Github user NarineK commented on a diff in the pull request: https://github.com/apache/spark/pull/14090#discussion_r70202736 --- Diff: docs/sparkr.md --- @@ -306,6 +306,64 @@ head(ldf, 3) {% endhighlight %} </div> +#### Run a given function on a large dataset grouping by input column(s) and using `gapply` or `gapplyCollect` + +##### gapply +Apply a function to each group of a `SparkDataFrame`. The function is to be applied to each group of the `SparkDataFrame` and should have only two parameters: grouping key and R `data.frame` corresponding to +that key. The groups are chosen from `SparkDataFrame`s column(s). +The output of function should be a `data.frame`. Schema specifies the row format of the resulting +`SparkDataFrame`. It must match the R function's output. --- End diff -- Thanks, I was looking at types.R file and have noticed that we have NA's for array, map and struct. https://github.com/apache/spark/blob/master/R/pkg/R/types.R#L42 But I guess in our case we can have: array, map and struct mapped to array, map and struct correspondingly ?!
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