MySQL：数据的增删改 + 单表查询 + 多表查询
数据的增删改
- 插入数据 INSERT
- 更新数据 UPDATE
- 删除数据 DELETE
在mysql中其实最重要的不是这三大操作，而是查询数据最重要
一、 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 二、插入数据 INSERT 1. 插入完整数据（顺序插入） 语法一： INSERT INTO 表名(字段1,字段2,字段3…字段n) VALUES(值1,值2,值3…值n); 语法二： INSERT INTO 表名 VALUES (值1,值2,值3…值n); 2. 指定字段插入数据 语法： INSERT INTO 表名(字段1,字段2,字段3…) VALUES (值1,值2,值3…); 3. 插入多条记录 语法： INSERT INTO 表名 VALUES (值1,值2,值3…值n), (值1,值2,值3…值n), (值1,值2,值3…值n); 4. 插入查询结果 语法： INSERT INTO 表名(字段1,字段2,字段3…字段n) SELECT (字段1,字段2,字段3…字段n) FROM 表2 WHERE …;
三、更新数据UPDATE 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’;
四、删除数据DELETE 语法： DELETE FROM 表名 WHERE CONITION; 示例： DELETE FROM mysql.user WHERE password=’’;
单表查询
语法：
一、单表查询的语法
SELECT 字段1,字段2... FROM 表名 WHERE 条件 GROUP BY field HAVING 筛选 ORDER BY field asc/desc（升序/降序，不写的话默认为升序） LIMIT 限制条数
上述语句是完整语法，where之后的是可有可无的
二、关键字的执行优先级（重点） 重点中的重点：关键字的执行优先级 from where group by having select distinct #去重 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.将分组的结果进行having过滤 5.执行select 6.去重 7.将结果按条件排序：order by asc/desc（升序/降序） 8.限制结果的显示条数
示例：按照下表中的字段和数据类型来设计公司员工表，以该表为例对各约束条件进行详细说明：
company.employee 员工id id int 姓名 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
创建员工表并插入记录：
#创建表,设置字段的约束条件 create table employee( id int primary key auto_increment, name varchar(20) not null, sex enum('male','female') not null default 'male', #大部分是男的 age int(3) unsigned not null default 28, hire_date date not null, post varchar(50), post_comment varchar(100), salary double(15,2), office int,#一个部门一个屋 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 | | | salart | double(15,2) | YES | | NULL | | | office | int(11) | YES | | NULL | | | depart_id | int(11) | YES | | NULL | | +--------------+-----------------------+------+-----+---------+----------------+ rows in set (0.08 sec) #插入记录 #三个部门：教学，销售，运营 insert into employee(name ,sex,age,hire_date,post,salary,office,depart_id) values ('egon','male',18,'20170301','老男孩驻沙河办事处外交大使',7300.33,401,1), #以下是教学部 ('alex','male',78,'20150302','teacher',1000000.31,401,1), ('wupeiqi','male',81,'20130305','teacher',8300,401,1), ('yuanhao','male',73,'20140701','teacher',3500,401,1), ('liwenzhou','male',28,'20121101','teacher',2100,401,1), ('jingliyang','female',18,'20110211','teacher',9000,401,1), ('jinxin','male',18,'19000301','teacher',30000,401,1), ('xiaomage','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) ; 创建员工表，并插入记录
where约束
where子句中可以使用：
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 'xiaomagepattern': pattern可以是%或者_ 模糊查询
%：表示任意多个字符，_：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 mysql> select id,emp_name from employee where id > 5; +----+------------+ | id | emp_name | +----+------------+ | 6 | jingliyang | | 7 | jinxin | | 8 | xiaomage | | 9 | 歪歪 | | 10 | 丫丫 | | 11 | 丁丁 | | 12 | 星星 | | 13 | 格格 | | 14 | 张野 | | 15 | 程咬金 | | 16 | 程咬银 | | 17 | 程咬铜 | | 18 | 程咬铁 | #2 多条件查询 mysql> select emp_name from employee where post='teacher' and salary>10000; +----------+ | emp_name | +----------+ | alex | | jinxin | +----------+ #3.