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/month...

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 。