接下来再走一步,让咱们看看一条SQL语句的前世此生。mysql
首先看一下示例语句:sql
SELECT DISTINCT < select_list > FROM < left_table > < join_type > JOIN < right_table > ON < join_condition > WHERE < where_condition > GROUP BY < group_by_list > HAVING < having_condition > ORDER BY < order_by_condition > LIMIT < limit_number >
然而它的执行顺序是这样的:数据库
1 FROM <left_table> 2 ON <join_condition> 3 <join_type> JOIN <right_table> 第二步和第三步会循环执行 4 WHERE <where_condition> 第四步会循环执行,多个条件的执行顺序是从左往右的。 5 GROUP BY <group_by_list> 6 HAVING <having_condition> 7 SELECT 分组以后才会执行SELECT 8 DISTINCT <select_list> 9 ORDER BY <order_by_condition> 10 LIMIT <limit_number>前9步都是SQL92标准语法。limit是MySQL的独有语法。
虽然本身没想到是这样的,不过一看仍是很天然和谐的,从哪里获取,不断的过滤条件,要选择同样或不同的,排好序,那才知道要取前几条呢。ide
既然如此了,那就让咱们一步步来看看其中的细节吧。函数
create database testQuery
CREATE TABLE table1 ( uid VARCHAR(10) NOT NULL, name VARCHAR(10) NOT NULL, PRIMARY KEY(uid) )ENGINE=INNODB DEFAULT CHARSET=UTF8; CREATE TABLE table2 ( oid INT NOT NULL auto_increment, uid VARCHAR(10), PRIMARY KEY(oid) )ENGINE=INNODB DEFAULT CHARSET=UTF8;
INSERT INTO table1(uid,name) VALUES('aaa','mike'),('bbb','jack'),('ccc','mike'),('ddd','mike'); INSERT INTO table2(uid) VALUES('aaa'),('aaa'),('bbb'),('bbb'),('bbb'),('ccc'),(NULL);
SELECT a.uid, count(b.oid) AS total FROM table1 AS a LEFT JOIN table2 AS b ON a.uid = b.uid WHERE a. NAME = 'mike' GROUP BY a.uid HAVING count(b.oid) < 2 ORDER BY total DESC LIMIT 1;
如今开始SQL解析之旅吧!测试
对FROM的左边的表和右边的表计算笛卡尔积(CROSS JOIN)。产生虚表VT1优化
mysql> select * from table1,table2; +-----+------+-----+------+ | uid | name | oid | uid | +-----+------+-----+------+ | aaa | mike | 1 | aaa | | bbb | jack | 1 | aaa | | ccc | mike | 1 | aaa | | ddd | mike | 1 | aaa | | aaa | mike | 2 | aaa | | bbb | jack | 2 | aaa | | ccc | mike | 2 | aaa | | ddd | mike | 2 | aaa | | aaa | mike | 3 | bbb | | bbb | jack | 3 | bbb | | ccc | mike | 3 | bbb | | ddd | mike | 3 | bbb | | aaa | mike | 4 | bbb | | bbb | jack | 4 | bbb | | ccc | mike | 4 | bbb | | ddd | mike | 4 | bbb | | aaa | mike | 5 | bbb | | bbb | jack | 5 | bbb | | ccc | mike | 5 | bbb | | ddd | mike | 5 | bbb | | aaa | mike | 6 | ccc | | bbb | jack | 6 | ccc | | ccc | mike | 6 | ccc | | ddd | mike | 6 | ccc | | aaa | mike | 7 | NULL | | bbb | jack | 7 | NULL | | ccc | mike | 7 | NULL | | ddd | mike | 7 | NULL | +-----+------+-----+------+ rows in set (0.00 sec)
