明天来分享几个MySQL常见的SQL谬误（不当）用法。咱们在作为一个初学者时，很有可能本人在写SQL时也没有留神到这些问题，导致写进去的SQL语句效率低下，所以咱们也能够自省自检一下。
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 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 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 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.id SET 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.id ORDER BY a.is_reply ASC, a.appraise_time DESC LIMIT 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)) t ORDER BY is_reply ASC, appraisetime DESC LIMIT 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：
- 聚合子查问；
- 含有LIMIT的子查问；
- UNION 或UNION ALL子查问；
- 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) t WHERE 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 operation WHERE 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 |+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+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.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 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 |+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+留言说一说，你已经在 SQL 上犯过的错！
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