day 42 mycql 查询操作,重点中的重点

 

数据库的查询操作是重点中的重点,最核心的内容就是它!

在查询时关键字的定义顺序:

select distinct(select-list) 

from (left-table)

(type-join) join (right-table)

on join(condition-联结两个表的条件)

where (where-condition 查询条件)

group by (group-by-list分组条件)

having (having-condition基于分组的筛选条件)

order by (order-by-condition排序条件)

limit(limit-num显示分页数)

 

 

关键字的查询顺序:

1,select

2,distinct(select-list)

3,from (left-table)

4,(type-join联表方式)join (right-table)

5,on join(join-condition联表的条件)

6,where (where-condition查询条件)

7,group by (group-by-condition分组条件)

8,having(having-condition基于分组的筛选条件)

9,order by(order-by排序条件)

10,limit(limit-number分页显示数据条数)

 

 

 

在MySQL管理软件中，可以通过SQL语句中的DML语言来实现数据的操作，包括

1. 使用INSERT实现数据的插入
2. UPDATE实现数据的更新
3. 使用DELETE实现数据的删除
4. 使用SELECT查询数据以及。

 

insert 使用方法:

1. 插入完整数据（顺序插入）
    语法一：
    INSERT INTO 表名(字段1,字段2,字段3…字段n) VALUES(值1,值2,值3…值n);

    语法二：
    INSERT INTO 表名 VALUES (值1,值2,值3…值n);

2. 指定字段插入数据
    语法：
    INSERT INTO 表名(字段1,字段2,字段3…) VALUES (值1,值2,值3…);

3. 插入多条记录
    语法：
    INSERT INTO 表名 VALUES
        (值1,值2,值3…值n),
        (值1,值2,值3…值n),
        (值1,值2,值3…值n);
        
4. 插入查询结果
    语法：
    INSERT INTO 表名(字段1,字段2,字段3…字段n) 
                    SELECT (字段1,字段2,字段3…字段n) FROM 表2
                    WHERE …;

 

update使用方法:

语法：
    UPDATE 表名 SET
        字段1=值1,
        字段2=值2,
        WHERE CONDITION;

示例：
    UPDATE mysql.user SET password=password(‘123’) 
        where user=’root’ and host=’localhost’;

 

delete 使用方法:

语法：
    DELETE FROM 表名 
        WHERE CONITION;

示例：
    DELETE FROM mysql.user 
        WHERE password=’’;

 

 

单表操作的方法:

简单语法要求:

SELECT 字段1,字段2... FROM 表名
                  WHERE 条件
                  GROUP BY field
                  HAVING 筛选
                  ORDER BY field
                  LIMIT 限制条数



重点中的重点：关键字的执行优先级
from
where
group by
having
select
distinct
order by
limit


执行顺序:
1.找到表:from

2.拿着where指定的约束条件，去文件/表中取出一条条记录

3.将取出的一条条记录进行分组group by，如果没有group by，则整体作为一组

4.将分组的结果进行having过滤

5.执行select

6.去重

7.将结果按条件排序：order by

8.限制结果的显示条数

我们在一句sql查询语句中的执行顺序,先是找到表格,用from,然后紧跟着是where找到后面的条件,

如果没有where那么我们是默认的所有条件为TRUE,即都满足where 1=1这个条件,然后再执行group by 在查询结果上进行分组,如果没有group by那么就是整体作为一个组,将整体的数据作为一个组进行过滤,然后执行select,它就相当于是python里面的print,在select里面去重复,进行排序,最后limit设定显示多少内容为一页.至此所有步骤执行完成.

