常见的错误SQL用法
1，LIMIT语句
对于下面简单的语句，一般DBA认为的方法是在类型，名称，create_time上下上组合索引。能有效的利用到索引，性能迅速提升。
SELECT *
FROM operation
WHEREtype = 'SQLStats'
AND name = 'SlowLog'
ORDERBY create_time
LIMIT1000, 10;
好吧，可能90％以上的DBA解决该问题就到此为止。但是当LIMIT子句变成“ LIMIT 1000000,10”时，程序员仍然会延迟：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百万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。
在重新数据浏览翻页，或者大数据分批添加等场景下，是可以将上一页的完全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。
2，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
> WHEREb.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'
其中片段bpn的定义为varchar（20），MySQL的策略是将串行转换为数字之后再比较。函数作用于表变量，索引无效。
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。
3，关联更新，删除
虽然MySQL5.6约会了物化特性，但需要特别注意它总体上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。
例如下面的一条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'
WHEREo.id IN (SELECT id
FROM (SELECT o.id,
o.status
FROM operation o
WHEREo.group = 123
AND o.status NOT IN ( 'done' )
ORDERBY o.parent,
o.id
LIMIT1) 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 |
+----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+
改为为JOIN之后，子查询的选择模式从DEPENDENT子查询转换为DERIVED，执行速度大大加快，从7秒降低到2秒钟。
UPDATE operation o
JOIN(SELECT o.id,
o.status
FROM operation o
WHEREo.group = 123
AND o.status NOT IN ( 'done' )
ORDERBY o.parent,
o.id
LIMIT1) 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 |
+----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+
4，混合排序
MySQL不能利用索引进行混合排序。但在某些场景下，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
ORDERBY a.is_reply ASC,
a.appraise_time DESC
LIMIT0, 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1两个状态，我们按照下面的方法重写后，执行时间从1.58秒降低到2秒钟。
SELECT *
FROM ((SELECT *
FROM my_order o
INNER JOIN my_appraise a
ON a.orderid = o.id
AND is_reply = 0
ORDERBY appraise_time DESC
LIMIT0, 20)
UNION ALL
(SELECT *
FROM my_order o
INNER JOIN my_appraise a
ON a.orderid = o.id
AND is_reply = 1
ORDERBY appraise_time DESC
LIMIT0, 20)) t
ORDERBYis_reply ASC,
appraisetime DESC
LIMIT20;
5，EXISTS语句
MySQL处理EXISTS子句时，仍采用交替子查询的执行方式。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'
WHEREn.topic_status < 4
AND EXISTS(SELECT 1
FROM message_info m
WHEREn.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 |
+----+--------------------+-------+------+ -----+------------------------------------------+---------+----
去掉存在更改为join，能够避免重叠子查询，将执行时间从1.93秒降低为1秒钟。
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'
WHEREn.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 |
+----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+
6，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;
包含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
GROUPBY target) t
WHEREtarget = 'rm-xxxx'
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
WHEREtarget = 'rm-xxxx'
GROUPBY 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 |
+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+
7，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 )
ORDERBY o.selltime DESC
LIMIT0, 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左右左右。
SELECT *
FROM (
SELECT *
FROM my_order o
WHERE( o.display = 0 )
AND ( o.ostaus = 1 )
ORDERBY o.selltime DESC
LIMIT0, 15
) o
LEFT JOIN my_userinfo u
ON o.uid = u.uid
LEFT JOIN my_productinfo p
ON o.pid = p.pid
ORDER BYo.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 |
+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+
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他问题吗？不严重出子查询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。因此我们可以重新编写语句如下，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
但是子查询在我们的SQL语句中出现了多次。这种写法已经存在额外的开销，还整个整个语句显的繁杂。使用WITH语句再次替换：
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。
编写且复杂的SQL语句也能解析数据库的负担。
页:
[1]