWHERE target = 'rm-xxxx'GROUP BY target执行打算变为：
+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+| 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 |+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+对于 MySQL 内部条件不能下推的具体解释阐明请参考以前文章：MySQL · 性能优化 · 条件下推到物化表 http://mysql.taobao.org/monthly/2016/07/08
7、提前放大范畴
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.pidWHERE ( o.display = 0 ) AND ( o.ostaus = 1 )ORDER BY o.selltime DESCLIMIT 0, 15该SQL语句原意是：先做一系列的左连贯，而后排序取前15条记录。从执行打算也能够看出，最初一步估算排序记录数为90万，工夫耗费为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) |+----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+因为最初 WHERE 条件以及排序均针对最左主表，因而能够先对 my_order 排序提前放大数据量再做左连贯。SQL 重写后如下，执行工夫放大为1毫秒左右。
SELECT *FROM (SELECT *FROM my_order oWHERE ( o.display = 0 ) AND ( o.ostaus = 1 )ORDER BY o.selltime DESCLIMIT 0, 15) o LEFT JOIN my_userinfo u ON o.uid = u.uid LEFT JOIN my_productinfo p ON o.pid = p.pidORDER BY o.selltime DESClimit 0, 15再查看执行打算：子查问物化后（select_type=DERIVED)参加 JOIN。尽管估算行扫描依然为90万，然而利用了索引以及 LIMIT 子句后，理论执行工夫变得很小。
+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+| 1 | PRIMARY | <derived2> | 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 |+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+8、两头后果集下推
再来看上面这个曾经初步优化过的例子(左连贯中的主表优先作用查问条件)：
SELECT a.*, c.allocatedFROM ( SELECT resourceid FROM my_distribute d WHERE isdelete = 0 AND cusmanagercode = '1234567' ORDER BY salecode limit 20) aLEFT JOIN ( SELECT resourcesid， sum(ifnull(allocation, 0) * 12345) allocated FROM my_resources GROUP BY resourcesid) cON a.resourceid = c.resourcesid那么该语句还存在其它问题吗？不难看出子查问 c 是全表聚合查问，在表数量特地大的状况下会导致整个语句的性能降落。
其实对于子查问 c，左连贯最初后果集只关怀能和主表 resourceid 能匹配的数据。因而咱们能够重写语句如下，执行工夫从原来的2秒降落到2毫秒。
SELECT a.*, c.allocatedFROM ( SELECT resourceid FROM my_distribute d WHERE isdelete = 0 AND cusmanagercode = '1234567' ORDER BY salecode limit 20) aLEFT 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) cON a.resourceid = c.resourcesid然而子查问 a 在咱们的SQL语句中呈现了屡次。这种写法不仅存在额定的开销，还使得整个语句显的繁冗。应用 WITH 语句再次重写：
WITH a AS( SELECT resourceid FROM my_distribute d WHERE isdelete = 0 AND cusmanagercode = '1234567' ORDER BY salecode limit 20)SELECT a.*, c.allocatedFROM aLEFT JOIN ( SELECT resourcesid， sum(ifnull(allocation, 0) * 12345) allocated FROM my_resources r, a WHERE r.resourcesid = a.resourcesid GROUP BY resourcesid) cON a.resourceid = c.resourcesid总结
数据库编译器产生执行打算，决定着SQL的理论执行形式。然而编译器只是尽力服务，所有数据库的编译器都不是尽如人意的。
上述提到的少数场景，在其它数据库中也存在性能问题。理解数据库编译器的个性，能力避规其短处，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，要把算法的思维或意识带进来。
编写简单SQL语句要养成应用 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累赘 。
起源：yq.aliyun.com/articles/72501