时间:2020-11-03 13:42 作者:admin610456

前言

mysql/' target='_blank'>mysql在2016年仍然保持强劲的数据库流行度增长趋势。越来越多的客户将自己的应用建立在MySQL数据库之上，甚至是从Oracle迁移到MySQL上来。但也存在部分客户在使用MySQL数据库的过程中遇到一些比如响应时间慢，CPU打满等情况。

阿里云RDS专家服务团队帮助云上客户解决过很多紧急问题。现将《ApsaraDB专家诊断报告》中出现的部分常见SQL问题总结如下，供大家参考。

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：

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 |+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+

关于 MySQL 外部条件不能下推的详细解释说明请参考文章：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 DESClimit 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 。

好了，以上就是这篇文章的全部内容了，希望本文的内容对大家的学习或者工作具有一定的参考学习价值，谢谢大家对脚本之家的支持。

(责任编辑：admin)