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:
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
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;
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;
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;
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’;
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
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;
# 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; ‘‘‘
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__‘;
# 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%‘; ‘‘‘
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
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;
# 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;
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)
# 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;
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;
# 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; ‘‘‘
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
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$‘; SELECT * FROM employee WHERE emp_name REGEXP ‘m2‘; 小结:对字符串匹配的方式 WHERE emp_name = ‘egon‘; WHERE emp_name LIKE ‘yua%‘; WHERE emp_name REGEXP ‘on$‘;
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]$‘;
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) ‘‘‘
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 | +----+------------+--------+------+--------+
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 | +----+------------+--------+------+--------+------+--------------+
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;
#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 | +----+------------+--------------+
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 | +------+-----------+--------------+
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
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;
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);
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;
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)
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