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What's the difference between RANK() and DENSE_RANK() functions in oracle?

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

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


A
AlSub

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() 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.

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.

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


very good idea to use select union all from dual to generate sample data without creating any table
@Jean-ChristopheBlanchard although you could just as easily use a values clause.
@Wildcard In PG, yes. In Oracle, no. At least not as of 11. I haven't run into 12 in prod yet.
Remove from dual for generating this data in Redshift
Ivan, RANK gives me an idea where I am relative to all those ahead of me. DENSE_RANK tells me the absolute rank. I may have the second highest salary, but there could be 100 people ahead of me. Which one is better depends on the question I'm answering.
L
Lukas Eder

This article here nicely explains it. Essentially, you can look at it as such:

CREATE TABLE t AS
SELECT 'a' v FROM dual UNION ALL
SELECT 'a'   FROM dual UNION ALL
SELECT 'a'   FROM dual UNION ALL
SELECT 'b'   FROM dual UNION ALL
SELECT 'c'   FROM dual UNION ALL
SELECT 'c'   FROM dual UNION ALL
SELECT 'd'   FROM dual UNION ALL
SELECT 'e'   FROM dual;

SELECT
  v,
  ROW_NUMBER() OVER (ORDER BY v) row_number,
  RANK()       OVER (ORDER BY v) rank,
  DENSE_RANK() OVER (ORDER BY v) dense_rank
FROM t
ORDER BY v;

The above will yield:

+---+------------+------+------------+
| V | ROW_NUMBER | RANK | DENSE_RANK |
+---+------------+------+------------+
| a |          1 |    1 |          1 |
| a |          2 |    1 |          1 |
| a |          3 |    1 |          1 |
| b |          4 |    4 |          2 |
| c |          5 |    5 |          3 |
| c |          6 |    5 |          3 |
| d |          7 |    7 |          4 |
| e |          8 |    8 |          5 |
+---+------------+------+------------+

In words

ROW_NUMBER() attributes a unique value to each row

RANK() attributes the same row number to the same value, leaving "holes"

DENSE_RANK() attributes the same row number to the same value, leaving no "holes"


Error :SQL Error: ORA-00923: FROM keyword not found where expected
S
Shine

rank() : It is used to rank a record within a group of rows.

dense_rank() : The DENSE_RANK function acts like the RANK function except that it assigns consecutive ranks.

Query -

select 
    ENAME,SAL,RANK() over (order by SAL) RANK
from 
    EMP;

Output -

+--------+------+------+
| ENAME  | SAL  | RANK |
+--------+------+------+
| SMITH  |  800 |    1 |
| JAMES  |  950 |    2 |
| ADAMS  | 1100 |    3 |
| MARTIN | 1250 |    4 |
| WARD   | 1250 |    4 |
| TURNER | 1500 |    6 |
+--------+------+------+

Query -

select 
    ENAME,SAL,dense_rank() over (order by SAL) DEN_RANK
from 
    EMP;

Output -

+--------+------+-----------+
| ENAME  | SAL  |  DEN_RANK |
+--------+------+-----------+
| SMITH  |  800 |         1 |
| JAMES  |  950 |         2 |
| ADAMS  | 1100 |         3 |
| MARTIN | 1250 |         4 |
| WARD   | 1250 |         4 |
| TURNER | 1500 |         5 |
+--------+------+-----------+

A
Anant_00
SELECT empno,
       deptno,
       sal,
       RANK() OVER (PARTITION BY deptno ORDER BY sal) "rank"
FROM   emp;

     EMPNO     DEPTNO        SAL       rank
---------- ---------- ---------- ----------
      7934         10       1300          1
      7782         10       2450          2
      7839         10       5000          3
      7369         20        800          1
      7876         20       1100          2
      7566         20       2975          3
      7788         20       3000          4
      7902         20       3000          4
      7900         30        950          1
      7654         30       1250          2
      7521         30       1250          2
      7844         30       1500          4
      7499         30       1600          5
      7698         30       2850          6


SELECT empno,
       deptno,
       sal,
       DENSE_RANK() OVER (PARTITION BY deptno ORDER BY sal) "rank"
FROM   emp;

     EMPNO     DEPTNO        SAL       rank
---------- ---------- ---------- ----------
      7934         10       1300          1
      7782         10       2450          2
      7839         10       5000          3
      7369         20        800          1
      7876         20       1100          2
      7566         20       2975          3
      7788         20       3000          4
      7902         20       3000          4
      7900         30        950          1
      7654         30       1250          2
      7521         30       1250          2
      7844         30       1500          3
      7499         30       1600          4
      7698         30       2850          5

H
Harinath
select empno
       ,salary
       ,row_number() over(order by salary desc) as Serial
       ,Rank() over(order by salary desc) as rank
       ,dense_rank() over(order by salary desc) as denseRank
from emp ;

Row_number() -> Used for generating serial number

Dense_rank() will give continuous rank but Rank() will skip rank in case of clash of rank.


