MySQL单表的CRUD及多表查询

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数据库表的增删改查操作:

  

  查:

    单表查询

      简单查询where约束group by分组聚合查询having过滤order by排序limit限制正则匹配

    多表查询

      连表查询交叉查询>內连查询左外连接查询右外连接查询全外链接查询连接结果筛选查询        

      子查询 :带关键字in的子查询带比较运算符的子查询带关键字exists的布尔判断结果查询 

 

表记录增删改总结:

mysql数据操作: DML

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。    
技术图片
#增insert into:
    (1)单条插入
        insert into 表名 value(值1,值2,...);
    (2)多条插入
        insert into 表名 values(值1,值2,...),(值1,值2,...),...;
    (3)指定字段插入
        insert into 表名(字段1,字段2,字段3,...) values(值1,值2,值3,...);
    (4)查询结果插入
        insert into 表名(字段1,字段2,字段3,...) select (字段1,字段2,字段3,...) from 表名1;
#删delete from:
    (1)清空列表
        delete from 表名;
    (2)删除某条记录
        delete from 表名 where 条件;
#改update set:
    (1)更新数据
        update 表名 set 字段=where 条件;
mysql表记录的增删改操作

 增:  

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1)单条插入
        insert into 表名 value(值1,值2,...);
(2)多条插入
        insert into 表名 values(值1,值2,...),(值1,值2,...),...;
(3)指定字段插入
        insert into 表名(字段1,字段2,字段3,...) values(值1,值2,值3,...);
(4)查询结果插入
        insetr into 表名(字段1,字段2,字段3,...) select (字段1,字段2,字段3,...) from 表名1;
插入数据insert into

删:  

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删delete from:
    (1)清空列表
        delete from 表名;
    (2)删除某条记录
        delete from 表名 where 条件;
删除数据delete

改:  

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改update set:
    (1)更新数据
        update 表名 set 字段=where 条件;
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’;
更新数据update

单表查:   

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查select from:
    (1)单表查询语法:
        select distinct 字段1,字段2... from  表名
                                                    where 条件
                                                    group by 字段
                                                    having  条件
                                                    order by 字段[asc/desc]
                                                    limit n/m,n

    (2)执行优先级:from>where>group by>select>having>order by>limit
        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.执行select(去重)
        5.将分组的结果进行having过滤
        6.将结果按条件排序:order by
        7.限制结果的显示条数limit

    (3)简单查询:
        1.重命名查询as:
            select * from 表名
            select 字段 as 自定义字段名 from 表名
        2.去重查询distinct:
            select distinct 字段 from 表名
        3.四则运算查询+-*/%等:
            select 字段*n from 表名;
        4.定义格式查询concat:
            select concat(字符串,字段1,字符串,字段2...) from 表名;
            select concat_ws(连接字符串,字段1,字段2 ,...) from 表名;


    (4)where约束条件:
        1.比较运算:>,<,=,>=,<=,!=,<>
        2.between m and n  m到n之间的值(包括m、n)
        3.in(a,b,c...)   在a,b,c...中的值
        4.逻辑运算:andornot
        5.模糊条件 like %/_      通配符:%表示任意个字符;  _下划线表示一个字符

    (5group by 分组:
        分组查询获取其他字段:
            GROUP BY关键字和GROUP_CONCAT()函数一起使用
    (6)having过滤:
        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
    (7order by排序:
        asc 顺序  desc 逆序
    (8)limit限制条数
        limit n #默认初始位置为0 取n个
        limit m,n #从m开始,往后取n个

    (9)聚合函数:
        聚合函数聚合的是组的内容,若是没有分组,则默认一组。
        count()        max()        min()        avg()        sum()
查询语法、聚合函数及关键字优先级
查select from:
(1)单表查询语法:
select distinct 字段1,字段2... from 表名
where 条件
group by 字段
having 条件
order by 字段[asc/desc]
limit n/m,n

(2)执行优先级:from>where>group by>select>having>order by>limit
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.执行select(去重)
5.将分组的结果进行having过滤
6.将结果按条件排序:order by
7.限制结果的显示条数limit

 单表数据准备: 

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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,
emp_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 |
| emp_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(emp_name,sex,age,hire_date,post,salary,office,depart_id) values
(egon,male,18,20170301,教学部门,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
表创建

  简单查询:

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

    SELECT * FROM employee;

    SELECT emp_name,salary FROM employee;

#避免重复DISTINCT
    SELECT DISTINCT post FROM employee;    

#通过四则运算查询
    SELECT emp_name, salary*12 FROM employee;
    SELECT emp_name, salary*12 AS Annual_salary FROM employee;
    SELECT emp_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: ,emp_name,  年薪: , salary*12)  AS Annual_salary 
   FROM employee;
   
