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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