高级查询 cume_dist()和percent_rank()

 

cume_dist()和percent_rank()这两个函数了，现在把他们的区别在这用个例子说明一下

SQL> create table cume (
  2  id integer,
  3  value number(8,2),
  4  name varchar2(30));

Table created.

SQL>
SQL> select  * from cume;

        ID      VALUE NAME
---------- ---------- ------------------------------------------------------------
         1        123 t1
         2        234 t2
         2        234 t21
         3        345 t3
         4        456 t4
         5        567 t5
         6        567 t6

7 rows selected.

SQL>
SQL> select id, value, cume_dist() over (order by value desc) as cume_dist, percent_rank() over (order by value desc) as percent_rank from cume;

        ID      VALUE  CUME_DIST PERCENT_RANK
---------- ---------- ---------- ------------
         5        567 .285714286            0
         6        567 .285714286            0
         4        456 .428571429   .333333333
         3        345 .571428571           .5
         2        234 .857142857   .666666667
         2        234 .857142857   .666666667
         1        123          1            1

7 rows selected.
数字看着不是很整齐，我们处理下
SQL> delete from cume where id = 2;

2 rows deleted.

SQL> select id, value, cume_dist() over (order by value desc) as cume_dist, percent_rank() over (order by value desc) as percent_rank from cume;

        ID      VALUE  CUME_DIST PERCENT_RANK
---------- ---------- ---------- ------------
         5        567         .4            0
         6        567         .4            0
         4        456         .6           .5
         3        345         .8          .75
         1        123          1            1

SQL>
从上面的例子我们可以看出cume_dist()函数统计的范围是0< cume_dist() <=1，但是取不到0。percent_rank()也是0<= percent_rank() <=1，0和1都可以取道的。
cume_disk()的计算公式应该是 = ((统计的列的种类)/(统计的列的总数))*每个重复种类中的个数；如value值为567的两个值，公式就是(4/5)*2=0.4。而最大就是1了
percetn_rank()的计算公式应该是 = ((统计的列的种类)/(统计的列的总数))*100%，但是第一个总是从0开始的，不管是重复几次，要是567有4次，那就是有四个都是0，最后一个是1。