   CONCAT_WS() 第一个参数为分隔符
   SELECT CONCAT_WS(:,emp_name,salary*12)  AS Annual_salary 
   FROM employee;

   结合CASE语句:
   SELECT
       (
           CASE
           WHEN emp_name = jingliyang THEN
               emp_name
           WHEN emp_name = alex THEN
               CONCAT(emp_name,_BIGSB)
           ELSE
               concat(emp_name, SB)
           END
       ) as new_name
   FROM
       employee;
简单查询详解
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# 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:,emp_name,>,<薪资:,salary,>) from employee;
# select concat(<名字:,emp_name,>),concat(<薪资:,salary,>) from employee;
# select distinct post from employee;
# select emp_name,salary*12 as annual_year from employee;
‘‘‘
简单查询示例

 

   where约束: 

where字句中可以使用:

  1. 比较运算符:> < >= <= <> !=
  2. between 80 and 100 值在80到100之间
  3. in(80,90,100) 值是80或90或100
  4. like ‘e%‘
      通配符可以是%或_,
      %表示任意多字符
      _表示一个字符 
  5. 逻辑运算符:在多个条件直接可以使用逻辑运算符 and or not

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

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

    SELECT emp_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 emp_name,post_comment FROM employee 
        WHERE post_comment IS NULL;

    SELECT emp_name,post_comment FROM employee 
        WHERE post_comment IS NOT NULL;
        
    SELECT emp_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 emp_name,salary FROM employee 
        WHERE salary=3000 OR salary=3500 OR salary=4000 OR salary=9000 ;
    
    SELECT emp_name,salary FROM employee 
        WHERE salary IN (3000,3500,4000,9000) ;

    SELECT emp_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 emp_name LIKE eg%;

    通配符’_’
    SELECT * FROM employee 
            WHERE emp_name LIKE al__;
where条件查询详解
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# 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
‘‘‘
# select emp_name,age from employee where post=teacher;
# select emp_name,age from employee where post=teacher and age>30;
# select emp_name,age,salary from employee where post=teacher and salary between 1000 and 9000;
# select *from employee where post_comment is not null;
# select emp_name,age,salary from employee where post=teacher and salary in(10000,9000,30000);
# select emp_name,age,salary from employee where post=teacher and salary  not in (10000,9000,30000);
# select emp_name,salary*12 as annul_salary from employee where post=teacher and emp_name like jin%;
‘‘‘
where查询示例

   group by 分组:  

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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(emp_name) FROM employee GROUP BY post;#按照岗位分组,并查看组内成员名
    SELECT post,GROUP_CONCAT(emp_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
group by 查询详解

  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

技术图片
#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;
聚合函数详解
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# 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
‘‘‘
# select post,group_concat(emp_name)from employee group by post;
# select post,count(emp_name)from employee group by post;
# select sex,count(emp_name)from employee group by sex;
# select post,group_concat(salary)from employee group by post;
# select post,avg(salary)from employee group by post;
# select post,max(salary)from employee group by post;
# select post,min(salary)from employee group by post;
# select sex,avg(salary)from employee group by sex;
聚合函数查询示例

  having过滤:

#!!!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
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mysql> select @@sql_mode;
+--------------------+
| @@sql_mode         |
+--------------------+
| ONLY_FULL_GROUP_BY |
+--------------------+
row in set (0.00 sec)

mysql> select * from emp where salary > 100000;
+----+------+------+-----+------------+---------+--------------+------------+--------+-----------+
| id | emp_name | sex  | age | hire_date  | post    | post_comment | salary     | office | depart_id |
+----+------+------+-----+------------+---------+--------------+------------+--------+-----------+
|  2 | alex | male |  78 | 2015-03-02 | teacher | NULL         | 1000000.31 |    401 |         1 |
+----+------+------+-----+------------+---------+--------------+------------+--------+-----------+
row in set (0.00 sec)

mysql> select post,group_concat(emp_name) from emp group by post having salary > 10000;#错误,分组后无法直接取到salary字段
ERROR 1054 (42S22): Unknown column salary in having clause
mysql> select post,group_concat(emp_name) from emp group by post having avg(salary) > 10000;
+-----------+-------------------------------------------------------+
| post | group_concat(emp_name) |
+-----------+-------------------------------------------------------+
| operation | 程咬铁,程咬铜,程咬银,程咬金,张野 |
| teacher | 成龙,jinxin,jingliyang,liwenzhou,yuanhao,wupeiqi,alex |
+-----------+-------------------------------------------------------+
rows in set (0.00 sec)
having过滤查询详解
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# 1. 查询各岗位内包含的员工个数小于2的岗位名、岗位内包含员工名字、个数
# 3. 查询各岗位平均薪资大于10000的岗位名、平均工资
# 4. 查询各岗位平均薪资大于10000且小于20000的岗位名、平均工资
‘‘‘
# select post, group_concat(emp_name),  count(emp_name) from employee group by post having count(emp_name)<2;
# select post,avg(salary) from employee group by post having avg(salary)>10000;
# select post,avg(salary) from employee group by post having 20000>avg(salary) and avg(salary)>10000;
having过滤查询示例

