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Overview

PERCENT_RANK() window function determines the relative rank of a value in a group of values, based on the ORDER BY expression in the OVER clause. It can be used with all data types supported by Oxla.

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Syntax

The syntax for this function is as follows:

PERCENT_RANK() OVER (
   [PARTITION BY partition_expression]
   ORDER BY sort_expression
)

The PERCENT_RANK() is calculated as:

(r - 1) / (n - 1)

Where r is the rank of the current row and n is the total number of rows in the window or partition.

Rows with equal values for the ranking criteria receive the same relative rank. The output data type for this function is DOUBLE PRECISION. The output will indicate the rank of values in a table, regardless of the input types.

  • If the optional PARTITION BY expression is present, the rankings are reset for each group of rows
  • If the ORDER BY expression is omitted then all relative ranks are equal to 0

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Parameters

  • (): this function takes no arguments but parentheses is required
  • PARTITION BY: optional clause used to divide the result set into partitions (PERCENT_RANK() function is applied to each partition independently)
  • ORDER BY: order of rows in each partition to which the function is applied

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Examples

For the needs of this section, we will create the winsales table that stores details about some sales transactions:

CREATE TABLE winsales(
    salesid int,
    dateid date,
    sellerid int,
    buyerid text,
    qty int,
    qty_shipped int);
INSERT INTO winsales VALUES
    (30001, '8/2/2003', 3, 'b', 10, 10),
    (10001, '12/24/2003', 1, 'c', 10, 10),
    (10005, '12/24/2003', 1, 'a', 30, null),
    (40001, '1/9/2004', 4, 'a', 40, null),
    (10006, '1/18/2004', 1, 'c', 10, null),
    (20001, '2/12/2004', 2, 'b', 20, 20),
    (40005, '2/12/2004', 4, 'a', 10, 10),
    (20002, '2/16/2004', 2, 'c', 20, 20),
    (30003, '4/18/2004', 3, 'b', 15, null),
    (30004, '4/18/2004', 3, 'b', 20, null),
    (30007, '9/7/2004', 3, 'c', 30, null);

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PERCENT_RANK() with ORDER BY

In this example, we will focus on executing the PERCENT_RANK() function with ORDER BY keyword and calculate the descending percent rank of all rows based on the quantity sold:

SELECT salesid, qty
   PERCENT_RANK() OVER (ORDER BY qty DESC) AS p_rnk
   RANK() OVER (ORDER BY qty DESC) AS rnk
FROM winsales
ORDER BY 2,1;

Here is the output for the query presented above that includes the sales ID along with the quantity sold and both percent and regular ranks:

   salesid | qty | p_rnk | rnk 
---------+-----+-------+-----
   10001 |  10 |   0.7 |   8
   10006 |  10 |   0.7 |   8
   30001 |  10 |   0.7 |   8
   40005 |  10 |   0.7 |   8
   30003 |  15 |   0.6 |   7
   20001 |  20 |   0.3 |   4
   20002 |  20 |   0.3 |   4
   30004 |  20 |   0.3 |   4
   10005 |  30 |   0.1 |   2
   30007 |  30 |   0.1 |   2
   40001 |  40 |     0 |   1

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PERCENT_RANK() with ORDER BY and PARTITION BY

In this example, we will focus on executing the PERCENT_RANK() function with ORDER BY keyword and PARTITION BY clause, partition the table by seller ID, order each partition by the quantity and assign a percent rank to each row:

SELECT salesid, sellerid, qty
   PERCENT_RANK() OVER (PARTITION BY sellerid ORDER BY qty DESC) AS p_rnk
FROM winsales
ORDER BY 2,3,1;

Here is the output for the query presented above:

  salesid | sellerid | qty |       p_rnk        
---------+----------+-----+--------------------
   10001 |        1 |  10 |                0.5
   10006 |        1 |  10 |                0.5
   10005 |        1 |  30 |                  0
   20001 |        2 |  20 |                  0
   20002 |        2 |  20 |                  0
   30001 |        3 |  10 |                  1
   30003 |        3 |  15 | 0.6666666666666666
   30004 |        3 |  20 | 0.3333333333333333
   30007 |        3 |  30 |                  0
   40005 |        4 |  10 |                  1
   40001 |        4 |  40 |                  0
(11 rows)