MySQL · 性能优化 · MySQL常见SQL错误用法

时间 2019-11-06

标签 mysql 性能优化常见 sql 错误用法栏目 MySQL 繁體版

原文原文链接

1. LIMIT 语句

分页查询是最经常使用的场景之一，但也一般也是最容易出问题的地方。好比对于下面简单的语句，通常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，性能迅速提高。前端

SELECT * 
FROM   operation 
WHERE  type = 'SQLStats' 
       AND name = 'SlowLog' 
ORDER  BY create_time 
LIMIT  1000, 10; 
复制代码

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条记录为何仍是慢？mysql

要知道数据库也并不知道第1000000条记录从什么地方开始，即便有索引也须要从头计算一次。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，是能够将上一页的最大值当成参数做为查询条件的。SQL从新设计以下：程序员

SELECT   * 
FROM     operation 
WHERE    type = 'SQLStats' 
AND      name = 'SlowLog' 
AND      create_time > '2017-03-16 14:00:00' 
ORDER BY create_time limit 10;
复制代码

在新设计下查询时间基本固定，不会随着数据量的增加而发生变化。算法

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外一个常见的错误。好比下面的语句：sql

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'
复制代码

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以后再比较。函数做用于表字段，索引失效。数据库

上述状况多是应用程序框架自动填入的参数，而不是程序员的原意。如今应用框架不少很繁杂，使用方便的同时也当心它可能给本身挖坑。bash

3. 关联更新、删除

虽然MySQL5.6引入了物化特性，但须要特别注意它目前仅仅针对查询语句的优化。对于更新或删除须要手工重写成JOIN。app

好比下面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。框架

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); 
复制代码

执行计划：函数

+----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+
| 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                         |
+----+--------------------+-------+-------+---------------+---------+---------+-------+------+-----------------------------------------------------+
复制代码

肯定从语义上查询条件能够直接下推后，重写以下：

SELECT target, 
       Count(*) 
FROM   operation 
WHERE  target = 'rm-xxxx' 
GROUP  BY target
复制代码

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 |
+----+-------------+-----------+------+---------------+-------+---------+-------+------+--------------------+
复制代码

7. 提早缩小范围

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 
复制代码

该SQL语句原意是：先作一系列的左链接，而后排序取前15条记录。从执行计划也能够看出，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) |
+----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+
复制代码

因为最后WHERE条件以及排序均针对最左主表，所以能够先对my_order排序提早缩小数据量再作左链接。SQL重写后以下，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
复制代码

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，可是利用了索引以及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                                        |
+----+-------------+------------+--------+---------------+---------+---------+-------+--------+----------------------------------------------------+
复制代码

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(左链接中的主表优先做用查询条件)：

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
复制代码

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，在表数量特别大的状况下会致使整个语句的性能降低。

其实对于子查询 c，左链接最后结果集只关心能和主表resourceid能匹配的数据。所以咱们能够重写语句以下，执行时间从原来的2秒降低到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
复制代码

可是子查询 a 在咱们的SQL语句中出现了屡次。这种写法不只存在额外的开销，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
复制代码

九、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。可是编译器只是尽力服务，全部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语句也能减少数据库的负担。