 

select简单方法:

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>


(7)     SELECT 
(8)     DISTINCT <select_list>
(1)     FROM <left_table>
(3)     <join_type> JOIN <right_table>
(2)     ON <join_condition>
(4)     WHERE <where_condition>
(5)     GROUP BY <group_by_list>
(6)     HAVING <having_condition>
(9)     ORDER BY <order_by_condition>
(10)    LIMIT <limit_number>

 

示例:

company.employee
    员工id      id                  int             
    姓名        emp_name            varchar
    性别        sex                 enum
    年龄        age                 int
    入职日期     hire_date           date
    岗位        post                varchar
    职位描述     post_comment        varchar
    薪水        salary              double
    办公室       office              int
    部门编号     depart_id           int



#创建表
create table employee(
id int not null unique auto_increment,
name varchar(20) not null,
sex enum('male','female') not null default 'male', #大部分是男的
age int(3) unsigned not null default 28,
hire_date date not null,
post varchar(50),
post_comment varchar(100),
salary double(15,2),
office int, #一个部门一个屋子
depart_id int
);


#查看表结构
mysql> desc employee;
+--------------+-----------------------+------+-----+---------+----------------+
| Field        | Type                  | Null | Key | Default | Extra          |
+--------------+-----------------------+------+-----+---------+----------------+
| id           | int(11)               | NO   | PRI | NULL    | auto_increment |
| name         | varchar(20)           | NO   |     | NULL    |                |
| sex          | enum('male','female') | NO   |     | male    |                |
| age          | int(3) unsigned       | NO   |     | 28      |                |
| hire_date    | date                  | NO   |     | NULL    |                |
| post         | varchar(50)           | YES  |     | NULL    |                |
| post_comment | varchar(100)          | YES  |     | NULL    |                |
| salary       | double(15,2)          | YES  |     | NULL    |                |
| office       | int(11)               | YES  |     | NULL    |                |
| depart_id    | int(11)               | YES  |     | NULL    |                |
+--------------+-----------------------+------+-----+---------+----------------+

#插入记录
#三个部门：教学，销售，运营
insert into employee(name,sex,age,hire_date,post,salary,office,depart_id) values
('egon','male',18,'20170301','老男孩驻沙河办事处外交大使',7300.33,401,1), #以下是教学部
('alex','male',78,'20150302','teacher',1000000.31,401,1),
('wupeiqi','male',81,'20130305','teacher',8300,401,1),
('yuanhao','male',73,'20140701','teacher',3500,401,1),
('liwenzhou','male',28,'20121101','teacher',2100,401,1),
('jingliyang','female',18,'20110211','teacher',9000,401,1),
('jinxin','male',18,'19000301','teacher',30000,401,1),
('成龙','male',48,'20101111','teacher',10000,401,1),

('歪歪','female',48,'20150311','sale',3000.13,402,2),#以下是销售部门
('丫丫','female',38,'20101101','sale',2000.35,402,2),
('丁丁','female',18,'20110312','sale',1000.37,402,2),
('星星','female',18,'20160513','sale',3000.29,402,2),
('格格','female',28,'20170127','sale',4000.33,402,2),

('张野','male',28,'20160311','operation',10000.13,403,3), #以下是运营部门
('程咬金','male',18,'19970312','operation',20000,403,3),
('程咬银','female',18,'20130311','operation',19000,403,3),
('程咬铜','male',18,'20150411','operation',18000,403,3),
('程咬铁','female',18,'20140512','operation',17000,403,3)
;

#ps：如果在windows系统中，插入中文字符，select的结果为空白，可以将所有字符编码统一设置成gbk

准备表和记录

#简单查询
    SELECT id,name,sex,age,hire_date,post,post_comment,salary,office,depart_id 
    FROM employee;

    SELECT * FROM employee;

    SELECT name,salary FROM employee;

#避免重复DISTINCT
    SELECT DISTINCT post FROM employee;    

#通过四则运算查询
    SELECT name, salary*12 FROM employee;
    SELECT name, salary*12 AS Annual_salary FROM employee;
    SELECT name, salary*12 Annual_salary FROM employee;

#定义显示格式
   CONCAT() 函数用于连接字符串
   SELECT CONCAT('姓名: ',name,'  年薪: ', salary*12)  AS Annual_salary 
   FROM employee;
   
   CONCAT_WS() 第一个参数为分隔符
   SELECT CONCAT_WS(':',name,salary*12)  AS Annual_salary 
   FROM employee;

小练习:

1 查出所有员工的名字，薪资,格式为
    <名字:egon>    <薪资:3000>
2 查出所有的岗位（去掉重复）
3 查出所有员工名字，以及他们的年薪,年薪的字段名为annual_year



select concat('<名字:',name,'>    ','<薪资:',salary,'>') from employee;
select distinct depart_id from employee;
select name,salary*12 annual_salary from employee;

where条件约束查询:

#1:单条件查询
    SELECT name FROM employee
        WHERE post='sale';
        
#2:多条件查询
    SELECT name,salary FROM employee
        WHERE post='teacher' AND salary>10000;

#3:关键字BETWEEN AND
    SELECT name,salary FROM employee 
        WHERE salary BETWEEN 10000 AND 20000;

    SELECT name,salary FROM employee 
        WHERE salary NOT BETWEEN 10000 AND 20000;
    
#4:关键字IS NULL(判断某个字段是否为NULL不能用等号，需要用IS)
    SELECT name,post_comment FROM employee 
        WHERE post_comment IS NULL;

    SELECT name,post_comment FROM employee 
        WHERE post_comment IS NOT NULL;
        
    SELECT name,post_comment FROM employee 
        WHERE post_comment=''; 注意''是空字符串，不是null
    ps：
        执行
        update employee set post_comment='' where id=2;
        再用上条查看，就会有结果了

#5:关键字IN集合查询
    SELECT name,salary FROM employee 
        WHERE salary=3000 OR salary=3500 OR salary=4000 OR salary=9000 ;
    
    SELECT name,salary FROM employee 
        WHERE salary IN (3000,3500,4000,9000) ;

    SELECT name,salary FROM employee 
        WHERE salary NOT IN (3000,3500,4000,9000) ;

#6:关键字LIKE模糊查询
    通配符’%’
    SELECT * FROM employee 
            WHERE name LIKE 'eg%';

    通配符’_’
    SELECT * FROM employee 
            WHERE name LIKE 'al__';

小练习:

1. 查看岗位是teacher的员工姓名、年龄
2. 查看岗位是teacher且年龄大于30岁的员工姓名、年龄
3. 查看岗位是teacher且薪资在9000-1000范围内的员工姓名、年龄、薪资
4. 查看岗位描述不为NULL的员工信息
5. 查看岗位是teacher且薪资是10000或9000或30000的员工姓名、年龄、薪资
6. 查看岗位是teacher且薪资不是10000或9000或30000的员工姓名、年龄、薪资
7. 查看岗位是teacher且名字是jin开头的员工姓名、年薪
复制代码

复制代码
select name,age from employee where post = 'teacher';
select name,age from employee where post='teacher' and age > 30; 
select name,age,salary from employee where post='teacher' and salary between 9000 and 10000;
select * from employee where post_comment is not null;
select name,age,salary from employee where post='teacher' and salary in (10000,9000,30000);
select name,age,salary from employee where post='teacher' and salary not in (10000,9000,30000);
select name,salary*12 from employee where post='teacher' and name like 'jin%';
复制代码

 

分组group by方法:

#1、首先明确一点：分组发生在where之后，即分组是基于where之后得到的记录而进行的

#2、分组指的是：将所有记录按照某个相同字段进行归类，比如针对员工信息表的职位分组，或者按照性别进行分组等

#3、为何要分组呢？
    取每个部门的最高工资
    取每个部门的员工数
    取男人数和女人数

小窍门：‘每’这个字后面的字段，就是我们分组的依据


#4、大前提：
    可以按照任意字段分组，但是分组完毕后，比如group by post，只能查看post字段，如果想查看组内信息，需要借助于聚合函数

单独使用GROUP BY关键字分组
    SELECT post FROM employee GROUP BY post;
    注意：我们按照post字段分组，那么select查询的字段只能是post，想要获取组内的其他相关信息，需要借助函数

GROUP BY关键字和GROUP_CONCAT()函数一起使用
    SELECT post,GROUP_CONCAT(name) FROM employee GROUP BY post;#按照岗位分组，并查看组内成员名
    SELECT post,GROUP_CONCAT(name) as emp_members FROM employee GROUP BY post;

GROUP BY与聚合函数一起使用
    select post,count(id) as count from employee group by post;#按照岗位分组，并查看每个组有多少人