   order by  排序  

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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;
order by排序详解
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# 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
‘‘‘
# select * from employee order by age,hire_date desc;
# select post,avg(salary)as avg_salary from employee group by post having avg(salary)>10000 order by avg_salary;
# select post,avg(salary)as avg_salary from employee group by post having avg(salary)>10000 order by avg_salary desc;
‘‘‘
order by 排序查询示例

  limit 限制 

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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
limit限制查询示例

   使用正则表达式查询 

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SELECT * FROM employee WHERE emp_name REGEXP ^ale;

SELECT * FROM employee WHERE emp_name REGEXP on$;

SELECT * FROM employee WHERE emp_name REGEXP m2;


小结:对字符串匹配的方式
WHERE emp_name = egon;
WHERE emp_name LIKE yua%;
WHERE emp_name REGEXP on$;
正则表达式查询
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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 emp_name regexp ^jin.*[gn]$;
正则表达式查询示例

 单表操作实例:(对日期的处理可以使用year(日期字段))  

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‘‘‘
书名 作者 出版社 价格 出版日期(publish_date)
倚天屠龙记 egon 北京工业地雷出版社 70 2019-7-1
九阳神功 alex 人民音乐不好听出版社 5 2018-7-4
九阴真经 yuan 北京工业地雷出版社 62 2017-7-12
九阴白骨爪 jin 人民音乐不好听出版社 40 2019–8-7
独孤九剑 alex 北京工业地雷出版社 12 2017-9-1
降龙十巴掌 egon 知识产权没有用出版社 20 2019-7-5
葵花宝典 yuan 知识产权没有用出版社 33 2019–8-2

0.建表book,并向表中插入数据
1.查询egon写的所有书和价格
2.找出最贵的图书的价格
3.求所有图书的均价
4.将所有图书按照出版日期排序
5.查询alex写的所有书的平均价格
6.查询人民音乐不好听出版社出版的所有图书
7.查询人民音乐出版社出版的alex写的所有图书和价格
8.找出出版图书均价最高的作者
9.找出最新出版的图书的作者和出版社
10.显示各出版社出版的所有图书
11.查找价格最高的图书,并将它的价格修改为50元
12.删除价格最低的那本书对应的数据
13.将所有alex写的书作业修改成alexsb
14.select year(publish_date) from book
自己研究上面sql语句中的year函数的功能,完成需求:
将所有2017年出版的图书从数据库中删除

‘‘‘


# create table book(id int primary key auto_increment,
#     b_name char(16),
#     b_author char(8),
#     b_press varchar(24),
#     b_price float(5,2),
#     publish_date date
#     );


# insert into book(b_name,b_author,b_press,b_price,publish_date) values
#     (‘倚天屠龙记‘,‘egon‘,‘北京工业地雷出版社‘,70,‘2019-7-1‘),
#     (‘九阳神功‘,‘alex‘,‘人民音乐不好听出版社‘,5,‘2018-7-4‘),
#     (‘九阴真经‘,‘yuan‘,‘北京工业地雷出版社‘,62,‘2017-7-12‘),
#     (‘九阴白骨爪‘,‘jin‘,‘人民音乐不好听出版社‘,40,‘2019-8-7‘),
#     (‘孤独九剑‘,‘alex‘,‘北京工业地雷出版社‘,12,‘2017-9-1‘),
#     (‘降龙十八掌‘,‘egon‘,‘知识产权没有用出版社‘,20,‘2019-7-5‘),
#     (‘葵花宝典‘,‘yuan‘,‘知识产权没有用出版社‘,33,‘2019-8-2‘);
‘‘‘
mysql> select * from book;
    +----+-----------------+----------+--------------------------------+---------+--------------+
    | id | b_name          | b_author | b_press                        | b_price | publish_date |
    +----+-----------------+----------+--------------------------------+---------+--------------+
    |  1 | 倚天屠龙记      | egon     | 北京工业地雷出版社             |   70.00 | 2019-07-01   |
    |  2 | 九阳神功        | alex     | 人民音乐不好听出版社           |    5.00 | 2018-07-04   |
    |  3 | 九阴真经        | yuan     | 北京工业地雷出版社             |   62.00 | 2017-07-12   |
    |  4 | 九阴白骨爪      | jin      | 人民音乐不好听出版社           |   40.00 | 2019-08-07   |
    |  5 | 孤独九剑        | alex     | 北京工业地雷出版社             |   12.00 | 2017-09-01   |
    |  6 | 降龙十八掌      | egon     | 知识产权没有用出版社           |   20.00 | 2019-07-05   |
    |  7 | 葵花宝典        | yuan     | 知识产权没有用出版社           |   33.00 | 2019-08-02   |
    +----+-----------------+----------+--------------------------------+---------+--------------+
    7 rows in set (0.00 sec)
‘‘‘