关键字BETWEEN AND SELECT name,salary FROM employee WHERE salary BETWEEN 10000 AND 20000; SELECT name,salary FROM employee WHERE salary NOT BETWEEN 10000 AND 20000; #注意''是空字符串，不是null SELECT name,post_comment FROM employee WHERE post_comment=''; 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 mysql> SELECT name,salary FROM employee WHERE salary=3000 OR salary=3500 OR salary=4000 OR salary=9000 ; +------------+---------+ | name | salary | +------------+---------+ | yuanhao | 3500.00 | | jingliyang | 9000.00 | +------------+---------+ rows in set (0.00 sec) mysql> SELECT name,salary FROM employee WHERE salary IN (3000,3500,4000,9000) ; +------------+---------+ | name | salary | +------------+---------+ | yuanhao | 3500.00 | | jingliyang | 9000.00 | +------------+---------+ mysql> SELECT name,salary FROM employee WHERE salary NOT IN (3000,3500,4000,9000) ; +-----------+------------+ | name | salary | +-----------+------------+ | egon | 7300.33 | | alex | 1000000.31 | | wupeiqi | 8300.00 | | liwenzhou | 2100.00 | | jinxin | 30000.00 | | xiaomage | 10000.00 | | 歪歪 | 3000.13 | | 丫丫 | 2000.35 | | 丁丁 | 1000.37 | | 星星 | 3000.29 | | 格格 | 4000.33 | | 张野 | 10000.13 | | 程咬金 | 20000.00 | | 程咬银 | 19000.00 | | 程咬铜 | 18000.00 | | 程咬铁 | 17000.00 | +-----------+------------+ rows in set (0.00 sec) #6:关键字LIKE模糊查询 通配符’%’ mysql> SELECT * FROM employee WHERE name LIKE 'jin%'; +----+------------+--------+-----+------------+---------+--------------+----------+--------+-----------+ | id | name | sex | age | hire_date | post | post_comment | salary | office | depart_id | +----+------------+--------+-----+------------+---------+--------------+----------+--------+-----------+ | 6 | jingliyang | female | 18 | 2011-02-11 | teacher | NULL | 9000.00 | 401 | 1 | | 7 | jinxin | male | 18 | 1900-03-01 | teacher | NULL | 30000.00 | 401 | 1 | +----+------------+--------+-----+------------+---------+--------------+----------+--------+-----------+ rows in set (0.00 sec) 通配符'_' mysql> SELECT age FROM employee WHERE name LIKE 'ale_'; +-----+ | age | +-----+ | 78 | +-----+ row in set (0.00 sec) 练习： 1. 查看岗位是teacher的员工姓名、年龄 2. 查看岗位是teacher且年龄大于30岁的员工姓名、年龄 3. 查看岗位是teacher且薪资在9000-1000范围内的员工姓名、年龄、薪资 4. 查看岗位描述不为NULL的员工信息 5. 查看岗位是teacher且薪资是10000或9000或30000的员工姓名、年龄、薪资 6. 查看岗位是teacher且薪资不是10000或9000或30000的员工姓名、年龄、薪资 7. 查看岗位是teacher且名字是jin开头的员工姓名、年薪 #对应的sql语句 select name,age from employee where post = 'teacher'; select name,age from employee where post='teacher' and age > 30; select name,age,salary from employee where post='teacher' and salary between 9000 and 10000; select * from employee where post_comment is not null; select name,age,salary from employee where post='teacher' and salary in (10000,9000,30000); select name,age,salary from employee where post='teacher' and salary not in (10000,9000,30000); select name,salary*12 from employee where post='teacher' and name like 'jin%'; where约束
group by 分组查询
#1、首先明确一点：分组发生在where之后，即分组是基于where之后得到的记录而进行的,没有where的话，会将所有的记录看做是一组 #2、分组指的是：将所有记录按照某个相同字段进行归类，比如针对员工信息表的职位分组，或者按照性别进行分组等 #3、为何要分组呢？ 取每个部门的最高工资 取每个部门的员工数 取男人数和女人数 小窍门：‘每’这个字后面的字段，就是我们分组的依据 #4、大前提： 可以按照任意字段分组，但是分组完毕后，比如group by post，只能查看post字段，如果想查看组内信息，需要借助于聚合函数
1、select * from employee group by post 是没有任何意义的，
由于没有设置ONLY_FULL_GROUP_BY,于是也可以有结果，默认都是组内的第一条记录，但其实这是没有意义的
mysql> select * from employee group by post; +----+--------+--------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+ | id | name | sex | age | hire_date | post | post_comment | salary | office | depart_id | +----+--------+--------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+ | 14 | 张野 | male | 28 | 2016-03-11 | operation | NULL | 10000.13 | 403 | 3 | | 9 | 歪歪 | female | 48 | 2015-03-11 | sale | NULL | 3000.13 | 402 | 2 | | 2 | alex | male | 78 | 2015-03-02 | teacher | | 1000000.31 | 401 | 1 | | 1 | egon | male | 18 | 2017-03-01 | 老男孩驻沙河办事处外交大使 | NULL | 7300.33 | 401 | 1 | +----+--------+--------+-----+------------+-----------------------------------------+--------------+------------+--------+-----------+ 4 rows in set (0.00 sec)