强调：

如果我们用unique的字段作为分组的依据，则每一条记录自成一组，这种分组没有意义
多条记录之间的某个字段值相同，该字段通常用来作为分组的依据

聚合函数:

#强调：聚合函数聚合的是组的内容，若是没有分组，则默认一组

示例：
    SELECT COUNT(*) FROM employee;
    SELECT COUNT(*) FROM employee WHERE depart_id=1;
    SELECT MAX(salary) FROM employee;
    SELECT MIN(salary) FROM employee;
    SELECT AVG(salary) FROM employee;
    SELECT SUM(salary) FROM employee;
    SELECT SUM(salary) FROM employee WHERE depart_id=3;

练习题:

1. 查询岗位名以及岗位包含的所有员工名字
2. 查询岗位名以及各岗位内包含的员工个数
3. 查询公司内男员工和女员工的个数
4. 查询岗位名以及各岗位的平均薪资
5. 查询岗位名以及各岗位的最高薪资
6. 查询岗位名以及各岗位的最低薪资
7. 查询男员工与男员工的平均薪资，女员工与女员工的平均薪资

#题1：分组
mysql> select post,group_concat(name) from employee group by post;
+-----------------------------------------+---------------------------------------------------------+
| post                                    | group_concat(name)                                      |
+-----------------------------------------+---------------------------------------------------------+
| operation                               | 张野,程咬金,程咬银,程咬铜,程咬铁                        |
| sale                                    | 歪歪,丫丫,丁丁,星星,格格                                |
| teacher                                 | alex,wupeiqi,yuanhao,liwenzhou,jingliyang,jinxin,成龙   |
| 老男孩驻沙河办事处外交大使              | egon                                                    |
+-----------------------------------------+---------------------------------------------------------+


#题目2：
mysql> select post,count(id) from employee group by post;
+-----------------------------------------+-----------+
| post                                    | count(id) |
+-----------------------------------------+-----------+
| operation                               |         5 |
| sale                                    |         5 |
| teacher                                 |         7 |
| 老男孩驻沙河办事处外交大使              |         1 |
+-----------------------------------------+-----------+


#题目3：
mysql> select sex,count(id) from employee group by sex;
+--------+-----------+
| sex    | count(id) |
+--------+-----------+
| male   |        10 |
| female |         8 |
+--------+-----------+

#题目4：
mysql> select post,avg(salary) from employee group by post;
+-----------------------------------------+---------------+
| post                                    | avg(salary)   |
+-----------------------------------------+---------------+
| operation                               |  16800.026000 |
| sale                                    |   2600.294000 |
| teacher                                 | 151842.901429 |
| 老男孩驻沙河办事处外交大使              |   7300.330000 |
+-----------------------------------------+---------------+

#题目5
mysql> select post,max(salary) from employee group by post;
+-----------------------------------------+-------------+
| post                                    | max(salary) |
+-----------------------------------------+-------------+
| operation                               |    20000.00 |
| sale                                    |     4000.33 |
| teacher                                 |  1000000.31 |
| 老男孩驻沙河办事处外交大使              |     7300.33 |
+-----------------------------------------+-------------+

#题目6
mysql> select post,min(salary) from employee group by post;
+-----------------------------------------+-------------+
| post                                    | min(salary) |
+-----------------------------------------+-------------+
| operation                               |    10000.13 |
| sale                                    |     1000.37 |
| teacher                                 |     2100.00 |
| 老男孩驻沙河办事处外交大使              |     7300.33 |
+-----------------------------------------+-------------+

#题目七
mysql> select sex,avg(salary) from employee group by sex;
+--------+---------------+
| sex    | avg(salary)   |
+--------+---------------+
| male   | 110920.077000 |
| female |   7250.183750 |
+--------+---------------+

 

六 HAVING过滤

HAVING与WHERE不一样的地方在于!!!!!!

