数据库表的增删改查操作：
增、删、改
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
- 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。
#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=值 where 条件;
mysql表记录的增删改操作
增：
（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：
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：
改update set：
（1）更新数据
update 表名 set 字段=值 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：
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：and、or 、not
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
（5）group 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
（7）order 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：
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：
#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
# 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
#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
# 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：
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
#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
# 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
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
# 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
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
# 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
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
SELECT * FROM employee WHERE emp_name REGEXP ‘^ale‘;
SELECT * FROM employee WHERE emp_name REGEXP ‘on$‘;
SELECT * FROM employee WHERE emp_name REGEXP ‘m{2}‘;
小结：对字符串匹配的方式
WHERE emp_name = ‘egon‘;
WHERE emp_name LIKE ‘yua%‘;
WHERE emp_name REGEXP ‘on$‘;
正则表达式查询
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)）
‘‘‘
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
#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
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
#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
#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
#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
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
#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
#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
#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
#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
原文地址：https://www.cnblogs.com/open-yang/p/11412496.html
时间： 2024-09-27 17:35:22