# select b_name,b_price from book where b_author=‘egon‘;
‘‘‘
mysql> select b_name,b_price from book where b_author=‘egon‘;
    +-----------------+---------+
    | b_name          | b_price |
    +-----------------+---------+
    | 倚天屠龙记      |   70.00 |
    | 降龙十八掌      |   20.00 |
    +-----------------+---------+
    2 rows in set (0.01 sec)
‘‘‘

# select max(b_price) from book;
‘‘‘
mysql> select max(b_price) from book;
    +--------------+
    | max(b_price) |
    +--------------+
    |        70.00 |
    +--------------+
    1 row in set (0.01 sec)
‘‘‘

# select avg(b_price) as avg_price from book;
‘‘‘
mysql> select avg(b_price) as avg_price from book;
    +-----------+
    | avg_price |
    +-----------+
    | 34.571429 |
    +-----------+
    1 row in set (0.00 sec)
‘‘‘

# select * from book order by publish_date;
‘‘‘
mysql> select * from book order by publish_date;
    +----+-----------------+----------+--------------------------------+---------+--------------+
    | id | b_name          | b_author | b_press                        | b_price | publish_date |
    +----+-----------------+----------+--------------------------------+---------+--------------+
    |  3 | 九阴真经        | yuan     | 北京工业地雷出版社             |   62.00 | 2017-07-12   |
    |  5 | 孤独九剑        | alex     | 北京工业地雷出版社             |   12.00 | 2017-09-01   |
    |  2 | 九阳神功        | alex     | 人民音乐不好听出版社           |    5.00 | 2018-07-04   |
    |  1 | 倚天屠龙记      | egon     | 北京工业地雷出版社             |   70.00 | 2019-07-01   |
    |  6 | 降龙十八掌      | egon     | 知识产权没有用出版社           |   20.00 | 2019-07-05   |
    |  7 | 葵花宝典        | yuan     | 知识产权没有用出版社           |   33.00 | 2019-08-02   |
    |  4 | 九阴白骨爪      | jin      | 人民音乐不好听出版社           |   40.00 | 2019-08-07   |
    +----+-----------------+----------+--------------------------------+---------+--------------+
    7 rows in set (0.01 sec)
‘‘‘

# select b_author,avg(b_price) from book where b_author=‘alex‘;
‘‘‘
mysql> select b_author,avg(b_price) from book where b_author=‘alex‘;
    +----------+--------------+
    | b_author | avg(b_price) |
    +----------+--------------+
    | alex     |     8.500000 |
    +----------+--------------+
    1 row in set (0.00 sec)
‘‘‘

# select b_press,group_concat(b_name) from book where b_press=‘人民音乐不好听出版社‘ group by b_press;
‘‘‘
    +--------------------------------+------------------------------+
    | b_press                        | group_concat(b_name)         |
    +--------------------------------+------------------------------+
    | 人民音乐不好听出版社           | 九阳神功,九阴白骨爪          |
    +--------------------------------+------------------------------+
    1 row in set (0.00 sec)
‘‘‘

# select  b_press,b_author,b_name,b_price from book where b_press=‘人民音乐不好听出版社‘ and b_author=‘alex‘;
‘‘‘
mysql> select  b_press,b_author,b_name,b_price from book where b_press=‘人民音乐不好听出版社‘ and b_author=‘alex‘;
    +--------------------------------+----------+--------------+---------+
    | b_press                        | b_author | b_name       | b_price |
    +--------------------------------+----------+--------------+---------+
    | 人民音乐不好听出版社           | alex     | 九阳神功     |    5.00 |
    +--------------------------------+----------+--------------+---------+
    1 row in set (0.00 sec)
‘‘‘

# select b_author,avg(b_price) from book group by b_author having avg(b_price) order by avg(b_price) desc limit 1;
‘‘‘
mysql> select b_author,avg(b_price) from book group by b_author having avg(b_price) order by avg(b_price) desc limit 1;
    +----------+--------------+
    | b_author | avg(b_price) |
    +----------+--------------+
    | yuan     |    47.500000 |
    +----------+--------------+
    1 row in set (0.00 sec)
‘‘‘