#！！！执行优先级从高到低：where > group by > having 
#1. Where 发生在分组group by之前，因而Where中可以有任意字段，但是绝对不能使用聚合函数。

#2. Having发生在分组group by之后，因而Having中可以使用分组的字段，无法直接取到其他字段,可以使用聚合函数

查询排序:

按单列排序
    SELECT * FROM employee ORDER BY salary;
    SELECT * FROM employee ORDER BY salary ASC;
    SELECT * FROM employee ORDER BY salary DESC;

按多列排序:先按照age排序，如果年纪相同，则按照薪资排序
    SELECT * from employee
        ORDER BY age,
        salary DESC;

 

1. 查询所有员工信息，先按照age升序排序，如果age相同则按照hire_date降序排序
2. 查询各岗位平均薪资大于10000的岗位名、平均工资,结果按平均薪资升序排列
3. 查询各岗位平均薪资大于10000的岗位名、平均工资,结果按平均薪资降序排列

#题目1
mysql> select * from employee ORDER BY age asc,hire_date desc;

#题目2
mysql> select post,avg(salary) from employee group by post having avg(salary) > 10000 order by avg(salary) asc;
+-----------+---------------+
| post      | avg(salary)   |
+-----------+---------------+
| operation |  16800.026000 |
| teacher   | 151842.901429 |
+-----------+---------------+

#题目3
mysql> select post,avg(salary) from employee group by post having avg(salary) > 10000 order by avg(salary) desc;
+-----------+---------------+
| post      | avg(salary)   |
+-----------+---------------+
| teacher   | 151842.901429 |
| operation |  16800.026000 |
+-----------+---------------+

 

限制查询的记录数:

示例：
    SELECT * FROM employee ORDER BY salary DESC 
        LIMIT 3;                    #默认初始位置为0 
    
    SELECT * FROM employee ORDER BY salary DESC
        LIMIT 0,5; #从第0开始，即先查询出第一条，然后包含这一条在内往后查5条

    SELECT * FROM employee ORDER BY salary DESC
        LIMIT 5,5; #从第5开始，即先查询出第6条，然后包含这一条在内往后查5条

mysql> select * from  employee limit 0,5;
+----+-----------+------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+
| id | name      | sex  | age | hire_date  | post                                    | post_comment | salary     | office | depart_id |
+----+-----------+------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+
|  1 | egon      | male |  18 | 2017-03-01 | 老男孩驻沙河办事处外交大使              | NULL         |    7300.33 |    401 |         1 |
|  2 | alex      | male |  78 | 2015-03-02 | teacher                                 |              | 1000000.31 |    401 |         1 |
|  3 | wupeiqi   | male |  81 | 2013-03-05 | teacher                                 | NULL         |    8300.00 |    401 |         1 |
|  4 | yuanhao   | male |  73 | 2014-07-01 | teacher                                 | NULL         |    3500.00 |    401 |         1 |
|  5 | liwenzhou | male |  28 | 2012-11-01 | teacher                                 | NULL         |    2100.00 |    401 |         1 |
+----+-----------+------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+
rows in set (0.00 sec)

mysql> select * from  employee limit 5,5;
+----+------------+--------+-----+------------+---------+--------------+----------+--------+-----------+
| id | name       | sex    | age | hire_date  | post    | post_comment | salary   | office | depart_id |
+----+------------+--------+-----+------------+---------+--------------+----------+--------+-----------+
|  6 | jingliyang | female |  18 | 2011-02-11 | teacher | NULL         |  9000.00 |    401 |         1 |
|  7 | jinxin     | male   |  18 | 1900-03-01 | teacher | NULL         | 30000.00 |    401 |         1 |
|  8 | 成龙       | male   |  48 | 2010-11-11 | teacher | NULL         | 10000.00 |    401 |         1 |
|  9 | 歪歪       | female |  48 | 2015-03-11 | sale    | NULL         |  3000.13 |    402 |         2 |
| 10 | 丫丫       | female |  38 | 2010-11-01 | sale    | NULL         |  2000.35 |    402 |         2 |
+----+------------+--------+-----+------------+---------+--------------+----------+--------+-----------+
rows in set (0.00 sec)