对虚表VT1进行ON筛选,只有那些符合 <join-condition> 的行才会被记录在虚表VT2中。ui
注意:这里由于语法限制,使用了WHERE代替,从中读者也能够感觉到二者之间微妙的关系;code
mysql> SELECT -> * -> FROM -> table1, -> table2 -> WHERE -> table1.uid = table2.uid -> ; +-----+------+-----+------+ | uid | name | oid | uid | +-----+------+-----+------+ | aaa | mike | 1 | aaa | | aaa | mike | 2 | aaa | | bbb | jack | 3 | bbb | | bbb | jack | 4 | bbb | | bbb | jack | 5 | bbb | | ccc | mike | 6 | ccc | +-----+------+-----+------+ rows in set (0.00 sec)
若是指定了OUTER JOIN(好比left join、 right join),那么保留表中未匹配的行就会做为外部行添加到虚拟表VT2中,产生虚拟表VT3。blog
若是FROM子句中包含两个以上的表的话,那么就会对上一个join链接产生的结果VT3和下一个表重复执行步骤1~3这三个步骤,一直处处理完全部的表为止。
mysql> SELECT -> * -> FROM -> table1 AS a -> LEFT OUTER JOIN table2 AS b ON a.uid = b.uid; +-----+------+------+------+ | uid | name | oid | uid | +-----+------+------+------+ | aaa | mike | 1 | aaa | | aaa | mike | 2 | aaa | | bbb | jack | 3 | bbb | | bbb | jack | 4 | bbb | | bbb | jack | 5 | bbb | | ccc | mike | 6 | ccc | | ddd | mike | NULL | NULL | +-----+------+------+------+ rows in set (0.00 sec)
对虚拟表VT3进行WHERE条件过滤。只有符合<where-condition>的记录才会被插入到虚拟表VT4中。
注意:此时由于分组,不能使用聚合运算;也不能使用SELECT中建立的别名;
与ON的区别:
若是有外部列,ON针对过滤的是关联表,主表(保留表)会返回全部的列;
若是没有添加外部列,二者的效果是同样的;
应用:
对主表的过滤应该放在WHERE;
mysql> SELECT -> * -> FROM -> table1 AS a -> LEFT OUTER JOIN table2 AS b ON a.uid = b.uid -> WHERE -> a. NAME = 'mike'; +-----+------+------+------+ | uid | name | oid | uid | +-----+------+------+------+ | aaa | mike | 1 | aaa | | aaa | mike | 2 | aaa | | ccc | mike | 6 | ccc | | ddd | mike | NULL | NULL | +-----+------+------+------+ rows in set (0.00 sec)
根据group by子句中的列,对VT4中的记录进行分组操做,产生虚拟表VT5。
注意:其后处理过程的语句,如SELECT,HAVING,所用到的列必须包含在GROUP BY中。对于没有出现的,得用聚合函数;
缘由:GROUP BY改变了对表的引用,将其转换为新的引用方式,可以对其进行下一级逻辑操做的列会减小;
个人理解是:
根据分组字段,将具备相同分组字段的记录归并成一条记录,由于每个分组只能返回一条记录,除非是被过滤掉了,而不在分组字段里面的字段可能会有多个值,多个值是没法放进一条记录的,因此必须经过聚合函数将这些具备多值的列转换成单值;
mysql> SELECT -> * -> FROM -> table1 AS a -> LEFT OUTER JOIN table2 AS b ON a.uid = b.uid -> WHERE -> a. NAME = 'mike' -> GROUP BY -> a.uid; +-----+------+------+------+ | uid | name | oid | uid | +-----+------+------+------+ | aaa | mike | 1 | aaa | | ccc | mike | 6 | ccc | | ddd | mike | NULL | NULL | +-----+------+------+------+ rows in set (0.00 sec)
对虚拟表VT5应用having过滤,只有符合<having-condition>的记录才会被 插入到虚拟表VT6中。
