MySQL · 性能优化 · MySQL常见SQL错误用法

时间:2023-02-12 09:32:57

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

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

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

9、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 。