S
Salman Lone

The only difference between the RANK() and DENSE_RANK() functions is in cases where there is a “tie”; i.e., in cases where multiple values in a set have the same ranking. In such cases, RANK() will assign non-consecutive “ranks” to the values in the set (resulting in gaps between the integer ranking values when there is a tie), whereas DENSE_RANK() will assign consecutive ranks to the values in the set (so there will be no gaps between the integer ranking values in the case of a tie).

For example, consider the set {25, 25, 50, 75, 75, 100}. For such a set, RANK() will return {1, 1, 3, 4, 4, 6} (note that the values 2 and 5 are skipped), whereas DENSE_RANK() will return {1,1,2,3,3,4}.


B
Brijesh Kumar Tripathi

Rank() SQL function generates rank of the data within ordered set of values but next rank after previous rank is row_number of that particular row. On the other hand, Dense_Rank() SQL function generates next number instead of generating row_number. Below is the SQL example which will clarify the concept:

Select ROW_NUMBER() over (order by Salary) as RowNum, Salary, 
RANK() over (order by Salary) as Rnk, 
DENSE_RANK() over (order by Salary) as DenseRnk from (
Select 1000 as Salary union all
Select 1000 as Salary union all
Select 1000 as Salary union all
Select 2000 as Salary union all
Select 3000 as Salary union all
Select 3000 as Salary union all
Select 8000 as Salary union all
Select 9000 as Salary) A

It will generate following output:

----------------------------
RowNum  Salary  Rnk DenseRnk
----------------------------
1       1000    1   1
2       1000    1   1
3       1000    1   1
4       2000    4   2
5       3000    5   3
6       3000    5   3
7       8000    7   4
8       9000    8   5

H
Himanshu

Rank(), Dense_rank(), row_number() These all are window functions that means they act as window over some ordered input set at first. These windows have different functionality attached to it based on the requirement. Heres the above 3 :

row_number()

Starting by row_number() as this forms the basis of these related window functions. row_number() as the name suggests gives a unique number to the set of rows over which its been applied. Similar to giving a serial number to each row.

Rank()

A subversion of row_number() can be said as rank(). Rank() is used to give same serial number to those ordered set rows which are duplicates but it still keeps the count mantained as similar to a row_number() for all those after duplicates rank() meaning as from below eg. For data 2 row_number() =rank() meaning both just differs in the form of duplicates.

Data row_number() rank() dense_rank() 
    1         1                    1       1
    1         2                    1       1
    1         3                    1       1
    2         4                    4       2

Finally,

Dense_rank() is an extended version of rank() as the name suggests its dense because as you can see from the above example rank() = dense_rank() for all data 1 but just that for data 2 it differs in the form that it mantains the order of rank() from previous rank() not the actual data


T
Tutu Kumari

Rank and Dense rank gives the rank in the partitioned dataset.

Rank() : It doesn't give you consecutive integer numbers.

Dense_rank() : It gives you consecutive integer numbers.

https://i.stack.imgur.com/fbv8Z.png

In above picture , the rank of 10008 zip is 2 by dense_rank() function and 24 by rank() function as it considers the row_number.


r
rjose

The only difference between the RANK() and DENSE_RANK() functions is in cases where there is a “tie”; i.e., in cases where multiple values in a set have the same ranking. In such cases, RANK() will assign non-consecutive “ranks” to the values in the set (resulting in gaps between the integer ranking values when there is a tie), whereas DENSE_RANK() will assign consecutive ranks to the values in the set (so there will be no gaps between the integer ranking values in the case of a tie).

For example, consider the set {30, 30, 50, 75, 75, 100}. For such a set, RANK() will return {1, 1, 3, 4, 4, 6} (note that the values 2 and 5 are skipped), whereas DENSE_RANK() will return {1,1,2,3,3,4}.