位置: IT常识 - 正文
推荐整理分享这几个SQL语法的坑,你踩过吗(这几个sql语法的区别),希望有所帮助,仅作参考,欢迎阅读内容。
文章相关热门搜索词:sql语法有哪些,这几个sql语法的关键词,这几个sql语法的特点,这几个sql语法的区别,sql语法范例大全,这几个sql语法的特点,这几个sql语法的特点,这几个sql语法的关键词,内容如对您有帮助,希望把文章链接给更多的朋友!
本文已经收录到Github仓库,该仓库包含计算机基础、Java基础、多线程、JVM、数据库、Redis、Spring、Mybatis、SpringMVC、SpringBoot、分布式、微服务、设计模式、架构、校招社招分享等核心知识点,欢迎star~
Github地址:https://github.com/Tyson0314/Java-learning
大家好,我是大彬~
今天给大家分享几个SQL常见的“坏毛病”及优化技巧。
SQL语句的执行顺序:
[外链图片转存失败,源站可能有防盗链机制,建议将图片保存下来直接上传(img-fy3iB43Z-1679581232719)(http://img.topjavaer.cn/img/sql优化1.png)]
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 operationWHERE type = 'SQLStats' AND name = 'SlowLog'ORDER BY create_timeLIMIT 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 operationWHERE 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。
面试网站
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 oSET 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.idSET 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.idORDER BY a.is_reply ASC, a.appraise_time DESCLIMIT 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)) tORDER BY is_reply ASC, appraisetime DESCLIMIT 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:
1、聚合子查询;
2、含有 LIMIT 的子查询;
3、UNION 或 UNION ALL 子查询;
4、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) tWHERE 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 operationWHERE 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 http://mysql.taobao.org/monthly/2016/07/08
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.pidWHERE ( o.display = 0 ) AND ( o.ostaus = 1 )ORDER BY o.selltime DESCLIMIT 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 oWHERE ( o.display = 0 ) AND ( o.ostaus = 1 )ORDER BY o.selltime DESCLIMIT 0, 15) o LEFT JOIN my_userinfo u ON o.uid = u.uid LEFT JOIN my_productinfo p ON o.pid = p.pidORDER BY o.selltime DESClimit 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.allocatedFROM ( SELECT resourceid FROM my_distribute d WHERE isdelete = 0 AND cusmanagercode = '1234567' ORDER BY salecode limit 20) aLEFT JOIN ( SELECT resourcesid, sum(ifnull(allocation, 0) * 12345) allocated FROM my_resources GROUP BY resourcesid) cON 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.allocatedFROM ( SELECT resourceid FROM my_distribute d WHERE isdelete = 0 AND cusmanagercode = '1234567' ORDER BY salecode limit 20) aLEFT 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) cON 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.allocatedFROM aLEFT JOIN ( SELECT resourcesid, sum(ifnull(allocation, 0) * 12345) allocated FROM my_resources r, a WHERE r.resourcesid = a.resourcesid GROUP BY resourcesid) cON 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 。
面试网站
最后给大家分享一个Github仓库,上面有大彬整理的300多本经典的计算机书籍PDF,包括C语言、C++、Java、Python、前端、数据库、操作系统、计算机网络、数据结构和算法、机器学习、编程人生等,可以star一下,下次找书直接在上面搜索,仓库持续更新中~
Github地址:https://github.com/Tyson0314/java-books
上一篇:ES6中 Promise 概念、基本用法和封装ajax(json数据使用)(es6 promise是什么)
下一篇:Opencv实战——图像拼接(opencv官方教程)
友情链接: 武汉网站建设