mysql> select * from  employee limit 10,5;
+----+-----------+--------+-----+------------+-----------+--------------+----------+--------+-----------+
| id | name      | sex    | age | hire_date  | post      | post_comment | salary   | office | depart_id |
+----+-----------+--------+-----+------------+-----------+--------------+----------+--------+-----------+
| 11 | 丁丁      | female |  18 | 2011-03-12 | sale      | NULL         |  1000.37 |    402 |         2 |
| 12 | 星星      | female |  18 | 2016-05-13 | sale      | NULL         |  3000.29 |    402 |         2 |
| 13 | 格格      | female |  28 | 2017-01-27 | sale      | NULL         |  4000.33 |    402 |         2 |
| 14 | 张野      | male   |  28 | 2016-03-11 | operation | NULL         | 10000.13 |    403 |         3 |
| 15 | 程咬金    | male   |  18 | 1997-03-12 | operation | NULL         | 20000.00 |    403 |         3 |
+----+-----------+--------+-----+------------+-----------+--------------+----------+--------+-----------+
rows in set (0.00 sec)

使用正则表达式进行查询:

SELECT * FROM employee WHERE name REGEXP '^ale';

SELECT * FROM employee WHERE name REGEXP 'on$';

SELECT * FROM employee WHERE name REGEXP 'm{2}';


小结：对字符串匹配的方式
WHERE name = 'egon';
WHERE name LIKE 'yua%';
WHERE name REGEXP 'on$';

 

小练习：

查看所有员工中名字是jin开头，n或者g结果的员工信息

select * from employee where name regexp '^jin.*[gn]$';

 

 

 

小练习题:

首先我们来建库,然后建表,再然后往表格里面添加数据,就可以演示简单的查询的基本用法了

create database TestDB;

CREATE TABLE table1
 (
     customer_id VARCHAR(10) NOT NULL,
     city VARCHAR(10) NOT NULL,
     PRIMARY KEY(customer_id)
 )ENGINE=INNODB DEFAULT CHARSET=UTF8;

 CREATE TABLE table2
 (
     order_id INT NOT NULL auto_increment,
     customer_id VARCHAR(10),
     PRIMARY KEY(order_id)
 )ENGINE=INNODB DEFAULT CHARSET=UTF8;


INSERT INTO table1(customer_id,city) VALUES('163','hangzhou');
 INSERT INTO table1(customer_id,city) VALUES('9you','shanghai');
 INSERT INTO table1(customer_id,city) VALUES('tx','hangzhou');
 INSERT INTO table1(customer_id,city) VALUES('baidu','hangzhou');

 INSERT INTO table2(customer_id) VALUES('163');
 INSERT INTO table2(customer_id) VALUES('163');
 INSERT INTO table2(customer_id) VALUES('9you');
 INSERT INTO table2(customer_id) VALUES('9you');
 INSERT INTO table2(customer_id) VALUES('9you');
 INSERT INTO table2(customer_id) VALUES('tx');
 INSERT INTO table2(customer_id) VALUES(NULL);

#查询来自杭州，并且订单数少于2的客户。
 SELECT a.customer_id, COUNT(b.order_id) as total_orders
 FROM table1 AS a
 LEFT JOIN table2 AS b
 ON a.customer_id = b.customer_id
 WHERE a.city = 'hangzhou'
 GROUP BY a.customer_id
 HAVING count(b.order_id) < 2
 ORDER BY total_orders DESC;

下面我们来具体剖析一下,程序的执行:

在这些SQL语句的执行过程中，都会产生一个虚拟表，用来保存SQL语句的执行结果（这是重点），我现在就来跟踪这个虚拟表的变化，得到最终的查询结果的过程，来分析整个SQL逻辑查询的执行顺序和过程。

执行FROM语句

第一步，执行FROM语句。我们首先需要知道最开始从哪个表开始的，这就是FROM告诉我们的。现在有了<left_table>和<right_table>两个表，我们到底从哪个表开始，还是从两个表进行某种联系以后再开始呢？它们之间如何产生联系呢？——笛卡尔积