2、设置ONLY_FULL_GROUP_BY
如果想分组，就必须设置全局的sql的模式为，ONLY_FULL_GROUP_BY
方式一：更改数据库的配置信息
E:\Program Files (x86)\mysql-5.7.21-winx64\my.ini
文件中添加 ONLY_FULL_GROUP_BY
更改配置信息以后，需要重新启动 mysql 服务器
方式二：在cmd终端
mysql> set global sql_mode='ONLY_FULL_GROUP_BY'; Query OK, 0 rows affected (0.00 sec) #查看MySQL 5.7默认的sql_mode如下： mysql> select @@global.sql_mode; +--------------------+ | @@global.sql_mode | +--------------------+ | ONLY_FULL_GROUP_BY | +--------------------+ 1 row in set (0.00 sec) mysql> exit;#设置成功后，一定要退出，然后重新登录方可生效 Bye
3、设置ONLY_FULL_GROUP_BY后，通过group by 分组之后，要想查看组内的信息，需要借助聚合函数，
也就是 select 之后只能是分组的字段，即group by 之后的字段，
此时 select * from ... 或查询其他字段都会报错
mysql> select * from emp group by post;# 报错 ERROR 1054 (42S22): Unknown column 'post' in 'group statement' mysql> select post from employee group by post; +-----------------------------------------+ | post | +-----------------------------------------+ | operation | | sale | | teacher | | 老男孩驻沙河办事处外交大使 | +-----------------------------------------+ rows in set (0.00 sec)
4、聚合函数
max()求最大值 min()求最小值 avg()求平均值 sum() 求和 count() 求总个数 一般直接写 count(1)就是计算总个数 #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 # 每个部门有多少个员工 select post,count(id) from employee group by post; # 每个部门的最高薪水 select post,max(salary) from employee group by post; # 每个部门的最低薪水 select post,min(salary) from employee group by post; # 每个部门的平均薪水 select post,avg(salary) from employee group by post; # 每个部门的所有薪水 select post,sum(age) from employee group by post;
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
总结：使用聚合函数一定要分组，但是select中可以使用聚合函数
select 1 from employee; 会在虚拟表中生成一个 1字段，值也都为1。
select count(1) from employee; 会在虚拟表中生成一个 count(1) 字段，然后计算1的个数。
having 过滤
过滤也称为二次筛选
HAVING与WHERE不一样的地方在于： #！！！执行优先级从高到低：where > group by > having
#1. Where 发生在分组group by之前，因而Where中可以有任意字段，但是绝对不能使用聚合函数。 #2. Having发生在分组group by之后，因而Having中只能是分组后的字段，无法直接取到其他字段,可以使用聚合函数
1、注意事项
select * from employee having salary > 100000;
解释：该语句现在是可以用的，之前的版本会报错，升级以后，不分组，则整体为一组，其中的字段都可以作为是分组的字段。
直接用having的时候，最好不要用 *
2、group_concat(字段名)
取分组后，非分组字段，也就是其他的字段
#需要用 group_concat(字段名)，取到其他的字段
select post,group_concat(name) from employee group by post having salary > 10000;
#报错，因为name不是分组的字段。
select post,name from employee group by post having salary > 10000;
3、小练习
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
2. 查询各岗位平均薪资大于10000的岗位名、平均工资
3. 查询各岗位平均薪资大于10000且小于20000的岗位名、平均工资
1. select post,group_concat(name),count(1) from employee group by post having count(1) < 2;
2. select post,avg(salary) from employee group by post having avg(salary)>10000; 3. select post,avg(salary) from employee group by post having avg(salary) between 10000 and 20000;
order by 查询排序
asc 升序， desc 降序
按单列排序 SELECT * FROM employee ORDER BY age; SELECT * FROM employee ORDER BY age ASC; SELECT * FROM employee ORDER BY age DESC;
按多列排序:先按照age升序排序，如果年纪相同，则按照id降序 SELECT * from employee ORDER BY age ASC, id DESC;
1、小练习
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
1. select * from employee order by age asc,hire_date desc; 2. select post,avg(salary) from employee group by post having avg(salary) > 10000 order by avg(salary); 3. select post,avg(salary) as A from employee group by post having A > 10000 order by A desc;
limit 限制查询的记录数
limit 可以用于分页展示数据
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
1、小练习
分页展示，每页5条
# 第1页数据 select * from employee limit 0,5; # 第2页数据 select * from employee limit 5,5; # 第3页数据 select * from employee limit 10,5;
多表查询
准备两种表，部门表(department)、员工表(employee)
