Python之旅.第十章.mysql.

单表查询

一、语法顺序

select distinct 查询字段1,查询字段2,。。。 from 表名

    where 分组之前的过滤条件

    group by 分组依据

    having 分组之后的过滤条件

    order by 排序字段

    limit 显示的条数;

 

二、执行顺序

def from(dir,file):

    open('%s\%s' %(dir,file),'r')

    return f

 

def where(f,pattern):

    for line in f:

        if pattern

            yield line

 

def group_by():

    pass

 

def having():

    pass

 

def distinct():

    pass

 

def order_by():

    pass

 

def limit():

    pass

 

def select():

    res1=from()   #在硬盘中找到表

    res2=where(res1,pattern)  #拿着where指定的约束条件,去文件/表中取出一条条记录,在内存中得到一张虚拟的表, 如果没有where,默认全True

    res3=group_by(res2,)  #将取出的一条条记录进行分组group by,如果没有group by,默认整体作为一组

    res4=having(res3)   #将分组的结果进行having过滤,如果没有having,默认全True

    res5=distinct(res4)  #去重, 如果没有distinct,默认不去重

    res6=order_by(res5)  #将结果按条件排序

    limit(res6)    #限制结果的显示条数

 

三、按照优先级的级别写SQL语句

a、先确定是哪张表 from db39.emp

b、是否有过滤条件 where name like '%i%'

。。。

z、放功能 select

 

四、where过滤

where字句中可以使用:

1. 比较运算符:> < >= <= <> !=  #不等于用 = 不用 <>

   select id,name from db39.emp where id >= 3 and id <= 6

 

2. between 80 and 100

   select *  from db39.emp where id between 3 and 6;  # >=3 and <=6

 

3. in(80,90,100) 值是8090100

   select * from emp where salary in (20000,18000,17000); # select * from emp where salary = 20000 or salary = 18000 or salary = 17000;

 

4. like 'egon%', pattern可以是%_, %表示任意多字符, _表示一个字符

   select name,salary from db39.emp where name like '%i%'  #要求:查询员工姓名中包含i字母的员工姓名与其薪资

   select name,salary from db39.emp where name like '____';  #要求:查询员工姓名是由四个字符组成的的员工姓名与其薪资

   select name,salary from db39.emp where char_length(name) = 4;   #结果与上一条一致

 

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

   select *  from db39.emp where id not between 3 and 6;

   select * from emp where salary not in (20000,18000,17000);

 

   要求:查询岗位描述为空的员工名与岗位名

   select name,post from db39.emp where post_comment is NULL;  #针对NULL必须用is,不能用=

   select name,post from db39.emp where post_comment is not NULL;

   #NULL指的是不占任何存储空间,在mysql中空字符串也是占存储空间的,即不为空(NULL

 

五、group by分组

    如果不设置成only_full_group_by模式,分完组后用*默认取出的是组内的第一个人的数据。但分完组后单独取组内的某个元素是没有意义的,所以,分组前,一般会对模式做如下处理

    #设置sql_modeonly_full_group_by,意味着以后但凡分组,只能取到分组的依据

    mysql> set global sql_mode="strict_trans_tables,only_full_group_by";

 

    #聚合函数 group function(一般与分组连用)

    select post,max(salary) from emp group by post; #取不出组内的元素name, age..,只能取组名(分组依据)或用聚合函数

 

    select post,min(salary) from emp group by post;

 

    select post,avg(salary) from emp group by post;

 

    select post,sum(salary) from emp group by post;

 

    select post,count(id) from emp group by post;

 

    #group_concat(分组之后用):把想要用的信息取出;字符串拼接操作

    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;

 

    # 补充concat(不分组时用):字符串拼接操作

    select concat("NAME: ",name) as 姓名,concat("SAL: ",salary) as 薪资 from emp;

 

    # 补充as语法:为字段或表取别名

    select name as 姓名,salary as 薪资 from emp;  # as可省略

    mysql> select emp.id,emp.name from emp as t1; # 报错

    mysql> select t1.id,t1.name from emp as t1;  # mysql> select id,name from emp as t1;

 

    # 查询四则运算

    select name,salary*12 as annual_salary from emp;

 

    #分组练习

    select post,group_concat(name) from emp group by post;  #查询岗位名以及岗位包含的所有员工名字

 

    select post,count(id) from emp group by post; #查询岗位名以及各岗位内包含的员工个数

 

    select sex,count(id) from emp group by sex;  #查询公司内男员工和女员工的个数

 

    select post,avg(salary) from emp group by post;  #查询岗位名以及各岗位的平均薪资

 

    select sex,avg(salary) from emp group by sex;  #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,avg(salary) from emp where age >= 30 group by post; #统计各部门年龄在30岁以上的员工平均工资

 

六、having过滤 (一定要用组名(分组依据)或聚合函数)

    having的语法格式与where一模一样,只不过having是在分组之后进行的进一步过滤

    where不能用聚合函数,而having是可以用聚合函数,这也是他们俩最大的区别

 

    #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;

 

    #强调:having必须在group by后面使用 (不认默认分组)

    select * from emp having avg(salary) > 10000; #报错

 

七、distinct去重 (在having之后执行,和postname等属于同一执行级别)

select distinct post,avg(salary) from emp where age >= 30 group by post having avg(salary) > 10000;

 

八、order by 排序 (默认升序)

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

select * from emp order by age desc,salary asc; #先按照age降序排,再按照薪资升序排

 

# 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);

 

九、limit 限制显示条数;分页

select * from emp limit 3;

select * from emp order by salary desc limit 1;  #显示薪资最高人的信息

select * from emp limit 0,5; #分页, 0开始,取5条(1-5

select * from emp limit 5,5; #分页, 5开始,取5条(6-10

 

十、正则表达式

select * from emp where name regexp '^jin.*(n|g)$';  #调正则;正则表达式通用

 

多表连接查询

一、笛卡尔积

   from emp,dep,dep2,...

  

二、内连接:把两张表有对应关系的记录连接成一张虚拟表

select * from emp inner join dep on emp.dep_id = dep.id;

 

#应用:

    select * from emp,dep where emp.dep_id = dep.id and dep.name = "技术"; # 不推荐;不要用where做连表的活

    select * from emp inner join dep on emp.dep_id = dep.id where dep.name = "技术";   #逻辑与上一条一致

 

三、左连接:在内连接的基础上,保留左边没有对应关系的记录

select * from emp left join dep on emp.dep_id = dep.id;

 

四、右连接:在内连接的基础上,保留右边没有对应关系的记录

select * from emp right join dep on emp.dep_id = dep.id;

 

五、全连接:在内连接的基础上,保留左、右边没有对应关系的记录

select * from emp left join dep on emp.dep_id = dep.id

union   #去重

select * from emp right join dep on emp.dep_id = dep.id;

 

六、多表连接可以是单表不断地与虚拟表连接

#查找各部门最高工资

select t1.* from emp as t1

inner join

(select post,max(salary) as ms from emp group by post) as t2  #把虚拟表提成t2

on t1.post = t2.post

where t1.salary = t2.ms

;

 

select t1.* from emp as t1

inner join

(select post,max(salary) as ms from emp group by post) as t2

on t1.salary = t2.ms

;

posted @ 2018-05-10 23:41  yangli0504  阅读(139)  评论(0编辑  收藏  举报