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
- 使用INSERT实现数据的插入
- UPDATE实现数据的更新
- 使用DELETE实现数据的删除
- 使用SELECT查询数据以及。
insert 使用方法:
. 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); . 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…); . 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); . 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(‘’)
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:
.找到表:from .拿着where指定的约束条件，去文件/表中取出一条条记录 .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 .将分组的结果进行having过滤 .执行select .去重 .将结果按条件排序：order by .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> () 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>
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() not null,
sex enum('male','female') not null default 'male', #大部分是男的
age int() unsigned not null default ,
hire_date date not null,
post varchar(),
post_comment varchar(),
salary double(,),
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() | NO | PRI | NULL | auto_increment |
| name | varchar() | NO | | NULL | |
| sex | enum('male','female') | NO | | male | |
| age | int() unsigned | NO | | | |
| hire_date | date | NO | | NULL | |
| post | varchar() | YES | | NULL | |
| post_comment | varchar() | YES | | NULL | |
| salary | double(,) | YES | | NULL | |
| office | int() | YES | | NULL | |
| depart_id | int() | 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',,'','老男孩驻沙河办事处外交大使',7300.33,,), #以下是教学部
('alex','male',,'','teacher',1000000.31,,),
('wupeiqi','male',,'','teacher',,,),
('yuanhao','male',,'','teacher',,,),
('liwenzhou','male',,'','teacher',,,),
('jingliyang','female',,'','teacher',,,),
('jinxin','male',,'','teacher',,,),
('成龙','male',,'','teacher',,,), ('歪歪','female',,'','sale',3000.13,,),#以下是销售部门
('丫丫','female',,'','sale',2000.35,,),
('丁丁','female',,'','sale',1000.37,,),
('星星','female',,'','sale',3000.29,,),
('格格','female',,'','sale',4000.33,,), ('张野','male',,'','operation',10000.13,,), #以下是运营部门
('程咬金','male',,'','operation',,,),
('程咬银','female',,'','operation',,,),
('程咬铜','male',,'','operation',,,),
('程咬铁','female',,'','operation',,,)
; #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* FROM employee;
SELECT name, salary* AS Annual_salary FROM employee;
SELECT name, salary* 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*) AS Annual_salary
FROM employee; CONCAT_WS() 第一个参数为分隔符
SELECT CONCAT_WS(':',name,salary*) AS Annual_salary
FROM employee;
小练习:
查出所有员工的名字，薪资,格式为
<名字:egon> <薪资:>
查出所有的岗位（去掉重复）
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* annual_salary from employee;
where条件约束查询:
#:单条件查询
SELECT name FROM employee
WHERE post='sale'; #:多条件查询
SELECT name,salary FROM employee
WHERE post='teacher' AND salary>; #:关键字BETWEEN AND
SELECT name,salary FROM employee
WHERE salary BETWEEN AND ; SELECT name,salary FROM employee
WHERE salary NOT BETWEEN AND ; #: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=;
再用上条查看，就会有结果了 #:关键字IN集合查询
SELECT name,salary FROM employee
WHERE salary= OR salary= OR salary= OR salary= ; SELECT name,salary FROM employee
WHERE salary IN (,,,) ; SELECT name,salary FROM employee
WHERE salary NOT IN (,,,) ; #: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:
. 查看岗位是teacher的员工姓名、年龄
. 查看岗位是teacher且年龄大于30岁的员工姓名、年龄
. 查看岗位是teacher且薪资在9000-1000范围内的员工姓名、年龄、薪资
. 查看岗位描述不为NULL的员工信息
. 查看岗位是teacher且薪资是10000或9000或30000的员工姓名、年龄、薪资
. 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
. 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 > ;
select name,age,salary from employee where post='teacher' and salary between and ;
select * from employee where post_comment is not null;
select name,age,salary from employee where post='teacher' and salary in (,,);
select name,age,salary from employee where post='teacher' and salary not in (,,);
select name,salary* from employee where post='teacher' and name like 'jin%';
复制代码
分组group by方法:
#、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 #、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 #、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 #、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=;
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=;
练习题:
. 查询岗位名以及岗位包含的所有员工名字
. 查询岗位名以及各岗位内包含的员工个数
. 查询公司内男员工和女员工的个数
. 查询岗位名以及各岗位的平均薪资
. 查询岗位名以及各岗位的最高薪资
. 查询岗位名以及各岗位的最低薪资
. 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 | |
| sale | |
| teacher | |
| 老男孩驻沙河办事处外交大使 | |
+-----------------------------------------+-----------+ #题目3：
mysql> select sex,count(id) from employee group by sex;
+--------+-----------+
| sex | count(id) |
+--------+-----------+
| male | |
| female | |
+--------+-----------+ #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;
. 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
. 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
. 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) > 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) > 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 ; #默认初始位置为0 SELECT * FROM employee ORDER BY salary DESC
LIMIT ,; #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 ,; #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 ,;
+----+-----------+------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+
| id | name | sex | age | hire_date | post | post_comment | salary | office | depart_id |
+----+-----------+------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+
| | egon | male | | -- | 老男孩驻沙河办事处外交大使 | NULL | 7300.33 | | |
