虽然自己没想到是这样的，不过一看还是很自然和谐的，从哪里获取，不断的过滤条件，要选择一样或不一样的，排好序，那才知道要取前几条呢。既然如此了，那就让我们一步步来看看其中的细节吧。准备工作1.创建测试数据库create database testQuery 2.创建测试表 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;
3.插入数据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); 4.最后想要的结果 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;
！现在开始SQL解析之旅吧！1. FROM当涉及多个表的时候，左边表的输出会作为右边表的输入，之后会生成一个虚拟表VT1。(1-J1)笛卡尔积计算两个相关联表的笛卡尔积(CROSS JOIN) ，生成虚拟表VT1-J1。 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 | ----- ------ ----- ------ 28 rows inset (0.00 sec)
(1-J2)ON过滤基于虚拟表VT1-J1这一个虚拟表进行过滤，过滤出所有满足ON 谓词条件的列，生成虚拟表VT1-J2。注意：这里因为语法限制，使用了'WHERE'代替，从中读者也可以感受到两者之间微妙的关系； 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 | ----- ------ ----- ------ 6 rows inset (0.00 sec)
(1-J3)添加外部列如果使用了外连接(LEFT,RIGHT,FULL)，主表（保留表）中的不符合ON条件的列也会被加入到VT1-J2中，作为外部行，生成虚拟表VT1-J3。 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 | ----- ------ ------ ------ 7 rows inset (0.00 sec)
下面从网上找到一张很形象的关于‘SQL JOINS'的解释图，如若侵犯了你的权益，请劳烦告知删除，谢谢。img2. WHERE对VT1过程中生成的临时表进行过滤，满足WHERE子句的列被插入到VT2表中。注意：此时因为分组，不能使用聚合运算；也不能使用SELECT中创建的别名；与ON的区别：如果有外部列，ON针对过滤的是关联表，主表（保留表）会返回所有的列；如果没有添加外部列，两者的效果是一样的；应用：对主表的过滤应该放在WHERE；对于关联表，先条件查询后连接则用ON，先连接后条件查询则用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 | ----- ------ ------ ------ 4 rows inset (0.00 sec)
3. GROUP BY这个子句会把VT2中生成的表按照GROUP BY中的列进行分组。生成VT3表。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；原因：GROUP BY改变了对表的引用，将其转换为新的引用方式，能够对其进行下一级逻辑操作的列会减少；我的理解是：根据分组字段，将具有相同分组字段的记录归并成一条记录，因为每一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，多个值是无法放进一条记录的，所以必须通过聚合函数将这些具有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 | ----- ------ ------ ------ 3 rows inset (0.00 sec)
4. HAVING这个子句对VT3表中的不同的组进行过滤，只作用于分组后的数据，满足HAVING条件的子句被加入到VT4表中。 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 | ----- ------ ------ ------ 2 rows inset (0.00 sec)
5. SELECT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(5-J2)DISTINCT寻找VT5-1中的重复列，并删掉，生成VT5-J2如果在查询中指定了DISTINCT子句，则会创建一张内存临时表（如果内存放不下，就需要存放在硬盘了）。这张临时表的表结构和上一步产生的虚拟表VT5是一样的，不同的是对进行DISTINCT操作的列增加了一个唯一索引，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 | ----- ------- 2 rows inset (0.00 sec)
6.ORDER BY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：唯一可使用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 | ----- ------- 2 rows inset (0.00 sec)
7.LIMITLIMIT子句从上一步得到的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，可以这么做：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，然后倒序排，再取N行结果集采用INNER JOIN优化，JOIN子句里也优先从索引获取ID列表，然后直接关联查询获得最终结果 mysql> 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; ----- ------- | uid | total | ----- ------- | ccc | 1 | ----- ------- 1 row inset (0.00 sec)
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