mysql> SELECT -> * -> FROM -> table1 AS a -> LEFT OUTER JOIN table2 AS b ON a.uid = b.uid -> WHERE -> a. NAME = 'mike' -> GROUP BY -> a.uid -> HAVING -> count(b.oid) < 2; +-----+------+------+------+ | uid | name | oid | uid | +-----+------+------+------+ | ccc | mike | 6 | ccc | | ddd | mike | NULL | NULL | +-----+------+------+------+ rows in set (0.00 sec)
这个子句对SELECT子句中的元素进行处理,生成VT5表。
(5-J1)计算表达式 计算SELECT 子句中的表达式,生成VT5-J1
寻找VT5-1中的重复列,并删掉,生成VT5-J2
若是在查询中指定了DISTINCT子句,则会建立一张内存临时表(若是内存放不下,就须要存放在硬盘了)。这张临时表的表结构和上一步产生的虚拟表VT5是同样的,不一样的是对进行DISTINCT操做的列增长了一个惟一索引,以此来除重复数据。
mysql> SELECT -> a.uid, -> count(b.oid) AS total -> FROM -> table1 AS a -> LEFT OUTER JOIN table2 AS b ON a.uid = b.uid -> WHERE -> a. NAME = 'mike' -> GROUP BY -> a.uid -> HAVING -> count(b.oid) < 2; +-----+-------+ | uid | total | +-----+-------+ | ccc | 1 | | ddd | 0 | +-----+-------+ rows in set (0.00 sec)
从VT5-J2中的表中,根据ORDER BY 子句的条件对结果进行排序,生成VT6表。
注意:惟一可以使用SELECT中别名的地方;
mysql> SELECT -> a.uid, -> count(b.oid) AS total -> FROM -> table1 AS a -> LEFT OUTER JOIN table2 AS b ON a.uid = b.uid -> WHERE -> a. NAME = 'mike' -> GROUP BY -> a.uid -> HAVING -> count(b.oid) < 2 -> ORDER BY -> total DESC; +-----+-------+ | uid | total | +-----+-------+ | ccc | 1 | | ddd | 0 | +-----+-------+ rows in set (0.00 sec)
LIMIT子句从上一步获得的VT6虚拟表中选出从指定位置开始的指定行数据。
注意:offset和rows的正负带来的影响;
当偏移量很大时效率是很低的,能够这么作:
采用子查询的方式优化,在子查询里先从索引获取到最大id,而后倒序排,再取N行结果集
mysql> SELEC -> a.uid, -> count(b.oid) AS total -> FROM -> table1 AS a -> LEFT JOIN table2 AS b ON a.uid = b.uid -> WHERE -> a. NAME = 'mike' -> GROUP BY -> a.uid -> HAVING -> count(b.oid) < 2 -> ORDER BY -> total DESC -> LIMIT 1; +-----+-------+ | uid | total | +-----+-------+ | ccc | 1 | +-----+-------+ row in set (0.00 sec)
FROM(将最近的两张表,进行笛卡尔积)---VT1
ON(将VT1按照它的条件进行过滤)---VT2
LEFT JOIN(保留左表的记录)---VT3
WHERE(过滤VT3中的记录)--VT4…VTn
GROUP BY(对VT4的记录进行分组)---VT5
HAVING(对VT5中的记录进行过滤)---VT6
SELECT(对VT6中的记录,选取指定的列)--VT7
ORDER BY(对VT7的记录进行排序)--VT8
单表查询:根据WHERE条件过滤表中的记录,造成中间表(这个中间表对用户是不可见的);而后根据SELECT的选择列选择相应的列进行返回最终结果。
两表链接查询:对两表求积(笛卡尔积)并用ON条件和链接链接类型进行过滤造成中间表;而后根据WHERE条件过滤中间表的记录,并根据SELECT指定的列返回查询结果。
笛卡尔积:行相乘、列相加。
多表链接查询:先对第一个和第二个表按照两表链接作查询,而后用查询结果和第三个表作链接查询,以此类推,直到全部的表都链接上为止,最终造成一个中间的结果表,而后根据WHERE条件过滤中间表的记录,并根据SELECT指定的列返回查询结果。
WHERE条件解析顺序
MySQL:从左往右去执行WHERE条件的。
写WHERE条件的时候,优先级高的部分要去编写过滤力度最大的条件语句。