做网站推广的,网站不公开简历做家教,wordpress模板知更鸟,做网站需要哪些程序1、LIMIT 语句 2、隐式转换 3、关联更新、删除 4、混合排序 5、EXISTS语句 6、条件下推 7、提前缩小范围 8、中间结果集下推 总结 sql语句的执行顺序#xff1a;
FROM
left_tableON
join_conditionjoin_typeJOIN
right_tableWHEREFROM
left_tableON
join_conditionjoin_typeJOIN
right_tableWHERE
where_conditionGROUP BY
group_by_listHAVING
having_conditionSELECTDISTINCT
select_listORDER BY
order_by_conditionLIMIT
limit_number1、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 SQLStatsAND 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 idFROM (SELECT o.id,o.statusFROM operation oWHERE o.group 123AND o.status NOT IN ( done )ORDER BY o.parent,o.idLIMIT 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 oJOIN (SELECT o.id,o.statusFROM operation oWHERE o.group 123AND o.status NOT IN ( done )ORDER BY o.parent,o.idLIMIT 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 oINNER 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 oINNER JOIN my_appraise aON a.orderid o.idAND is_reply 0ORDER BY appraise_time DESCLIMIT 0, 20)UNION ALL(SELECT *FROM my_order oINNER JOIN my_appraise aON a.orderid o.idAND is_reply 1ORDER BY appraise_time DESCLIMIT 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 nLEFT JOIN my_neighbor_apply sraON n.id sra.neighbor_idAND sra.user_id xxx
WHERE n.topic_status 4AND EXISTS(SELECT 1FROM message_info mWHERE n.id m.neighbor_idAND 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 nINNER JOIN message_info mON n.id m.neighbor_idAND m.inuser xxxLEFT JOIN my_neighbor_apply sraON n.id sra.neighbor_idAND sra.user_id xxx
WHERE n.topic_status 4AND 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 operationGROUP 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 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 oLEFT JOIN my_userinfo uON o.uid u.uidLEFT JOIN my_productinfo pON 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
) oLEFT JOIN my_userinfo uON o.uid u.uidLEFT JOIN my_productinfo pON 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 resourceidFROM my_distribute dWHERE isdelete 0AND cusmanagercode 1234567ORDER BY salecode limit 20) a
LEFT JOIN(SELECT resourcesid sum(ifnull(allocation, 0) * 12345) allocatedFROM my_resourcesGROUP 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 resourceidFROM my_distribute dWHERE isdelete 0AND cusmanagercode 1234567ORDER BY salecode limit 20) a
LEFT JOIN(SELECT resourcesid sum(ifnull(allocation, 0) * 12345) allocatedFROM my_resources r,(SELECT resourceidFROM my_distribute dWHERE isdelete 0AND cusmanagercode 1234567ORDER BY salecode limit 20) aWHERE r.resourcesid a.resourcesidGROUP 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 resourceidFROM my_distribute dWHERE isdelete 0AND cusmanagercode 1234567ORDER BY salecode limit 20)
SELECT a.*,c.allocated
FROM a
LEFT JOIN(SELECT resourcesid sum(ifnull(allocation, 0) * 12345) allocatedFROM my_resources r,aWHERE r.resourcesid a.resourcesidGROUP BY resourcesid) c
ON 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 。
