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https://issues.apache.org/jira/browse/SPARK-15797?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15894509#comment-15894509
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Pau Tallada Crespí commented on SPARK-15797:
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Hi, any progress on this? :P
> To expose groupingSets for DataFrame
> ------------------------------------
>
> Key: SPARK-15797
> URL: https://issues.apache.org/jira/browse/SPARK-15797
> Project: Spark
> Issue Type: New Feature
> Components: SQL
> Affects Versions: 1.5.1
> Reporter: Priyanka Garg
>
> Currently, Cube and rollup functions are exposed in data frame but not
> grouping sets.
> For eg.
> df.rollup($"department", $"group", $designation).avg() results into
> a. All combinations of department , group and designations
> b. All combinations of department , group , taking designation as null
> c. All departments , taking groups and designation as null
> d. taking department and group both null ( means aggregating on the complete
> data)
> On the same lines , there should be a function grouping sets , in which
> custom groupings can be specified.
> For eg.
> df.groupingSets(($"department", $"group", $"designation"), ($"group")
> ,($"designation"), () ).avg()
> This should result into:
> 1. All combinations of department, group and designation
> 2. All values of group taking department and designation as null
> 3. All values of designation, taking department and group as null.
> 4. Aggregation on complete data i.e. taking designation, group and department
> as null.
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