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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 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：
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) 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 |
+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+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.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 DESC
limit 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.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.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.allocated
FROM a
LEFT JOIN
(SELECT resourcesid，sum(ifnull(allocation, 0) * 12345) allocated
FROM my_resources r,
a
WHERE r.resourcesid = a.resourcesid
GROUP BY resourcesid) c
ON 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
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