关于什么是笛卡尔积，请自行Google补脑。经过FROM语句对两个表执行笛卡尔积，会得到一个虚拟表，暂且叫VT1（vitual table 1），内容如下：

+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| 163         | hangzhou |        1 | 163         |
| 9you        | shanghai |        1 | 163         |
| baidu       | hangzhou |        1 | 163         |
| tx          | hangzhou |        1 | 163         |
| 163         | hangzhou |        2 | 163         |
| 9you        | shanghai |        2 | 163         |
| baidu       | hangzhou |        2 | 163         |
| tx          | hangzhou |        2 | 163         |
| 163         | hangzhou |        3 | 9you        |
| 9you        | shanghai |        3 | 9you        |
| baidu       | hangzhou |        3 | 9you        |
| tx          | hangzhou |        3 | 9you        |
| 163         | hangzhou |        4 | 9you        |
| 9you        | shanghai |        4 | 9you        |
| baidu       | hangzhou |        4 | 9you        |
| tx          | hangzhou |        4 | 9you        |
| 163         | hangzhou |        5 | 9you        |
| 9you        | shanghai |        5 | 9you        |
| baidu       | hangzhou |        5 | 9you        |
| tx          | hangzhou |        5 | 9you        |
| 163         | hangzhou |        6 | tx          |
| 9you        | shanghai |        6 | tx          |
| baidu       | hangzhou |        6 | tx          |
| tx          | hangzhou |        6 | tx          |
| 163         | hangzhou |        7 | NULL        |
| 9you        | shanghai |        7 | NULL        |
| baidu       | hangzhou |        7 | NULL        |
| tx          | hangzhou |        7 | NULL        |
+-------------+----------+----------+-------------+

 

执行ON过滤

执行完笛卡尔积以后，接着就进行ON a.customer_id = b.customer_id条件过滤，根据ON中指定的条件，去掉那些不符合条件的数据，得到VT2表，内容如下：

+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| 163         | hangzhou |        1 | 163         |
| 163         | hangzhou |        2 | 163         |
| 9you        | shanghai |        3 | 9you        |
| 9you        | shanghai |        4 | 9you        |
| 9you        | shanghai |        5 | 9you        |
| tx          | hangzhou |        6 | tx          |
+-------------+----------+----------+-------------+

添加外部行

这一步只有在连接类型为OUTER JOIN时才发生，如LEFT OUTER JOIN、RIGHT OUTER JOIN和FULL OUTER JOIN。在大多数的时候，我们都是会省略掉OUTER关键字的，但OUTER表示的就是外部行的概念。

LEFT OUTER JOIN把左表记为保留表，得到的结果为：

+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| 163         | hangzhou |        1 | 163         |
| 163         | hangzhou |        2 | 163         |
| 9you        | shanghai |        3 | 9you        |
| 9you        | shanghai |        4 | 9you        |
| 9you        | shanghai |        5 | 9you        |
| tx          | hangzhou |        6 | tx          |
| baidu       | hangzhou |     NULL | NULL        |
+-------------+----------+----------+-------------+

RIGHT OUTER JOIN把右表记为保留表，得到的结果为：

+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| 163         | hangzhou |        1 | 163         |
| 163         | hangzhou |        2 | 163         |
| 9you        | shanghai |        3 | 9you        |
| 9you        | shanghai |        4 | 9you        |
| 9you        | shanghai |        5 | 9you        |
| tx          | hangzhou |        6 | tx          |
| NULL        | NULL     |        7 | NULL        |
+-------------+----------+----------+-------------+

FULL OUTER JOIN把左右表都作为保留表，得到的结果为：

+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| 163         | hangzhou |        1 | 163         |
| 163         | hangzhou |        2 | 163         |
| 9you        | shanghai |        3 | 9you        |
| 9you        | shanghai |        4 | 9you        |
| 9you        | shanghai |        5 | 9you        |
| tx          | hangzhou |        6 | tx          |
| baidu       | hangzhou |     NULL | NULL        |
| NULL        | NULL     |        7 | NULL        |
+-------------+----------+----------+-------------+

