8 种常被忽视的 SQL 错误用法
sql语句的执行顺序：
FROM
< left_table > ON < join_condition > < join_type >
JOIN < right_table >
WHERE
< where_condition >
GROUP BY
< group_by_list >
HAVING
< having_condition > SELECT DISTINCT
< select_list >
ORDER BY
< order_by_condition >
LIMIT < limit_number >
一、LIMIT 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。
二、隐式转换
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。
三、关联更新、删除
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 |
+----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+
四、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;
五、EXISTS语句
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 |
+----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+
六、条件下推
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 | <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 |
+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+
七、提前缩小范围
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 DESC
LIMIT 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 | <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 |
+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+
八、中间结果集下推
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：
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 。
