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>

1、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。

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
     > 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。

3、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 |
+----+-------------+-------+------+---------------+-------+---------+-------+------+-----------------------------------------------------+

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;

5、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           | +----+-------------+-------+--------+ -----+------------------------------------------+---------+ -----+------+ -----+

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：

1、聚合子查询；2、含有 LIMIT 的子查询；3、UNION 或 UNION ALL 子查询；4、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 | +----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+

关于 MySQL 外部条件不能下推的详细解释说明请参考以前文章：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 |
+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+

8、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。

8 种最坑SQL语法，工作中踩过吗？ 2022-05-30 14:11·Java架构师追风