ROLLINGSUM Function
Computes the rolling sum of 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 sum of previous values is the value in the first row.
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
and0
, which computes the rolling average from the current row back to the first row of the dataset.
This function works with the Window transform. See Window Transform.
Wrangle vs. SQL: This function is part of Wrangle, a proprietary data transformation language. Wrangle is not SQL. For more information, see Wrangle Language.
Basic Usage
Column example:
rollingsum(myCol)
Output: Returns the rolling sum of all values in the myCol
column.
Rows before example:
rollingsum(myNumber, 3)
Output: Returns the rolling sum of the current row and the three previous row values in the myNumber
column.
Rows before and after example:
rollingsum(myNumber, 3, 2)
Output: Returns the rolling sum of the three previous row values, the current row value, and the two rows after the current one in the myNumber
column.
Syntax and Arguments
rollingsum(col_ref, rowsBefore_integer, rowsAfter_integer) order: order_col [group: group_col]
Argument  Required?  Data Type  Description 

col_ref  Y  string  Name of column whose values are applied to the function 
rowsBefore_integer  N  integer  Number of rows before the current one to include in the computation. 
rowsAfter_integer  N  integer  Number of rows after the current one to include in the computation 
For more information on the order
and group
parameters, see Window Transform.
For more information on syntax standards, see Language Documentation Syntax Notes.
col_ref
Name of the column whose values are used to compute the rolling sum.
Multiple columns and wildcards are not supported.
Usage Notes:
Required?  Data Type  Example Value 

Yes  String (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 sum, including the current row. For example, if the first value is 5
, the current row and the five rows before it are used in the computation. Negative values for rowsAfter_integer
compute the rolling function from rows preceding the current one.
rowBefore=0
generates the current row value only.rowBefore=1
uses all rows preceding the current one.If
rowsAfter
is not specified, then the value0
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 Type  Example Value 

No  Integer  4 
Examples
Tip
For additional examples, see Common Tasks.
Example  Rolling window functions
This example describes how to use rolling computational functions.
Functions:
Item  Description 

ROLLINGSUM Function  Computes the rolling sum of values forward or backward of the current row within the specified column. 
ROLLINGAVERAGE Function  Computes the rolling average of values forward or backward of the current row within the specified column. 
ROWNUMBER Function  Generates a new column containing the row number as sorted by the 
Also:
Item  Description 

MONTH Function  Derives the month integer value from a Datetime value. Source value can be a a reference to a column containing Datetime values or a literal. 
FLOOR Function  Computes the largest integer that is not more than the input value. Input can be an Integer, a Decimal, a column reference, or an expression. 
ROWNUMBER Function  Generates a new column containing the row number as sorted by the 
The following dataset contains sales data over the final quarter of the year.
Source:
Date  Sales 

10/2/16  200 
10/9/16  500 
10/16/16  350 
10/23/16  400 
10/30/16  190 
11/6/16  550 
11/13/16  610 
11/20/16  480 
11/27/16  660 
12/4/16  690 
12/11/16  810 
12/18/16  950 
12/25/16  1020 
1/1/17  680 
Transformation:
First, you want to maintain the row information as a separate column. Since data is ordered already by the Date
column, you can use the following:
Transformation Name 


Parameter: Formulas  ROWNUMBER() 
Parameter: Order by  Date 
Rename this column to rowId
for week of quarter.
Now, you want to extract month and week information from the Date
values. Deriving the month value:
Transformation Name 


Parameter: Formula type  Single row formula 
Parameter: Formula  MONTH(Date) 
Parameter: New column name  'Month' 
Deriving the quarter value:
Transformation Name 


Parameter: Formula type  Single row formula 
Parameter: Formula  (1 + FLOOR(((month1)/3))) 
Parameter: New column name  'QTR' 
Deriving the weekofquarter value:
Transformation Name 


Parameter: Formulas  ROWNUMBER() 
Parameter: Group by  QTR 
Parameter: Order by  Date 
Rename this column WOQ
(week of quarter).
Deriving the weekofmonth value:
Transformation Name 


Parameter: Formulas  ROWNUMBER() 
Parameter: Group by  Month 
Parameter: Order by  Date 
Rename this column WOM
(week of month).
Now, you perform your rolling computations. Compute the running total of sales using the following:
Transformation Name 


Parameter: Formulas  ROLLINGSUM(Sales, 1, 0) 
Parameter: Group by  QTR 
Parameter: Order by  Date 
The 1
parameter is used in the above computation to gather the rolling sum of all rows of data from the current one to the first one. Note that the use of the QTR
column for grouping, which moves the value for the 01/01/2017
into its own computational bucket. This may or may not be preferred.
Rename this column QTD
(quarter todate). Now, generate a similar column to compute the rolling average of weekly sales for the quarter:
Transformation Name 


Parameter: Formulas  ROUND(ROLLINGAVERAGE(Sales, 1, 0)) 
Parameter: Group by  QTR 
Parameter: Order by  Date 
Since the ROLLINGAVERAGE
function can compute fractional values, it is wrapped in the ROUND
function for neatness. Rename this column avgWeekByQuarter
.
Results:
When the unnecessary columns are dropped and some reordering is applied, your dataset should look like the following:
Date  WOQ  Sales  QTD  avgWeekByQuarter 

10/2/16  1  200  200  200 
10/9/16  2  500  700  350 
10/16/16  3  350  1050  350 
10/23/16  4  400  1450  363 
10/30/16  5  190  1640  328 
11/6/16  6  550  2190  365 
11/13/16  7  610  2800  400 
11/20/16  8  480  3280  410 
11/27/16  9  660  3940  438 
12/4/16  10  690  4630  463 
12/11/16  11  810  5440  495 
12/18/16  12  950  6390  533 
12/25/16  13  1020  7410  570 
1/1/17  1  680  680  680 