# select b_press,group_concat(b_name)as press_books from book group by b_press;
‘‘‘
mysql> select b_press,group_concat(b_name)as press_books from book group by b_press;
    +--------------------------------+-------------------------------------------+
    | b_press                        | press_books                               |
    +--------------------------------+-------------------------------------------+
    | 人民音乐不好听出版社           | 九阳神功,九阴白骨爪                       |
    | 北京工业地雷出版社             | 倚天屠龙记,九阴真经,孤独九剑              |
    | 知识产权没有用出版社           | 降龙十八掌,葵花宝典                       |
    +--------------------------------+-------------------------------------------+
    3 rows in set (0.00 sec)
‘‘‘


# select max(b_price) from book;
# update book  set b_price=50 where b_price=70.0 ;
#update book  set b_price=50 order by b_price desc limit 1;#( 只能设置一个)
‘‘‘
mysql> select * from book;
    +----+-----------------+----------+--------------------------------+---------+--------------+
    | id | b_name          | b_author | b_press                        | b_price | publish_date |
    +----+-----------------+----------+--------------------------------+---------+--------------+
    |  1 | 倚天屠龙记      | egon     | 北京工业地雷出版社             |   50.00 | 2019-07-01   |
    |  2 | 九阳神功        | alex     | 人民音乐不好听出版社           |    5.00 | 2018-07-04   |
    |  3 | 九阴真经        | yuan     | 北京工业地雷出版社             |   62.00 | 2017-07-12   |
    |  4 | 九阴白骨爪      | jin      | 人民音乐不好听出版社           |   40.00 | 2019-08-07   |
    |  5 | 孤独九剑        | alex     | 北京工业地雷出版社             |   12.00 | 2017-09-01   |
    |  6 | 降龙十八掌      | egon     | 知识产权没有用出版社           |   20.00 | 2019-07-05   |
    |  7 | 葵花宝典        | yuan     | 知识产权没有用出版社           |   33.00 | 2019-08-02   |
    +----+-----------------+----------+--------------------------------+---------+--------------+
    7 rows in set (0.00 sec)
‘‘‘

# select min(b_price) from book;
# delete from book where b_price=5;
‘‘‘
mysql> select * from book;
    +----+-----------------+----------+--------------------------------+---------+--------------+
    | id | b_name          | b_author | b_press                        | b_price | publish_date |
    +----+-----------------+----------+--------------------------------+---------+--------------+
    |  1 | 倚天屠龙记      | egon     | 北京工业地雷出版社             |   50.00 | 2019-07-01   |
    |  3 | 九阴真经        | yuan     | 北京工业地雷出版社             |   62.00 | 2017-07-12   |
    |  4 | 九阴白骨爪      | jin      | 人民音乐不好听出版社           |   40.00 | 2019-08-07   |
    |  5 | 孤独九剑        | alex     | 北京工业地雷出版社             |   12.00 | 2017-09-01   |
    |  6 | 降龙十八掌      | egon     | 知识产权没有用出版社           |   20.00 | 2019-07-05   |
    |  7 | 葵花宝典        | yuan     | 知识产权没有用出版社           |   33.00 | 2019-08-02   |
    +----+-----------------+----------+--------------------------------+---------+--------------+
    6 rows in set (0.00 sec)
‘‘‘

# update book set b_author=‘alexsb‘ where b_author=‘alex‘;
‘‘‘
mysql>  select * from book;
    +----+-----------------+----------+--------------------------------+---------+--------------+
    | id | b_name          | b_author | b_press                        | b_price | publish_date |
    +----+-----------------+----------+--------------------------------+---------+--------------+
    |  1 | 倚天屠龙记      | egon     | 北京工业地雷出版社             |   50.00 | 2019-07-01   |
    |  3 | 九阴真经        | yuan     | 北京工业地雷出版社             |   62.00 | 2017-07-12   |
    |  4 | 九阴白骨爪      | jin      | 人民音乐不好听出版社           |   40.00 | 2019-08-07   |
    |  5 | 孤独九剑        | alexsb   | 北京工业地雷出版社             |   12.00 | 2017-09-01   |
    |  6 | 降龙十八掌      | egon     | 知识产权没有用出版社           |   20.00 | 2019-07-05   |
    |  7 | 葵花宝典        | yuan     | 知识产权没有用出版社           |   33.00 | 2019-08-02   |
    +----+-----------------+----------+--------------------------------+---------+--------------+
    6 rows in set (0.00 sec)
‘‘‘

