MySQL · 性能优化 · MySQL常见SQL错误用法

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。

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条记录为何仍是慢？

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：

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加而发生变化。

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外一个常见的错误。好比下面的语句：

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以后再比较。函数做用于表字段，索引失效。

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。

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。

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。

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

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 

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 

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) | +----+-------------+-------+--------+---------------+---------+---------+-----------------+--------+----------------------------------------------------+ 

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 

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

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 

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 

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 

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 。