CUME_DIST window function - Amazon Redshift
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# CUME_DIST window function

Calculates the cumulative distribution of a value within a window or partition. Assuming ascending ordering, the cumulative distribution is determined using this formula:

```count of rows with values <= x / count of rows in the window or partition```

where x equals the value in the current row of the column specified in the ORDER BY clause. The following dataset illustrates use of this formula:

``````Row#	Value	  Calculation    CUME_DIST
1        2500	   (1)/(5)	   0.2
2        2600	   (2)/(5)	   0.4
3        2800	   (3)/(5)	   0.6
4        2900	   (4)/(5)	   0.8
5        3100	   (5)/(5)	   1.0``````

The return value range is >0 to 1, inclusive.

## Syntax

``````CUME_DIST ()
OVER (
[ PARTITION BY partition_expression ]
[ ORDER BY order_list ]
)``````

## Arguments

OVER

A clause that specifies the window partitioning. The OVER clause cannot contain a window frame specification.

PARTITION BY partition_expression

Optional. An expression that sets the range of records for each group in the OVER clause.

ORDER BY order_list

The expression on which to calculate cumulative distribution. The expression must have either a numeric data type or be implicitly convertible to one. If ORDER BY is omitted, the return value is 1 for all rows.

If ORDER BY doesn't produce a unique ordering, the order of the rows is nondeterministic. For more information, see Unique ordering of data for window functions.

FLOAT8

## Examples

The following example calculates the cumulative distribution of the quantity for each seller:

``````select sellerid, qty, cume_dist()
over (partition by sellerid order by qty)
from winsales;

sellerid   qty	   cume_dist
--------------------------------------------------
1         10.00	   0.33
1         10.64	   0.67
1         30.37	   1
3         10.04	   0.25
3         15.15	   0.5
3         20.75	   0.75
3         30.55	   1
2         20.09	   0.5
2         20.12	   1
4         10.12	   0.5
4         40.23	   1``````

For a description of the WINSALES table, see Sample table for window function examples.