1.修改表名
alter table 表名 rename 新表名;
- 1
2.新增字段
alter table 表名 add 字段名 字段类型(数字) 约束条件: alter table 表名 add 字段名 字段类型(数字) 约束条件 after 已经存在的字段; alter table 表名 add 字段名 字段类型(数字) 约束条件 first;
- 1
- 2
- 3
3.修改字段
alter table 表名 change 旧字段 新字段 字段类型(数字) 约束条件; alter table 表名 modify 字段名 新的字段类型(数字) 约束条件;
- 1
- 2
4.删除字段
alter table 表名 drop 字段名;
- 1
5.实操展示
1.数据准备(直接拷贝)
create table emp( 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 ); #三个部门:教学,销售,运营 insert into emp(name,sex,age,hire_date,post,salary,office,depart_id) values ('jason','male',18,'20170301','浦东第一帅形象代言',7300.33,401,1), #以下是教学部 ('tom','male',78,'20150302','teacher',1000000.31,401,1), ('kevin','male',81,'20130305','teacher',8300,401,1), ('tony','male',73,'20140701','teacher',3500,401,1), ('owen','male',28,'20121101','teacher',2100,401,1), ('jack','female',18,'20110211','teacher',9000,401,1), ('jenny','male',18,'19000301','teacher',30000,401,1), ('sank','male',48,'20101111','teacher',10000,401,1), ('哈哈','female',48,'20150311','sale',3000.13,402,2),#以下是销售部门 ('呵呵','female',38,'20101101','sale',2000.35,402,2), ('西西','female',18,'20110312','sale',1000.37,402,2), ('乐乐','female',18,'20160513','sale',3000.29,402,2), ('拉拉','female',28,'20170127','sale',4000.33,402,2), ('僧龙','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);
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
- 11
- 12
- 13
- 14
- 15
- 16
- 17
- 18
- 19
- 20
- 21
- 22
- 23
- 24
- 25
- 26
- 27
- 28
- 29
- 30
- 31
- 32
2.查询关键字之select与from
select:自定义查询表中字段对应的数据
from:指定操作的对象(可能是多张表)
(1)SQL语句的关键字编写顺序与执行顺序是不一致的!!!eg: select name from emp; 肯定是先支持from确定表 之后执行select确定字段
- 1
- 2
(2)编写SQL语句针对select和from可以先写个固定模板
select * from 表名 其他操作 select后的字段可能是实际的 也可能是通过SQL动态产生的 所以可以先用*占位最后再修改
- 1
- 2
3.查询关键字之where筛选
敲个重点之模糊查询:查询条件不清晰,不明确的情况下,这种查询我们统称为模糊查询 关键字:like(开启模糊查询的关键字) 关键符号: '%':匹配任意个数的任意字符 '_':匹配单个个数的任意字符
- 1
- 2
- 3
- 4
- 5
(1)查询id大于等于3小于等于6的数据
select id,name from emp where id >=3 and id <=6; select * from emp where id between 3 and 6;
- 1
- 2
(2)查询薪资是20000或者18000或者17000的数据
select * from emp where salary = 20000 or salary = 18000 or salary = 17000; select * from emp where salary in (20000,18000,17000); # 简写
- 1
- 2
(3)查询员工姓名中包含o字母的员工姓名和薪资
补充之查询步骤: 如果是刚接触mysql查询,建议按照查询的优先级顺序拼写出你的sql语句 步骤一:先是查那张表 from emp 步骤二:再是根据什么条件去查 where name like '%o%' 步骤三:再是对查询出来的数据筛选展示部分 select name,salary
- 1
- 2
- 3
- 4
- 5
select name,salary from emp where name like '%o%';
- 1
(4)查询员工姓名是由四个字符组成的员工姓名与其薪资
select name,salary from emp where name like '____'; select name,salary from emp where char_length(name) = 4;
- 1
- 2
(5)查询id小于3或者大于6的数据
select * from emp where id not between 3 and 6;
- 1
(6)查询薪资不在20000,18000,17000范围的数据
select * from emp where salary not in (20000,18000,17000);
- 1
(7)查询岗位描述为空的员工名与岗位名,针对null不能用符号,只能用is
select name,post from emp where post_comment = NULL; # 查询为空 select name,post from emp where post_comment is NULL; select name,post from emp where post_comment is not NULL;
- 1
- 2
- 3
3.查询关键字之group by分组
(1)分组:按照一些指定的条件将单个单个的数据分为一个个整体分组之后我们研究的对象应该是以组为单位,不应该在直接获取单个数据项; 如果获取了应该直接报错,select后面可以直接填写的字段名只能是分组的依据(其他字段需要借助于一些方法才可以获取).
