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oracle的分析函数over 及开窗函数
一:分析函数over
Oracle从8.1.6开始提供分析函数,分析函数用于计算基于组的某种聚合值,它和聚合函数的不同之处是
对于每个组返回多行,而聚合函数对于每个组只返回一行。 
下面通过几个例子来说明其应用。                                       
1:统计某商店的营业额。        
     date       sale
     1           20
     2           15
     3           14
     4           18
     5           30
    规则:按天统计:每天都统计前面几天的总额
    得到的结果:
    DATE   SALE       SUM
    ----- -------- ------
    1      20        20           --1天           
    2      15        35           --1天+2天           
    3      14        49           --1天+2天+3天           
    4      18        67            .          
    5      30        97            .
     
2:统计各班成绩第一名的同学信息
    NAME   CLASS S                         
    ----- ----- ---------------------- 
    fda    1      80                     
    ffd    1      78                     
    dss    1      95                     
    cfe    2      74                     
    gds    2      92                     
    gf     3      99                     
    ddd    3      99                     
    adf    3      45                     
    asdf   3      55                     
    3dd    3      78              
   
    通过:   
    --
    select * from                                                                       
    (                                                                            
    select name,class,s,rank()over(partition by class order by s desc) mm from t2
    )                                                                            
    where mm=1 
    --
    得到结果:
    NAME   CLASS S                       MM                                                                                        
    ----- ----- ---------------------- ---------------------- 
    dss    1      95                      1                      
    gds    2      92                      1                      
    gf     3      99                      1                      
    ddd    3      99                      1          
   
    注意:
    1.在求第一名成绩的时候,不能用row_number(),因为如果同班有两个并列第一,row_number()只返回一个结果          
    2.rank()和dense_rank()的区别是:
      --rank()是跳跃排序,有两个第二名时接下来就是第四名
      --dense_rank()l是连续排序,有两个第二名时仍然跟着第三名
     
     
3.分类统计 (并显示信息)
    A   B   C                      
    -- -- ---------------------- 
    m   a   2                      
    n   a   3                      
    m   a   2                      
    n   b   2                      
    n   b   1                      
    x   b   3                      
    x   b   2                      
    x   b   4                      
    h   b   3
   select a,c,sum(c)over(partition by a) from t2                
   得到结果:
   A   B   C        SUM(C)OVER(PARTITIONBYA)      
   -- -- ------- ------------------------ 
   h   b   3        3                        
   m   a   2        4                        
   m   a   2        4                        
   n   a   3        6                        
   n   b   2        6                        
   n   b   1        6                        
   x   b   3        9                        
   x   b   2        9                        
   x   b   4        9                        
  
   如果用sum,group by 则只能得到
   A   SUM(C)                            
   -- ---------------------- 
   h   3                      
   m   4                      
   n   6                      
   x   9                      
   无法得到B列值       
  
=====

select * from test

数据:
A B C 
1 1 1 
1 2 2 
1 3 3 
2 2 5 
3 4 6 


---将B栏位值相同的对应的C 栏位值加总
select a,b,c, SUM(C) OVER (PARTITION BY B) C_Sum
from test

A B C C_SUM 
1 1 1 1 
1 2 2 7 
2 2 5 7 
1 3 3 3 
3 4 6 6 



---如果不需要已某个栏位的值分割,那就要用 null

eg: 就是将C的栏位值summary 放在每行后面

select a,b,c, SUM(C) OVER (PARTITION BY null) C_Sum
from test

A B C C_SUM 
1 1 1 17 
1 2 2 17 
1 3 3 17 
2 2 5 17 
3 4 6 17

 

求个人工资占部门工资的百分比

SQL> select * from salary;

NAME DEPT SAL
---------- ---- -----
a 10 2000
b 10 3000
c 10 5000
d 20 4000

SQL> select name,dept,sal,sal*100/sum(sal) over(partition by dept) percent from salary;

NAME DEPT SAL PERCENT
---------- ---- ----- ----------
a 10 2000 20
b 10 3000 30
c 10 5000 50
d 20 4000 100

二:开窗函数           
      开窗函数指定了分析函数工作的数据窗口大小,这个数据窗口大小可能会随着行的变化而变化,举例如下: 
1:     
   over(order by salary) 按照salary排序进行累计,order by是个默认的开窗函数
   over(partition by deptno)按照部门分区
2:
  over(order by salary range between 5 preceding and 5 following)
   每行对应的数据窗口是之前行幅度值不超过5,之后行幅度值不超过5
   例如:对于以下列
     aa
     1
     2
     2
     2
     3
     4
     5
     6
     7
     9
   
   sum(aa)over(order by aa range between 2 preceding and 2 following)
   得出的结果是
            AA                       SUM
            ---------------------- ------------------------------------------------------- 
            1                       10                                                      
            2                       14                                                      
            2                       14                                                      
            2                       14                                                      
            3                       18                                                      
            4                       18                                                      
            5                       22                                                      
            6                       18                                                                
            7                       22                                                                
            9                       9                                                                 
             
   就是说,对于aa=5的一行 ,sum为   5-1<=aa<=5+2 的和
   对于aa=2来说 ,sum=1+2+2+2+3+4=14     ;
   又如 对于aa=9 ,9-1<=aa<=9+2 只有9一个数,所以sum=9    ;
              
3:其它:
     over(order by salary rows between 2 preceding and 4 following)
          每行对应的数据窗口是之前2行,之后4行 
4:下面三条语句等效:           
     over(order by salary rows between unbounded preceding and unbounded following)
          每行对应的数据窗口是从第一行到最后一行,等效:
     over(order by salary range between unbounded preceding and unbounded following)
           等效
     over(partition by null)
posted on 2011-12-01 10:00 紫蝶∏飛揚↗ 阅读(1248) 评论(0)  编辑  收藏 所属分类: 数据库

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