# select year(publish_date) from book
‘‘‘
mysql> select year(publish_date) from book;
    +--------------------+
    | year(publish_date) |
    +--------------------+
    |               2019 |
    |               2017 |
    |               2019 |
    |               2017 |
    |               2019 |
    |               2019 |
    +--------------------+
    6 rows in set (0.00 sec)
‘‘‘


# delete from book where year(publish_date)=2017;
‘‘‘
mysql> delete from book where year(publish_date)=2017;
    Query OK, 2 rows affected (0.00 sec)

mysql> select * from book;
    +----+-----------------+----------+--------------------------------+---------+--------------+
    | id | b_name          | b_author | b_press                        | b_price | publish_date |
    +----+-----------------+----------+--------------------------------+---------+--------------+
    |  1 | 倚天屠龙记      | egon     | 北京工业地雷出版社             |   50.00 | 2019-07-01   |
    |  4 | 九阴白骨爪      | jin      | 人民音乐不好听出版社           |   40.00 | 2019-08-07   |
    |  6 | 降龙十八掌      | egon     | 知识产权没有用出版社           |   20.00 | 2019-07-05   |
    |  7 | 葵花宝典        | yuan     | 知识产权没有用出版社           |   33.00 | 2019-08-02   |
    +----+-----------------+----------+--------------------------------+---------+--------------+
    4 rows in set (0.00 sec)
‘‘‘
单表操作实例

 

多表查:

连表查询
表和表是怎么连在一起的
通过笛卡尔积得到一个全量拼接的大表
select * from 表1,表2;两个表的记录会完全拼接

内连接(inner join) 双方能够互相匹配的项才会被显示出来
select * from 表1 inner join 表2 [as 新表名] on 条件;


外连接
左外连接(left join) 只完整的显示左表中的所有内容,以及右表中与左表匹配的项
select * from 表1 left join 表2 on 条件;

右外连接(right join) 只完整的显示右表中的所有内容,以及左表中与右表匹配的项
select * from 表1 right join 表2 on 条件;

全外连接 永远显示左表和右表中所有的项
select * from 表1 left join 表2 on 条件
union
select * from 表1 right join 表2 on 条件;

子查询(效率低)
总是在一个select中 套着另一个select语句
嵌套着的这个select语句就是一个子查询语句

 

 多表数据准备:

  employee表中的dep_id可以设置外键关联到department表

技术图片
#建表
create table department(
id int,
name varchar(20) 
);

create table employee(
id int primary key auto_increment,
name varchar(20),
sex enum(male,female) not null default male,
age int,
dep_id int
);

#插入数据
insert into department values
(200,技术),
(201,人力资源),
(202,销售),
(203,运营);

insert into employee(name,sex,age,dep_id) values
(egon,male,18,200),
(alex,female,48,201),
(wupeiqi,male,38,201),
(yuanhao,female,28,202),
(liwenzhou,male,18,200),
(jingliyang,female,18,204)
;


#查看表结构和数据
mysql> desc department;
+-------+-------------+------+-----+---------+-------+
| Field | Type | Null | Key | Default | Extra |
+-------+-------------+------+-----+---------+-------+
| id | int(11) | YES | | NULL | |
| name | varchar(20) | YES | | NULL | |
+-------+-------------+------+-----+---------+-------+

mysql> desc employee;
+--------+-----------------------+------+-----+---------+----------------+
| Field | Type | Null | Key | Default | Extra |
+--------+-----------------------+------+-----+---------+----------------+
| id | int(11) | NO | PRI | NULL | auto_increment |
| name | varchar(20) | YES | | NULL | |
| sex | enum(male,female) | NO | | male | |
| age | int(11) | YES | | NULL | |
| dep_id | int(11) | YES | | NULL | |
+--------+-----------------------+------+-----+---------+----------------+

mysql> select * from department;
+------+--------------+
| id | name |
+------+--------------+
| 200 | 技术 |
| 201 | 人力资源 |
| 202 | 销售 |
| 203 | 运营 |
+------+--------------+

mysql> select * from employee;
+----+------------+--------+------+--------+
| id | name | sex | age | dep_id |
+----+------------+--------+------+--------+
| 1 | egon | male | 18 | 200 |
| 2 | alex | female | 48 | 201 |
| 3 | wupeiqi | male | 38 | 201 |
| 4 | yuanhao | female | 28 | 202 |
| 5 | liwenzhou | male | 18 | 200 |
| 6 | jingliyang | female | 18 | 204 |
+----+------------+--------+------+--------+
表department与employee

连表查询

SELECT 字段列表
    FROM 表1 INNER|LEFT|RIGHT JOIN 表2 [as 新表名]  
ON 表1.字段 = 表2.字段; 