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), ('nvshen','male',18,200), ('xiaomage','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 | | +-------+-------------+------+-----+---------+-------+ rows in set (0.19 sec) 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 | | +--------+-----------------------+------+-----+---------+----------------+ rows in set (0.01 sec) mysql> select * from department; +------+--------------+ | id | name | +------+--------------+ | 200 | 技术 | | 201 | 人力资源 | | 202 | 销售 | | 203 | 运营 | +------+--------------+ rows in set (0.02 sec) 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 | nvshen | male | 18 | 200 | | 6 | xiaomage | female | 18 | 204 | +----+----------+--------+------+--------+ rows in set (0.00 sec)
ps:观察两张表，发现department表中id=203部门在employee中没有对应的员工，发现employee中id=6的员工在department表中没有对应关系。
多表连接查询
两张表的准备工作已完成，比如现在我要查询的员工信息以及该员工所在的部门。从该题中，我们看出既要查员工又要查该员工的部门，肯定要将两张表进行连接查询，多表连接查询。
外链接语法：
SELECT 字段列表 FROM 表1 INNER|LEFT|RIGHT JOIN 表2 ON 表1.字段 = 表2.字段;
1、交叉链接，不适用任何的匹配条件，生成笛卡尔积
select * from employee,department;
..........................
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 select name from department where id not in (select dep_id from employee group by dep_id);
2、带 比较运算符 的子查询
#查询大于所有人平均年龄的员工名与年龄 select name,age from employee where age > (select avg(age) from employee);
#查询大于部门内平均年龄的员工名、年龄 思路： （1）先对员工表(employee)中的人员分组(group by)，查询出dep_id以及平均年龄。 (2)将查出的结果作为临时表,再对根据临时表的dep_id和employee的dep_id作为筛选条件将employee表和临时表进行内连接。 (3)最后再将employee员工的年龄是大于平均年龄的员工名字和年龄筛选。 select t1.name,t1.age from employee as t1
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 select * from employee where exists (select id from department where id=200);
#department表中存在dept_id=205，False select * from employee where exists (select id from department where id=204);
4、小练习
需求：查询每个部门最新入职的那位员工
表结构如下：
#创建表 create table employee( id int not null unique auto_increment, name varchar(20) not null, sex enum('male','female') not null default 'male', #大部分是男的 age int(3) unsigned not null default 28, hire_date date not null, post varchar(50), post_comment varchar(100), salary double(15,2), office int, #一个部门一个屋子 depart_id int ); #插入记录 #三个部门：教学，销售，运营 insert into employee(name,sex,age,hire_date,post,salary,office,depart_id) values ('egon','male',18,'20170301','老男孩驻沙河办事处外交大使',7300.33,401,1), #以下是教学部 ('alex','male',78,'20150302','teacher',1000000.31,401,1), ('wupeiqi','male',81,'20130305','teacher',8300,401,1), ('yuanhao','male',73,'20140701','teacher',3500,401,1), ('liwenzhou','male',28,'20121101','teacher',2100,401,1), ('jingliyang','female',18,'20110211','teacher',9000,401,1), ('jinxin','male',18,'19000301','teacher',30000,401,1), ('成龙','male',48,'20101111','teacher',10000,401,1), ('歪歪','female',48,'20150311','sale',3000.13,402,2),#以下是销售部门 ('丫丫','female',38,'20101101','sale',2000.35,402,2), ('丁丁','female',18,'20110312','sale',1000.37,402,2), ('星星','female',18,'20160513','sale',3000.29,402,2), ('格格','female',28,'20170127','sale',4000.33,402,2), ('张野','male',28,'20160311','operation',10000.13,403,3), #以下是运营部门 ('程咬金','male',18,'19970312','operation',20000,403,3), ('程咬银','female',18,'20130311','operation',19000,403,3), ('程咬铜','male',18,'20150411','operation',18000,403,3), ('程咬铁','female',18,'20140512','operation',17000,403,3) ;
# answer
select * from employee as t1 inner join (select post,max(hire_date) as new_date from employee group by post) as t2 on t1.post=t2.post where t1.hire_date=t2.new_date;
浙公网安备 33010602011771号