问题描述

RANK() 和 DENSE_RANK() 函数有什么区别?如何在下面的emptbl表中找出第n个薪水?

What's the difference between RANK() and DENSE_RANK() functions? How to find out nth salary in the following emptbl table?

DEPTNO  EMPNAME    SAL
------------------------------
10       rrr    10000.00
11       nnn    20000.00
11       mmm    5000.00
12       kkk    30000.00
10       fff    40000.00
10       ddd    40000.00
10       bbb    50000.00
10       ccc    50000.00

如果表数据中有nulls，如果我想找出nth的salary怎么办?

If in the table data having nulls, what will happen if I want to find out nth salary?

推荐答案

RANK 为您提供有序分区内的排名.平局被分配相同的排名，跳过下一个排名.因此，如果您有 3 个项目处于第 2 位，则列出的下一个排名将是第 5 位.

RANK gives you the ranking within your ordered partition. Ties are assigned the same rank, with the next ranking(s) skipped. So, if you have 3 items at rank 2, the next rank listed would be ranked 5.

DENSE_RANK 再次为您提供有序分区内的排名，但排名是连续的.如果有多个项目的等级，则不跳过等级.

DENSE_RANK again gives you the ranking within your ordered partition, but the ranks are consecutive. No ranks are skipped if there are ranks with multiple items.

至于空值，它取决于 ORDER BY 子句.这是一个简单的测试脚本，您可以使用它来查看会发生什么:

As for nulls, it depends on the ORDER BY clause. Here is a simple test script you can play with to see what happens:

with q as (
select 10 deptno, 'rrr' empname, 10000.00 sal from dual union all
select 11, 'nnn', 20000.00 from dual union all
select 11, 'mmm', 5000.00 from dual union all
select 12, 'kkk', 30000 from dual union all
select 10, 'fff', 40000 from dual union all
select 10, 'ddd', 40000 from dual union all
select 10, 'bbb', 50000 from dual union all
select 10, 'xxx', null from dual union all
select 10, 'ccc', 50000 from dual)
select empname, deptno, sal
     , rank() over (partition by deptno order by sal nulls first) r
     , dense_rank() over (partition by deptno order by sal nulls first) dr1
     , dense_rank() over (partition by deptno order by sal nulls last) dr2
 from q; 

EMP     DEPTNO        SAL          R        DR1        DR2
--- ---------- ---------- ---------- ---------- ----------
xxx         10                     1          1          4
rrr         10      10000          2          2          1
fff         10      40000          3          3          2
ddd         10      40000          3          3          2
ccc         10      50000          5          4          3
bbb         10      50000          5          4          3
mmm         11       5000          1          1          1
nnn         11      20000          2          2          2
kkk         12      30000          1          1          1

9 rows selected.

这是一个链接 一个很好的解释和一些例子.

Here's a link to a good explanation and some examples.

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