  1 交叉连接:不适用任何匹配条件。生成笛卡尔积  

技术图片
mysql> select * from employee,department;
+----+------------+--------+------+--------+------+--------------+
| id | name       | sex    | age  | dep_id | id   | name         |
+----+------------+--------+------+--------+------+--------------+
|  1 | egon       | male   |   18 |    200 |  200 | 技术         |
|  1 | egon       | male   |   18 |    200 |  201 | 人力资源     |
|  1 | egon       | male   |   18 |    200 |  202 | 销售         |
|  1 | egon       | male   |   18 |    200 |  203 | 运营         |
|  2 | alex       | female |   48 |    201 |  200 | 技术         |
|  2 | alex       | female |   48 |    201 |  201 | 人力资源     |
|  2 | alex       | female |   48 |    201 |  202 | 销售         |
|  2 | alex       | female |   48 |    201 |  203 | 运营         |
|  3 | wupeiqi    | male   |   38 |    201 |  200 | 技术         |
|  3 | wupeiqi    | male   |   38 |    201 |  201 | 人力资源     |
|  3 | wupeiqi    | male   |   38 |    201 |  202 | 销售         |
|  3 | wupeiqi    | male   |   38 |    201 |  203 | 运营         |
|  4 | yuanhao    | female |   28 |    202 |  200 | 技术         |
|  4 | yuanhao    | female |   28 |    202 |  201 | 人力资源     |
|  4 | yuanhao    | female |   28 |    202 |  202 | 销售         |
|  4 | yuanhao    | female |   28 |    202 |  203 | 运营         |
|  5 | liwenzhou  | male   |   18 |    200 |  200 | 技术         |
|  5 | liwenzhou  | male   |   18 |    200 |  201 | 人力资源     |
|  5 | liwenzhou  | male   |   18 |    200 |  202 | 销售         |
|  5 | liwenzhou  | male   |   18 |    200 |  203 | 运营         |
|  6 | jingliyang | female |   18 |    204 |  200 | 技术         |
|  6 | jingliyang | female |   18 |    204 |  201 | 人力资源     |
|  6 | jingliyang | female |   18 |    204 |  202 | 销售         |
|  6 | jingliyang | female |   18 |    204 |  203 | 运营         |
+----+------------+--------+------+--------+------+--------------+
交叉连接,笛卡尔积

  2 内连接:只连接匹配的行

技术图片
#找两张表共有的部分,相当于利用条件从笛卡尔积结果中筛选出了正确的结果
#department没有204这个部门,因而employee表中关于204这条员工信息没有匹配出来
mysql> select employee.id,employee.name,employee.age,employee.sex,department.name from employee inner join department on employee.dep_id=department.id; 
+----+-----------+------+--------+--------------+
| id | name      | age  | sex    | name         |
+----+-----------+------+--------+--------------+
|  1 | egon      |   18 | male   | 技术         |
|  2 | alex      |   48 | female | 人力资源     |
|  3 | wupeiqi   |   38 | male   | 人力资源     |
|  4 | yuanhao   |   28 | female | 销售         |
|  5 | liwenzhou |   18 | male   | 技术         |
+----+-----------+------+--------+--------------+

#上述sql等同于
mysql> select employee.id,employee.name,employee.age,employee.sex,department.name from employee,department where employee.dep_id=department.id;
inner join内连接
  3 外链接之左连接:优先显示左表全部记录 
技术图片
#以左表为准,即找出所有员工信息,当然包括没有部门的员工
#本质就是:在内连接的基础上增加左边有右边没有的结果
mysql> select employee.id,employee.name,department.name as depart_name from employee left join department on employee.dep_id=department.id;
+----+------------+--------------+
| id | name       | depart_name  |
+----+------------+--------------+
|  1 | egon       | 技术         |
|  5 | liwenzhou  | 技术         |
|  2 | alex       | 人力资源     |
|  3 | wupeiqi    | 人力资源     |
|  4 | yuanhao    | 销售         |
|  6 | jingliyang | NULL         |
+----+------------+--------------+
left join左外连接

  4 外链接之右连接:优先显示右表全部记录

技术图片
#以右表为准,即找出所有部门信息,包括没有员工的部门
#本质就是:在内连接的基础上增加右边有左边没有的结果
mysql> select employee.id,employee.name,department.name as depart_name from employee right join department on employee.dep_id=department.id;
+------+-----------+--------------+
| id   | name      | depart_name  |
+------+-----------+--------------+
|    1 | egon      | 技术         |
|    2 | alex      | 人力资源     |
|    3 | wupeiqi   | 人力资源     |
|    4 | yuanhao   | 销售         |
|    5 | liwenzhou | 技术         |
| NULL | NULL      | 运营         |
+------+-----------+--------------+
right join右外连接

