{"action":"created","comment":{"url":"https://api.github.com/repos/apache/spark/pulls/comments/66671272","id":66671272,"diff_hunk":"@@ -286,6 +290,9 @@ case class FlatMapGroupsInR(\n     child: LogicalPlan) extends UnaryNode with ObjectProducer{\n \n   override lazy val schema = outputSchema\n+\n+  override protected def stringArgs: Iterator[Any] = Iterator(inputSchema, outputSchema,\n+    outputObjAttr, child)","path":"sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/object.scala","position":null,"original_position":18,"commit_id":"0ca74fddc91a94d8b5c69c2e510afeee8531c0e2","original_commit_id":"20a1c37f348ca90a03100814e6c3d5327396a6ce","user":{"login":"shivaram","id":143893,"avatar_url":"https://avatars.githubusercontent.com/u/143893?v=3","gravatar_id":"","url":"https://api.github.com/users/shivaram","html_url":"https://github.com/shivaram","followers_url":"https://api.github.com/users/shivaram/followers","following_url":"https://api.github.com/users/shivaram/following{/other_user}","gists_url":"https://api.github.com/users/shivaram/gists{/gist_id}","starred_url":"https://api.github.com/users/shivaram/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/shivaram/subscriptions","organizations_url":"https://api.github.com/users/shivaram/orgs","repos_url":"https://api.github.com/users/shivaram/repos","events_url":"https://api.github.com/users/shivaram/events{/privacy}","received_events_url":"https://api.github.com/users/shivaram/received_events","type":"User","site_admin":false},"body":"Ah I see - Sorry. I think I saw the diff from one commit there. Also it looks like that commit reverted the override change to the MapPartitionsInR class ?  I think thats useful to have. Do you want to do  that in a separate PR ?","created_at":"2016-06-10T19:50:35Z","updated_at":"2016-06-10T19:50:35Z","html_url":"https://github.com/apache/spark/pull/12836#discussion_r66671272","pull_request_url":"https://api.github.com/repos/apache/spark/pulls/12836","_links":{"self":{"href":"https://api.github.com/repos/apache/spark/pulls/comments/66671272"},"html":{"href":"https://github.com/apache/spark/pull/12836#discussion_r66671272"},"pull_request":{"href":"https://api.github.com/repos/apache/spark/pulls/12836"}}},"pull_request":{"url":"https://api.github.com/repos/apache/spark/pulls/12836","id":68527135,"html_url":"https://github.com/apache/spark/pull/12836","diff_url":"https://github.com/apache/spark/pull/12836.diff","patch_url":"https://github.com/apache/spark/pull/12836.patch","issue_url":"https://api.github.com/repos/apache/spark/issues/12836","number":12836,"state":"open","locked":false,"title":"[SPARK-12922][SparkR][WIP] Implement gapply() on DataFrame in SparkR","user":{"login":"NarineK","id":12010601,"avatar_url":"https://avatars.githubusercontent.com/u/12010601?v=3","gravatar_id":"","url":"https://api.github.com/users/NarineK","html_url":"https://github.com/NarineK","followers_url":"https://api.github.com/users/NarineK/followers","following_url":"https://api.github.com/users/NarineK/following{/other_user}","gists_url":"https://api.github.com/users/NarineK/gists{/gist_id}","starred_url":"https://api.github.com/users/NarineK/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/NarineK/subscriptions","organizations_url":"https://api.github.com/users/NarineK/orgs","repos_url":"https://api.github.com/users/NarineK/repos","events_url":"https://api.github.com/users/NarineK/events{/privacy}","received_events_url":"https://api.github.com/users/NarineK/received_events","type":"User","site_admin":false},"body":"## What changes were proposed in this pull request?\r\n\r\ngapply() applies an R function on groups grouped by one or more columns of a DataFrame, and returns a DataFrame. It is like GroupedDataSet.flatMapGroups() in the Dataset API.\r\n\r\nPlease, let me know what do you think and if you have any ideas to improve it.\r\n\r\nThank you!\r\n\r\n## How was this patch tested?\r\nUnit tests.\r\n1. Primitive test with different column types\r\n2. Add a boolean column\r\n3. Compute average by a 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