Amazon Redshift will no longer support the creation of new Python UDFs starting Patch 198. Existing Python UDFs will continue to function until June 30, 2026. For more information, see the [ blog post ](https://aws.amazon.com/blogs/big-data/amazon-redshift-python-user-defined-functions-will-reach-end-of-support-after-june-30-2026/). 

# CUME\$1DIST window function
<a name="r_WF_CUME_DIST"></a>

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
<a name="r_WF_CUME_DIST-synopsis"></a>

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

## Arguments
<a name="r_WF_CUME_DIST-arguments"></a>

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

PARTITION BY *partition\$1expression*   
Optional. An expression that sets the range of records for each group in the OVER clause.

ORDER BY *order\$1list*   
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](c_Window_functions.md#r_Examples_order_by_WF). 

## Return type
<a name="r_WF_CUME_DIST-returns"></a>

FLOAT8

## Examples
<a name="r_WF_CUME_DIST-examples"></a>

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](c_Window_functions.md#r_Window_function_example).