  5 全外连接:显示左右两个表全部记录

技术图片
全外连接:在内连接的基础上增加左边有右边没有的和右边有左边没有的结果
#注意:mysql不支持全外连接 full JOIN
#强调:mysql可以使用此种方式间接实现全外连接
select * from employee left join department on employee.dep_id = department.id
union
select * from employee right join department on employee.dep_id = department.id
;
#查看结果
+------+------------+--------+------+--------+------+--------------+
| id   | name       | sex    | age  | dep_id | id   | name         |
+------+------------+--------+------+--------+------+--------------+
|    1 | egon       | male   |   18 |    200 |  200 | 技术         |
|    5 | liwenzhou  | male   |   18 |    200 |  200 | 技术         |
|    2 | alex       | female |   48 |    201 |  201 | 人力资源     |
|    3 | wupeiqi    | male   |   38 |    201 |  201 | 人力资源     |
|    4 | yuanhao    | female |   28 |    202 |  202 | 销售         |
|    6 | jingliyang | female |   18 |    204 | NULL | NULL        |
| NULL | NULL       | NULL   | NULL |   NULL |  203 | 运营         |
+------+------------+--------+------+--------+------+--------------+

#注意 union与union all的区别:union会去掉相同的纪录
left join-uion-right join全外连接

  6.符合条件连接查询  

技术图片
#示例1:以内连接的方式查询employee和department表,并且employee表中的age字段值必须大于25,即找出年龄大于25岁的员工以及员工所在的部门
select employee.name,department.name from employee inner join department
    on employee.dep_id = department.id
    where age > 25;

#示例2:以内连接的方式查询employee和department表,并且以age字段的升序方式显示
select employee.id,employee.name,employee.age,department.name from employee,department
    where employee.dep_id = department.id
    and age > 25
    order by age asc;
连表查询结果筛选

子查询

#1:子查询是将一个查询语句嵌套在另一个查询语句中。
#2:内层查询语句的查询结果,可以为外层查询语句提供查询条件。
#3:子查询中可以包含:IN、NOT IN、ANY、ALL、EXISTS 和 NOT EXISTS等关键字
#4:还可以包含比较运算符:= 、 !=、> 、<等

   1. 带IN关键字的子查询 

技术图片
#查询平均年龄在25岁以上的部门名
select id,name from department
    where id in 
        (select dep_id from employee group by dep_id having avg(age) > 25);

#查看技术部员工姓名
select name from employee
    where dep_id in 
        (select id from department where name=技术);

#查看不足1人的部门名(子查询得到的是有人的部门id)
select name from department where id not in (select distinct dep_id from employee);
带关键字in的子查询

    2 .带比较运算符的子查询

 

技术图片
#比较运算符:=!=>>=<<=<>
#查询大于所有人平均年龄的员工名与年龄
mysql> select name,age from emp where age > (select avg(age) from emp);
+---------+------+
| name    | age  |
+---------+------+
| alex    | 48   |
| wupeiqi | 38   |
+---------+------+
rows in set (0.00 sec)


#查询大于部门内平均年龄的员工名、年龄(省略了重命名关键字as)
select t1.name,t1.age from emp t1
inner join 
(select dep_id,avg(age) avg_age from emp group by dep_id) t2
on t1.dep_id = t2.dep_id
where t1.age > t2.avg_age;
带比较运算符的子查询

 

   3. 带EXISTS关键字的子查询

EXISTS关字键字表示存在。在使用EXISTS关键字时,内层查询语句不返回查询的记录。
而是返回一个真假值:True或False,当返回True时,外层查询语句将进行查询;当返回值为False时,外层查询语句不进行查询

技术图片
#department表中存在dept_id=203,Ture
mysql> select * from employee
    ->     where exists
    ->         (select id from department where id=200);
+----+------------+--------+------+--------+
| id | name       | sex    | age  | dep_id |
+----+------------+--------+------+--------+
|  1 | egon       | male   |   18 |    200 |
|  2 | alex       | female |   48 |    201 |
|  3 | wupeiqi    | male   |   38 |    201 |
|  4 | yuanhao    | female |   28 |    202 |
|  5 | liwenzhou  | male   |   18 |    200 |
|  6 | jingliyang | female |   18 |    204 |
+----+------------+--------+------+--------+

#department表中存在dept_id=205,False
mysql> select * from employee
    ->     where exists
    ->         (select id from department where id=204);
Empty set (0.00 sec)
带exists关键字的布尔判断子查询

 

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