| | alex | male | | -- | teacher | | 1000000.31 | | |
| | wupeiqi | male | | -- | teacher | NULL | 8300.00 | | |
| | yuanhao | male | | -- | teacher | NULL | 3500.00 | | |
| | liwenzhou | male | | -- | teacher | NULL | 2100.00 | | |
+----+-----------+------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+
rows in set (0.00 sec) mysql> select * from employee limit ,;
+----+------------+--------+-----+------------+---------+--------------+----------+--------+-----------+
| id | name | sex | age | hire_date | post | post_comment | salary | office | depart_id |
+----+------------+--------+-----+------------+---------+--------------+----------+--------+-----------+
| | jingliyang | female | | -- | teacher | NULL | 9000.00 | | |
| | jinxin | male | | -- | teacher | NULL | 30000.00 | | |
| | 成龙 | male | | -- | teacher | NULL | 10000.00 | | |
| | 歪歪 | female | | -- | sale | NULL | 3000.13 | | |
| | 丫丫 | female | | -- | sale | NULL | 2000.35 | | |
+----+------------+--------+-----+------------+---------+--------------+----------+--------+-----------+
rows in set (0.00 sec) mysql> select * from employee limit ,;
+----+-----------+--------+-----+------------+-----------+--------------+----------+--------+-----------+
| id | name | sex | age | hire_date | post | post_comment | salary | office | depart_id |
+----+-----------+--------+-----+------------+-----------+--------------+----------+--------+-----------+
| | 丁丁 | female | | -- | sale | NULL | 1000.37 | | |
| | 星星 | female | | -- | sale | NULL | 3000.29 | | |
| | 格格 | female | | -- | sale | NULL | 4000.33 | | |
| | 张野 | male | | -- | operation | NULL | 10000.13 | | |
| | 程咬金 | male | | -- | operation | NULL | 20000.00 | | |
+----+-----------+--------+-----+------------+-----------+--------------+----------+--------+-----------+
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() NOT NULL,
city VARCHAR() NOT NULL,
PRIMARY KEY(customer_id)
)ENGINE=INNODB DEFAULT CHARSET=UTF8; CREATE TABLE table2
(
order_id INT NOT NULL auto_increment,
customer_id VARCHAR(),
PRIMARY KEY(order_id)
)ENGINE=INNODB DEFAULT CHARSET=UTF8; INSERT INTO table1(customer_id,city) VALUES('','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('');
INSERT INTO table2(customer_id) VALUES('');
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) <
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 ），内容如下：
+-------------+----------+----------+-------------+
| customer_id | city | order_id | customer_id |
+-------------+----------+----------+-------------+
| | hangzhou | | |
| 9you | shanghai | | |
| baidu | hangzhou | | |
| tx | hangzhou | | |
| | hangzhou | | |
| 9you | shanghai | | |
| baidu | hangzhou | | |
| tx | hangzhou | | |
| | hangzhou | | 9you |
| 9you | shanghai | | 9you |
| baidu | hangzhou | | 9you |
| tx | hangzhou | | 9you |
| | hangzhou | | 9you |
| 9you | shanghai | | 9you |
| baidu | hangzhou | | 9you |
| tx | hangzhou | | 9you |
| | hangzhou | | 9you |
| 9you | shanghai | | 9you |
| baidu | hangzhou | | 9you |
| tx | hangzhou | | 9you |
| | hangzhou | | tx |
| 9you | shanghai | | tx |
| baidu | hangzhou | | tx |
| tx | hangzhou | | tx |
| | hangzhou | | NULL |
| 9you | shanghai | | NULL |
| baidu | hangzhou | | NULL |
| tx | hangzhou | | 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 |
+-------------+----------+----------+-------------+
| | hangzhou | | |
| | hangzhou | | |
| 9you | shanghai | | 9you |
| 9you | shanghai | | 9you |
| 9you | shanghai | | 9you |
| tx | hangzhou | | 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 |
+-------------+----------+----------+-------------+
| | hangzhou | | |
| | hangzhou | | |
| 9you | shanghai | | 9you |
| 9you | shanghai | | 9you |
| 9you | shanghai | | 9you |
| tx | hangzhou | | 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 |
+-------------+----------+----------+-------------+
| | hangzhou | | |
| | hangzhou | | |
| 9you | shanghai | | 9you |
| 9you | shanghai | | 9you |
| 9you | shanghai | | 9you |
| tx | hangzhou | | tx |
| NULL | NULL | | 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 |
+-------------+----------+----------+-------------+
| | hangzhou | | |
| | hangzhou | | |
| 9you | shanghai | | 9you |
| 9you | shanghai | | 9you |
| 9you | shanghai | | 9you |
| tx | hangzhou | | tx |
| baidu | hangzhou | NULL | NULL |
| NULL | NULL | | 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 |
+-------------+----------+----------+-------------+
| | hangzhou | | |
| | hangzhou | | |
| 9you | shanghai | | 9you |
| 9you | shanghai | | 9you |
| 9you | shanghai | | 9you |
| tx | hangzhou | | 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 |
+-------------+----------+----------+-------------+
| | hangzhou | | |
| | hangzhou | | |
| tx | hangzhou | | tx |
| baidu | hangzhou | NULL | NULL |
+-------------+----------+----------+-------------+
但是在使用WHERE子句时，需要注意以下两点：
- 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； - 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 |
+-------------+----------+----------+-------------+
| | hangzhou | | |
| baidu | hangzhou | NULL | NULL |
| tx | hangzhou | | 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 | | 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 | |
| tx | |
+-------------+--------------+
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 | |
| baidu | |
+-------------+--------------+
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.