介绍：
MSQL8.0新增窗口函数商口函数又被称为开窗函数，与Oracle窗口函数类似，属于MysaL的一大特点
非聚合窗口函数是相对于聚函数来说的。聚合函数是对一组数据计算后返回单个值(即分组)，非聚合函数一次只会处理一行数据。窗口聚合函数在行记录上计算某个字段的结果时，可将窗口范围内的数据输入到聚合函数中，并不改变行数。
语法结构：
window_function ( expr ) OVER(
PARTITION BY ...
ORDER BY ...
frame_clause
)
其中，window_function是窗口函数的名称;expr是参数，有些函数不需要参数;oVER子句包含三个选项:
分区(PARTITION BY)
PARTITION BY选项用于将数据行拆分成多个分区(组)，它的作用类似于GROUP BY分组。如果省略了PARTITION BY，所有的数据作为一个组进行计算
排序(ORDER BY)
OVER子句中的ORDER BY选项用于指定分区内的排序方式，与ORDER BY子句的作用类似以及
窗口大小(frame_clause)
frame_clause选项用于在当前分区内指定一个计算窗口，也就是一个与当前行相关的数据子集
1，序号函数
序号函数有三个: kow_NUMBER()、RANK()、DENSE_RANK()，可以用来实现分组排序，并添加序号。
格式：
row_number ( ) | rank ( ) | dense_rank () over (
partition by ...
order by ...
)
不加 partition by表示全局排序
--按每个部门的员工按薪资，并排名
select
dname,
ename,
salary,
row_number() over (partition by dname order by salary desc) as rn
from employee;
select
dname,
ename,
salary,
rank() over (partition by dname order by salary desc) as rn
from employee;
--按每个部门的员工按薪资前3名，并排名
select * FROM(
select
dname,
ename,
salary,
rank() over (partition by dname order by salary desc) as rn
from employee) as t
where t.rn<=3;2，开窗聚合函数
在窗口中每条记录动态地应用聚合函数（SUM()、AVG()、MAX()、MIN()、COUNT())，可以动态计算在推窗口内的各种聚合函数值。
如果没有order by排序语句默认把分组内的所有数据进行sum操作
select
dname,
ename,
hiredate,
salary,
sum(salary) over (partition by dname order by hiredate) as pv1
from employee;
select
dname,
ename,
hiredate,
salary,
sum(salary) over (partition by dname order by hiredate rows between unbounded preceding and current row) as pv1
from employee;--和上面的结果相同
select
dname,
ename,
hiredate,
salary,
sum(salary) over (partition by dname order by hiredate rows between 3 unbounded preceding and current row) as pv1
from employee;--从该行向上3行相加
select
dname,
ename,
hiredate,
salary,
sum(salary) over (partition by dname order by hiredate rows between 3 unbounded preceding and 1 current row) as pv1
from employee;--从该行向上3行以及向后1行（包括本行）相加3，分布函数
（1）CUME_DIST
用途:分组内小于、等于当前rank值的行数/分组内总行数
应用场景:查询小于等于当前薪资(salary）的比例
select
dname,
ename,
salary,
cume_dist() over ( order by salary desc) as rn ,
cume_dist() over (partition by dname order by salary ) as rn
from employee;
列如3000
不分组的话，数据中小于等于3000的有12个
故为3/12=0.25
（2）PERCENT_RANK
用途:每行按照公式(rank-1) /(rows-1)进行计算。其中，rank为RANK()函数产生的序号，rows为当前窗口的记录总行数
应用场景:不常用
select
dname,
ename,
salary,
rank() over (partition by dname order by salary desc) as rn1 ,
percent_rank() over (partition by dname order by salary ) as rn2
from employee;
第一行：(1-1)/(6-1)=0
第二行：(1-1)/(6-1)=0
第三行：(3-1)/(6-1)=0.44，前后函数-LAG和LEAD
介绍：
用途:返回位于当前行的前n行（LAG(expr,n)）或后n行（LEAD(expr,n)）的expr的值
应用场景:查询前1名同学的成绩和当前同学成绩的差值
select
dname,
ename,
hiredate,
salary,
lag(hiredate,1,'2000-01-01') over(partition by dname order by hiredate) as rn1 ,
lag(hiredate,2) over (partition by dname order by hiredate ) as rn2
from employee;
select
dname,
ename,
hiredate,
salary,
lead(hiredate,1,'2000-01-01') over(partition by dname order by hiredate) as rn1 ,
lead(hiredate,2) over (partition by dname order by hiredate ) as rn2
from employee;
5，头尾函数-FIRST_VALUE和LAST_VALUE
用途:返回第一个(FIRST_VALUE(expr))或最后一个(LAST_VALUE(expr)) expr的值
应用场景:截止到当前，按照日期排序查询第1个入职和最后1个入职员工的薪资
select
dname,
ename,
hiredate,
salary,
first_value(salary) over(partition by dname order by hiredate) as rn1 ,
last_value(salary) over (partition by dname order by hiredate ) as rn2
from employee;6，其他函数-NTH_VALUE(expr,n)、NTILE(n)
（1）NTH_VALUE(expr,n)
用途:返回窗口中第n个expr的值。expr可以是表达式，也可以是列名
应用场景:截止到当前薪资，显示每个员工的薪资中排名第2或者第3的薪资
select
dname,
ename,
hiredate,
salary,
nth_value(salary,2) over(partition by dname order by hiredate) as second_salary ,
nth_value(salary,3) over (partition by dname order by hiredate ) as third_salary
from employee;（2）NTILE(n)
用途:将分区中的有序数据分为n个等级，记录等级数
应用场景:将每个部门员工按照入职日期分成3组
select
dname,
ename,
hiredate,
salary,
ntile(3) over(partition by dname order by hiredate) as rn1
from employee;
--每个部门的第一组
select* from (
select
dname,
ename,
hiredate,
salary,
ntile(3) over(partition by dname order by hiredate) as rn1
from employee) as t
where t.rn1=1;