- 1
- 2
my.ini配置修改: set global sql_mode = 'strict_trans_tables,only_full_group_by';
- 1
- 2
select post(字段名) from emp(表名) group by post(以什么字段分组);
- 1
(2)
配合分组常见使用的有聚合函数:
max 最大值
min 最小值
sum 总和
count 计数
avg 平均(3)举个栗子:获取每个部门的最高工资
以组为单位统计组内数据>>>聚合查询(聚集到一起合成为一个结果)
每个部门的最高工资:select post,max(salary) from emp group by post; 补充:在显示的时候还可以给字段取别名 select post as '部门',max(salary) as '最高工资' from emp group by post; as 也可以省略,但是不推荐省,因为寓意不明确
- 1
- 2
- 3
- 4
- 5
- 6
每个部门的最低工资:select post,min(salary) from emp group by post;
- 1
每个部门的平均工资
select post,avg(salary) from emp group by post;
- 1
每个部门的工资总和
select post,sum(salary) from emp group by post;
- 1
每个部门的人数
select post,count(id) from emp group by post;
- 1
查询分组之后的部门名称和每个部门下所有的学生姓名
group_concat(分组之后用)不仅可以用来显示除分组外字段还有拼接字符串的作用select post,group_concat(name) from emp group by post; select post,group_concat(name,"_SB") from emp group by post; select post,group_concat(name,": ",salary) from emp group by post; select post,group_concat(salary) from emp group by post;
- 1
- 2
- 3
- 4
- 5
- 6
- 7
4.查询关键字之having过滤
where与having的功能其实是一样的 都是用来筛选数据
只不过where用于分组之前的筛选 而having用于分组之后的筛选
为了人为的区分 所以叫where是筛选 having是过滤
(1)统计各部门年龄在30岁以上的员工平均工资,并且保留平均工资大于10000的部门select post,avg(salary) from emp where age >= 30 group by post having avg(salary) > 10000; +---------+---------------+ | post | avg(salary) | +---------+---------------+ | teacher | 255450.077500 | +---------+---------------+ 1 row in set (0.10 sec)
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
- 11
- 12
5.查询关键字之distinct去重
去重的前提是数据必须一模一样!!!select distinct age from emp; +-----+ | age | +-----+ | 18 | | 78 | | 81 | | 73 | | 28 | | 48 | | 38 | +-----+ 7 rows in set (0.00 sec)
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
- 11
- 12
- 13
- 14
- 15
6.查询关键字之order by排序
select * from emp order by salary asc; #默认升序排 select * from emp order by salary desc; #降序排 select * from emp order by age desc; #降序排 #先按照age降序排,在年轻相同的情况下再按照薪资升序排 select * from emp order by age desc,salary asc; # 统计各部门年龄在10岁以上的员工平均工资,并且保留平均工资大于1000的部门,然后对平均工资进行排序 select post,avg(salary) from emp where age > 10 group by post having avg(salary) > 1000 order by avg(salary) ; +-----------------------------+---------------+ | post | avg(salary) | +-----------------------------+---------------+ | sale | 2600.294000 | | 浦东第一帅形象代言 | 7300.330000 | | operation | 16800.026000 | | teacher | 151842.901429 | +-----------------------------+---------------+ 4 rows in set (0.00 sec)
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
- 11
- 12
- 13
- 14
- 15
- 16
- 17
- 18
- 19
- 20
- 21
- 22
- 23
- 24
- 25
- 26
7.查询关键字之limit分页
# 限制展示条数 select * from emp limit 3; # 查询工资最高的人的详细信息 select * from emp order by salary desc limit 1;
- 1
- 2
- 3
- 4
# 分页显示 select * from emp limit 0,5; # 第一个参数表示起始位置,第二个参数表示的是条数,不是索引位置 select * from emp limit 5,5;
- 1
- 2
- 3
8.查询关键字之regexp正则
select * from emp where name regexp '^j.*(n|y)$';
- 1
1.前戏
- 子查询
将一张表的查询结果括号括起来当做另外一条SQL语句的条件
eg:类似以日常生活中解决问题的方式
第一步干什么
第二步基于第一步的结果在做操作 …- 连表操作
先将所有涉及到结果的表全部拼接到一起形成一张大表 然后从大表中查询数据
建表:create table dep1( id int primary key auto_increment, name varchar(20) ); create table emp1( id int primary key auto_increment, name varchar(20), gender enum('male','female') not null default 'male', age int, dep_id int ); #插入数据 insert into dep1 values (200,'技术'), (201,'人力资源'), (202,'销售'), (203,'运营'), (205,'安保') ; insert into emp1(name,gender,age,dep_id) values ('jason','male',18,200), ('dragon','female',48,201), ('kevin','male',18,201), ('nick','male',28,202), ('owen','male',18,203), ('jerry','female',18,204);
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
- 11
- 12
- 13
- 14
- 15
- 16
- 17
- 18
- 19
- 20
- 21
- 22
- 23
- 24
- 25
- 26
- 27
- 28
- 29
2.子查询
查询jason的部门名称
分布方法:
第一步:先获取jason的部门编号select dep_id from emp1 where name = 'jason'; # 200
- 1
第二步:根据部门编号获取部门名称
select name from dep1 where id = 200;
