{"action":"created","comment":{"url":"https://api.github.com/repos/apache/spark/pulls/comments/35997658","id":35997658,"diff_hunk":"@@ -244,34 +244,65 @@ private[sql] case class InsertIntoHadoopFsRelation(\n     }\n \n     def writeRows(taskContext: TaskContext, iterator: Iterator[InternalRow]): Unit = {\n+      // Track which rows have been output to disk so that if a data sort is necessary mid-write,\n+      // we don't end up outputting the same data twice\n+      val writtenRows: HashSet[InternalRow] = new HashSet[InternalRow]\n+\n+      // Flag to track whether data has been sorted in which case it's safe to close previously\n+      // used outputWriters\n+      var sorted: Boolean = false\n+\n       // If anything below fails, we should abort the task.\n       try {\n         writerContainer.executorSideSetup(taskContext)\n \n-        // Projects all partition columns and casts them to strings to build partition directories.\n-        val partitionCasts = partitionOutput.map(Cast(_, StringType))\n-        val partitionProj = newProjection(codegenEnabled, partitionCasts, output)\n-        val dataProj = newProjection(codegenEnabled, dataOutput, output)\n+        // Sort the data by partition so that it's possible to use a single outputWriter at a\n+        // time to process the incoming data\n+        def sortRows(iterator: Iterator[InternalRow]): Iterator[InternalRow] = {\n+          // Sort by the same key used to look up the outputWriter to allow us to recyle the writer\n+          iterator.toArray.sortBy(writerContainer.computePartitionPath).toIterator","path":"sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/commands.scala","position":54,"original_position":54,"commit_id":"9d5a70e4808f911dd985e63836c6cc30a0c804c8","original_commit_id":"9d5a70e4808f911dd985e63836c6cc30a0c804c8","user":{"login":"davies","id":40902,"avatar_url":"https://avatars.githubusercontent.com/u/40902?v=3","gravatar_id":"","url":"https://api.github.com/users/davies","html_url":"https://github.com/davies","followers_url":"https://api.github.com/users/davies/followers","following_url":"https://api.github.com/users/davies/following{/other_user}","gists_url":"https://api.github.com/users/davies/gists{/gist_id}","starred_url":"https://api.github.com/users/davies/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/davies/subscriptions","organizations_url":"https://api.github.com/users/davies/orgs","repos_url":"https://api.github.com/users/davies/repos","events_url":"https://api.github.com/users/davies/events{/privacy}","received_events_url":"https://api.github.com/users/davies/received_events","type":"User","site_admin":false},"body":"I think the items will be loaded into memory lazily by iterator, that's the advantage of Iterator than Array.","created_at":"2015-07-31T17:50:27Z","updated_at":"2015-07-31T17:50:27Z","html_url":"https://github.com/apache/spark/pull/7514#discussion_r35997658","pull_request_url":"https://api.github.com/repos/apache/spark/pulls/7514","_links":{"self":{"href":"https://api.github.com/repos/apache/spark/pulls/comments/35997658"},"html":{"href":"https://github.com/apache/spark/pull/7514#discussion_r35997658"},"pull_request":{"href":"https://api.github.com/repos/apache/spark/pulls/7514"}}},"pull_request":{"url":"https://api.github.com/repos/apache/spark/pulls/7514","id":40310874,"html_url":"https://github.com/apache/spark/pull/7514","diff_url":"https://github.com/apache/spark/pull/7514.diff","patch_url":"https://github.com/apache/spark/pull/7514.patch","issue_url":"https://api.github.com/repos/apache/spark/issues/7514","number":7514,"state":"open","locked":false,"title":"[SPARK-8890][SQL][WIP] Reduce memory consumption for dynamic partition insert","user":{"login":"ilganeli","id":1483345,"avatar_url":"https://avatars.githubusercontent.com/u/1483345?v=3","gravatar_id":"","url":"https://api.github.com/users/ilganeli","html_url":"https://github.com/ilganeli","followers_url":"https://api.github.com/users/ilganeli/followers","following_url":"https://api.github.com/users/ilganeli/following{/other_user}","gists_url":"https://api.github.com/users/ilganeli/gists{/gist_id}","starred_url":"https://api.github.com/users/ilganeli/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ilganeli/subscriptions","organizations_url":"https://api.github.com/users/ilganeli/orgs","repos_url":"https://api.github.com/users/ilganeli/repos","events_url":"https://api.github.com/users/ilganeli/events{/privacy}","received_events_url":"https://api.github.com/users/ilganeli/received_events","type":"User","site_admin":false},"body":"This patch will do the following based on discussion here: [https://issues.apache.org/jira/browse/SPARK-8890](SPARK-8890): \r\n\r\n1) Attempt to create new outputWriter for each partition (current behavior)\r\n2) When maximum is exceeded, pause output of rows.\r\n3) Sort all remaining data such that we can process one partition at at time.\r\n4) One partition at a time, create an outputWriter and write all rows associated with that key\r\n5) Close outputWriter for that key and open a new outputWriter, continue from step 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