添加外部行的工作就是在VT2表的基础上添加保留表中被过滤条件过滤掉的数据，非保留表中的数据被赋予NULL值，最后生成虚拟表VT3。

由于我在准备的测试SQL查询逻辑语句中使用的是LEFT JOIN，过滤掉了以下这条数据：

| baidu       | hangzhou |     NULL | NULL        |


现在就把这条数据添加到VT2表中，得到的VT3表如下：

+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| 163         | hangzhou |        1 | 163         |
| 163         | hangzhou |        2 | 163         |
| 9you        | shanghai |        3 | 9you        |
| 9you        | shanghai |        4 | 9you        |
| 9you        | shanghai |        5 | 9you        |
| tx          | hangzhou |        6 | tx          |
| baidu       | hangzhou |     NULL | NULL        |
+-------------+----------+----------+-------------+

 

执行WHERE过滤

对添加外部行得到的VT3进行WHERE过滤，只有符合<where_condition>的记录才会输出到虚拟表VT4中。当我们执行WHERE a.city = 'hangzhou'的时候，就会得到以下内容，并存在虚拟表VT4中：

+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| 163         | hangzhou |        1 | 163         |
| 163         | hangzhou |        2 | 163         |
| tx          | hangzhou |        6 | tx          |
| baidu       | hangzhou |     NULL | NULL        |
+-------------+----------+----------+-------------+

 

但是在使用WHERE子句时，需要注意以下两点：

1. 由于数据还没有分组，因此现在还不能在WHERE过滤器中使用where_condition=MIN(col)这类对分组统计的过滤；
2. 由于还没有进行列的选取操作，因此在SELECT中使用列的别名也是不被允许的，如：SELECT city as c FROM t WHERE c='shanghai';是不允许出现的。

 

执行GROUP BY分组

GROU BY子句主要是对使用WHERE子句得到的虚拟表进行分组操作。我们执行测试语句中的GROUP BY a.customer_id，就会得到以下内容(默认只显示组内第一条)：

+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| 163         | hangzhou |        1 | 163         |
| baidu       | hangzhou |     NULL | NULL        |
| tx          | hangzhou |        6 | tx          |
+-------------+----------+----------+-------------+

得到的内容会存入虚拟表VT5中，此时，我们就得到了一个VT5虚拟表，接下来的操作都会在该表上完成。

 

执行HAVING过滤

HAVING子句主要和GROUP BY子句配合使用，对分组得到的VT5虚拟表进行条件过滤。当我执行测试语句中的HAVING count(b.order_id) < 2时，将得到以下内容：

+-------------+----------+----------+-------------+
| customer_id | city     | order_id | customer_id |
+-------------+----------+----------+-------------+
| baidu       | hangzhou |     NULL | NULL        |
| tx          | hangzhou |        6 | tx          |
+-------------+----------+----------+-------------+

 

SELECT列表

现在才会执行到SELECT子句，不要以为SELECT子句被写在第一行，就是第一个被执行的。

我们执行测试语句中的SELECT a.customer_id, COUNT(b.order_id) as total_orders，从虚拟表VT6中选择出我们需要的内容。我们将得到以下内容：

+-------------+--------------+
| customer_id | total_orders |
+-------------+--------------+
| baidu       |            0 |
| tx          |            1 |
+-------------+--------------+

 

执行ORDER BY子句

对虚拟表中的内容按照指定的列进行排序，然后返回一个新的虚拟表，我们执行测试SQL语句中的ORDER BY total_orders DESC，就会得到以下内容：

+-------------+--------------+
| customer_id | total_orders |
+-------------+--------------+
| tx          |            1 |
| baidu       |            0 |
+-------------+--------------+

 

 

LIMIT n, m

表示从第n条记录开始选择m条记录。而很多开发人员喜欢使用该语句来解决分页问题。对于小数据，使用LIMIT子句没有任何问题，当数据量非常大的时候，使用LIMIT n, m是非常低效的。因为LIMIT的机制是每次都是从头开始扫描，如果需要从第60万行开始，读取3条数据，就需要先扫描定位到60万行，然后再进行读取，而扫描的过程是一个非常低效的过程。所以，对于大数据处理时，是非常有必要在应用层建立一定的缓存机制（现在的大数据处理，大都使用缓存）

 

using语法简介:

 在查询中使用联表的话有join on 语法

还有using语法

举例:

select name from actor as a inner join boss as b on a.id=b.id 

select name from actor as a inner join boss as b using id

using 里面的参数必须是在两个表格里面都存在的才可以,否则无法使用它.