- 1
变成子查询后:select name from dep1 where id = (select dep_id from emp1 where name = 'jason'); +--------+ | name | +--------+ | 技术 | +--------+ 1 row in set (0.00 sec)
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
3.连表操作
(1)select * from emp1,dep1; # 笛卡尔积
‘’‘我们不会使用笛卡尔积来求数据 效率太低 连表有专门的语法’‘’
(2)如何避免笛卡尔现象:
推导一:连接时加条件,满足这个条件的记录才会被筛选出来
但是我们可以发现,两张表结合在一起之后,都少东西了,因为有数据没有关联起来。select * from emp1,dep1 where dep1.id = emp1.dep_id;
- 1
推导二:建立连接inner join 内连接 只拼接两边都有的字段数据 left join 左连接 以左表为基准 展示所有的数据 没有对应则NULL填充 select * from emp1 left join dep1 on emp1.dep_id = dep1.id; right join 右连接 以右表为基准 展示所有的数据 没有对应则NULL填充 select * from emp1 right join dep1 on emp1.dep_id = dep1.id; union 全连接
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
- 11
- 12
mysql> select post,group_concat(name) from emp group by post;
+-----------------------------+------------------------------------------------+
| post | group_concat(name) |
+-----------------------------+------------------------------------------------+
| operation | 程咬铁,程咬铜,程咬银,程咬金,僧龙 |
| sale | 拉拉,乐乐,西西,呵呵,哈哈 |
| teacher | sank,jenny,jack,owen,tony,kevin,tom |
| 浦东第一帅形象代言 | jason |
+-----------------------------+------------------------------------------------+
4 rows in set (0.00 sec)
2.查询岗位名以及各岗位内包含的员工个数
mysql> select post, count(id) from emp group by post;
+-----------------------------+-----------+
| post | count(id) |
+-----------------------------+-----------+
| operation | 5 |
| sale | 5 |
| teacher | 7 |
| 浦东第一帅形象代言 | 1 |
+-----------------------------+-----------+
4 rows in set (0.00 sec)
3.查询公司内男员工和女员工的个数
mysql> select sex,count(id) from emp group by sex;
+--------+-----------+
| sex | count(id) |
+--------+-----------+
| male | 10 |
| female | 8 |
+--------+-----------+
2 rows in set (0.00 sec)
4.查询岗位名以及各岗位的平均薪资
mysql> select post,avg(salary) from emp group by post;
+-----------------------------+---------------+
| post | avg(salary) |
+-----------------------------+---------------+
| operation | 16800.026000 |
| sale | 2600.294000 |
| teacher | 151842.901429 |
| 浦东第一帅形象代言 | 7300.330000 |
+-----------------------------+---------------+
4 rows in set (0.00 sec)
5.查询岗位名以及各岗位的最高薪资
mysql> select post, max(salary) from emp group by post;
+-----------------------------+-------------+
| post | max(salary) |
+-----------------------------+-------------+
| operation | 20000.00 |
| sale | 4000.33 |
| teacher | 1000000.31 |
| 浦东第一帅形象代言 | 7300.33 |
+-----------------------------+-------------+
4 rows in set (0.00 sec)
6.查询岗位名以及各岗位的最低薪资
mysql> select post,min(salary) from emp group by post;
+-----------------------------+-------------+
| post | min(salary) |
+-----------------------------+-------------+
| operation | 10000.13 |
| sale | 1000.37 |
| teacher | 2100.00 |
| 浦东第一帅形象代言 | 7300.33 |
+-----------------------------+-------------+
4 rows in set (0.00 sec)
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
mysql> select sex,avg(salary) from emp group by sex;
+--------+---------------+
| sex | avg(salary) |
+--------+---------------+
| male | 110920.077000 |
| female | 7250.183750 |
+--------+---------------+
2 rows in set (0.00 sec)
8.统计各部门年龄在30岁以上的员工平均工资
mysql> select post, avg(salary) from emp where age > 30 group by post;
+---------+---------------+
| post | avg(salary) |
+---------+---------------+
| sale | 2500.240000 |
| teacher | 255450.077500 |
+---------+---------------+
2 rows in set (0.00 sec)
mysql> select post, avg(salary) from emp where age > 10 group by post having avg(salary) > 1000 order by avg(salary) desc;
+-----------------------------+---------------+
| post | avg(salary) |
+-----------------------------+---------------+
| teacher | 151842.901429 |
| operation | 16800.026000 |
| 浦东第一帅形象代言 | 7300.330000 |
| sale | 2600.294000 |
+-----------------------------+---------------+
4 rows in set (0.00 sec)