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Oracle® Database SQL Language Reference
12c Release 1 (12.1)

E17209-15
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CUME_DIST

Aggregate Syntax

cume_dist_aggregate::=

Description of cume_dist_aggregate.gif follows
Description of the illustration cume_dist_aggregate.gif

Analytic Syntax

cume_dist_analytic::=

Description of cume_dist_analytic.gif follows
Description of the illustration cume_dist_analytic.gif

See Also:

"Analytic Functions" for information on syntax, semantics, and restrictions

Purpose

CUME_DIST calculates the cumulative distribution of a value in a group of values. The range of values returned by CUME_DIST is >0 to <=1. Tie values always evaluate to the same cumulative distribution value.

This function takes as arguments any numeric data type or any nonnumeric data type that can be implicitly converted to a numeric data type. Oracle Database determines the argument with the highest numeric precedence, implicitly converts the remaining arguments to that data type, makes the calculation, and returns NUMBER.

See Also:

Table 2-10, "Implicit Type Conversion Matrix" for more information on implicit conversion and "Numeric Precedence" for information on numeric precedence

Aggregate Example

The following example calculates the cumulative distribution of a hypothetical employee with a salary of $15,500 and commission rate of 5% among the employees in the sample table oe.employees:

SELECT CUME_DIST(15500, .05) WITHIN GROUP
  (ORDER BY salary, commission_pct) "Cume-Dist of 15500" 
  FROM employees;

Cume-Dist of 15500
------------------
        .972222222

Analytic Example

The following example calculates the salary percentile for each employee in the purchasing division. For example, 40% of clerks have salaries less than or equal to Himuro.

SELECT job_id, last_name, salary, CUME_DIST() 
  OVER (PARTITION BY job_id ORDER BY salary) AS cume_dist
  FROM employees
  WHERE job_id LIKE 'PU%'
  ORDER BY job_id, last_name, salary, cume_dist;

JOB_ID     LAST_NAME                     SALARY  CUME_DIST
---------- ------------------------- ---------- ----------
PU_CLERK   Baida                           2900         .8
PU_CLERK   Colmenares                      2500         .2
PU_CLERK   Himuro                          2600         .4
PU_CLERK   Khoo                            3100          1
PU_CLERK   Tobias                          2800         .6
PU_MAN     Raphaely                       11000          1