接下来再走一步，让我们看看一条SQL语句的前世今生。

首先看一下示例语句：

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：

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 分组之后才会执行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。

1. 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、最后需要的结果

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！

2. from

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

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)

3. on 过滤

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。

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 |
+-----+------+-----+------+
rows in set (0.00 sec)

4. Outer join 添加外部列

如果指定了OUTER JOIN（比如left join、 right join），那么保留表中未匹配的行就会作为外部行添加到虚拟表VT2中，产生虚拟表VT3。

如果FROM子句中包含两个以上的表的话，那么就会对上一个join连接产生的结果VT3和下一个表重复执行步骤1~3这三个步骤，一直到处理完所有的表为止。

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)

5. where

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 |
+-----+------+------+------+
rows in set (0.00 sec)

6. Group by

根据group by子句中的列，对VT4中的记录进行分组操作，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；

原因：GROUP BY 5b4 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 |
+-----+------+------+------+
rows in set (0.00 sec)

7. having

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)<
2230
/code>

8. 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

9. 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 |
+-----+-------+
rows in set (0.00 sec)

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)

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)