风景区网站建设论文范文,营销型网站搭建,石家庄网络推广建站,淘宝seo搜索排名优化来源 | yq.aliyun.com/articles/72501MySQL 在近几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#xff0c;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#xff0c… 来源 | yq.aliyun.com/articles/72501MySQL 在近几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) tON 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以前文章MySQL · 性能优化 · 条件下推到物化表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.uidLEFT 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_typeDERIVED)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
AliSQL即将推出WITH语法敬请期待。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。
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