# ROLLINGCOUNTA Function

Computes the rolling count of non-null values forward or backward of the current row within the specified column.
• If an input value is missing or null, it is not factored in the computation. For example, for the first row in the dataset, the rolling count of non-null values of previous values is undefined.
• The row from which to extract a value is determined by the order in which the rows are organized based on the order parameter.

If you are working on a randomly generated sample of your dataset, the values that you see for this function might not correspond to the values that are generated on the full dataset during job execution.

• The function takes a column name and two optional integer parameters that determine the window backward and forward of the current row.
• The default integer parameter values are -1 and 0, which computes the rolling function from the current row back to the first row of the dataset.
• This function works with the following transforms:

For more information on a non-rolling version of this function, see COUNTA Function.

## Basic Usage

Column example:

derive type:single value:ROLLINGCOUNTA(myCol)

Output: Generates a new column containing the rolling count of non-null values in the myCol column from the first row of the dataset to the current one.

Rows before example:

window value:ROLLINGCOUNTA(myNumber, 3)

Output: Generates the new column, which contains the rolling count of non-null values of the current row and the two previous row values in the myNumber column.

Rows before and after example:

window value:ROLLINGCOUNTA(myNumber, 3, 2)

Output: Generates the new column, which contains the rolling count of non-nulls from the two previous row values, the current row value, and the two rows after the current one in the myNumber column.

## Syntax

window value:ROLLINGCOUNTA(col_ref, rowsBefore_integer, rowsAfter_integer) order: order_col [group: group_col]

ArgumentRequired?Data TypeDescription
col_refYstringName of column whose values are applied to the function
rowsBefore_integerNintegerNumber of rows before the current one to include in the computation
rowsAfter_integerNintegerNumber of rows after the current one to include in the computation

For more information on the order and group parameters, see Window Transform.

### col_ref

Name of the column whose values are used to compute the function.

• Multiple columns and wildcards are not supported.

Usage Notes:

Required?Data TypeExample Value
YesString (column reference to Integer or Decimal values)myColumn

### rowsBefore_integer, rowsAfter_integer

Integers representing the number of rows before or after the current one from which to compute the rolling function, including the current row. For example, if the first value is 5, the current row and the four rows after it are used in the computation. Negative values for k compute the rolling average from rows preceding the current one.

• rowBefore=1 generates the current row value only.
• rowBefore=-1 uses all rows preceding the current one.
• If rowsAfter is not specified, then the value 0 is applied.
• If a group parameter is applied, then these parameter values should be no more than the maximum number of rows in the groups.

Usage Notes:

Required?Data TypeExample Value
NoInteger4

## Examples

### Example - Counting messages

In the following example, messages are tabulated every 10 seconds from a system. If no message is generated, null values are returned.

Source:

TimestampmsgTypemsgDescription
15:10:00 PMwarningServer restarted.
15:10:10 PMwarningUnable to locate patterns file.
15:10:20 PM
15:10:30 PM
15:10:40 PMerrorCannot connect to data source.
15:10:50 PMerrorCannot open dataset.
15:11:00 PM
15:11:10 PM
15:11:20 PMerrorInsufficient permissions to write to target location.
15:11:30 PM
15:11:40 PMwarningServer restarted.
15:11:50 PMwarningUnable to locate patterns file.
15:12:00 PMerrorData node offline.
15:12:10 PM
15:12:20 PM
15:12:30 PMwarningInvalid statement in recipe.
15:12:40 PM
15:12:50 PM

Transform:

You are interested in counting the number of entries for the preceding minute for each row. You add the following:

derive type: multiple value: rollingcounta(msgType, 5, 0) order: Timestamp as: 'rollingcounta_msgType'

Results:

TimestampmsgTypemsgDescriptionrollingcounta_msgType
15:10:00 PMwarningServer restarted.1
15:10:10 PMwarningUnable to locate patterns file.2
15:10:20 PM 2
15:10:30 PM 2
15:10:40 PMerrorCannot connect to data source.3
15:10:50 PMerrorCannot open dataset.4
15:11:00 PM 3
15:11:10 PM 2
15:11:20 PMerrorInsufficient permissions to write to target location.3
15:11:30 PM 3
15:11:40 PMwarningServer restarted.3
15:11:50 PMwarningUnable to locate patterns file.3
15:12:00 PMerrorData node offline.4
15:12:10 PM 4
15:12:20 PM 3
15:12:30 PMwarningInvalid statement in recipe.4
15:12:40 PM 3
15:12:50 PM 2