SUM Function

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Computes the sum of all values found in all row values in a column. Input column can be of Integer or Decimal.

If a row contains a missing or null value, it is not factored into the calculation. If no numeric values are found in the source column, the function returns 0.
When used in a pivot transform, the function is computed for each instance of the value specified in the group parameter. See Pivot Transform.

For a version of this function computed over a rolling window of rows, see ROLLINGSUM Function.

Basic Usage

pivot value:SUM(myRating) group:postal_code limit:1

Output: Generates a two-column column containing the unique values of the postal_code column and the sum of the group of values from the myRating column for the postal_code value. The limit parameter defines the maximum number of output columns.

Syntax and Arguments

pivot value:SUM(function_col_ref) [group:group_col_ref] [limit:limit_count]

Argument	Required?	Data Type	Description
function_col_ref	Y	string	Name of column to which to apply the function

For more information on the group and limit parameters, see Pivot Transform.

For more information on syntax standards, see Language Documentation Syntax Notes.

function_col_ref

Name of the column the values of which you want to calculate the sum. Column must contain Integer or Decimal values.

Literal values are not supported as inputs.
Multiple columns and wildcards are not supported.

Usage Notes:

Required?	Data Type	Example Value
Yes	String (column reference)	`myValues`

Examples

Tip: For additional examples, see Common Tasks.

This example illustrates the following functions:

LIST - Extracts up to 1000 values from one column into an array in a new column. See LIST Function.
LISTUNIQUE - Extracts up to 1000 unique values from one columninto an array in a new column. See LISTUNIQUE Function.

You have the following set of orders for two months, and you are interested in identifying the set of colors that have been sold for each product for each month and the total quantity of product sold for each month.

Source:

OrderId	Date	Item	Qty	Color
1001	1/15/15	Pants	1	red
1002	1/15/15	Shirt	2	green
1003	1/15/15	Hat	3	blue
1004	1/16/15	Shirt	4	yellow
1005	1/16/15	Hat	5	red
1006	1/20/15	Pants	6	green
1007	1/15/15	Hat	7	blue
1008	4/15/15	Shirt	8	yellow
1009	4/15/15	Shoes	9	brown
1010	4/16/15	Pants	1	red
1011	4/16/15	Hat	2	green
1012	4/16/15	Shirt	3	blue
1013	4/20/15	Shoes	4	black
1014	4/20/15	Hat	5	blue
1015	4/20/15	Pants	6	black

Transform:

To track by month, you need a column containing the month value extracted from the date:

set col:Date value:DATEFORMAT(Date, 'MMM yyyy')

You can use the following transform to check the list of unique values among the colors:

pivot value: LISTUNIQUE(Color, 1000) group: Date limit:10

Date	listunique_Color
Jan 2015	["green","blue","red","yellow"]
Apr 2015	["brown","blue","red","yellow","black","green"]

Delete the above transform.

You can aggregate the data in your dataset, grouped by the reformatted Date values, and apply the LIST function to the Color column. In the same aggregation, you can include a summation function for the Qty column:

pivot value: LIST(Color, 1000) SUM(Qty) group: Date limit:10

Results:

Date	list_Color	sum_Qty
Jan 2015	["green","blue","blue","red","green","red","yellow"]	28
Apr 2015	["brown","blue","red","yellow","black","blue","black","green"]	38

If needed, you can unpack the list array data using the following:

unnest col:list_Color

See Also for SUM Function:

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SUM Function

Basic Usage

Syntax and Arguments

function_col_ref

Examples