sumOver
sumOver
calculates the sum of a measure partitioned by a list of
dimensions.
sumOver
is supported for use with analyses based on SPICE and direct query data sets.
Syntax
The brackets are required. To see which arguments are optional, see the following descriptions.
sumOver (
measure
,[ partition_field, ... ]
,calculation level
)
Arguments
 measure

The measure that you want to do the calculation for, for example
sum({Sales Amt})
. Use an aggregation if the calculation level is set toNULL
orPOST_AGG_FILTER
. Don't use an aggregation if the calculation level is set toPRE_FILTER
orPRE_AGG
.  partition field

(Optional) One or more dimensions that you want to partition by, separated by commas.
Each field in the list is enclosed in {} (curly braces), if it is more than one word. The entire list is enclosed in [ ] (square brackets).
 calculation level

(Optional) Specifies the calculation level to use:

PRE_FILTER
– prefilter calculations are computed before the dataset filters. 
PRE_AGG
– preaggregate calculations are computed before applying aggregations and top and bottom N filters to the visuals. 
POST_AGG_FILTER
– (default) table calculations are computed when the visuals display.
This value defaults to
POST_AGG_FILTER
when blank. For more information, see Using LevelAware Aggregations. 
Example
The following example calculates the sum of sum(Sales)
, partitioned
by City
and State
.
sumOver ( sum(Sales), [City, State] )
The following example sums Billed Amount
over Customer
Region
. This example uses the revenue sample dataset, located in an Amazon S3 bucket. The fields in the table
calculation are in the field wells of the visual.
sumOver ( sum({Billed Amount}), [{Customer Region}] )
The following screenshot shows the results of the example. With the addition of
Customer Segment
, the total amount billed for each is summed for the
Customer Region
, and displays in the calculated field.