{"action":"created","comment":{"url":"https://api.github.com/repos/apache/spark/pulls/comments/64796643","id":64796643,"diff_hunk":"@@ -319,14 +362,19 @@ final class DataFrameWriter private[sql](df: DataFrame) {\n         checkpointPath.toUri.toString\n       }\n \n-      val sink = new MemorySink(df.schema)\n+      if (!Seq(OutputMode.Append, OutputMode.Complete).contains(outputMode)) {","path":"sql/core/src/main/scala/org/apache/spark/sql/DataFrameWriter.scala","position":57,"original_position":57,"commit_id":"58f88b8f829b7a1408b2ce471b4d5d0a23031ee7","original_commit_id":"3a79d41b14535ffe4f65595126614832a094bf9b","user":{"login":"tdas","id":663212,"avatar_url":"https://avatars.githubusercontent.com/u/663212?v=3","gravatar_id":"","url":"https://api.github.com/users/tdas","html_url":"https://github.com/tdas","followers_url":"https://api.github.com/users/tdas/followers","following_url":"https://api.github.com/users/tdas/following{/other_user}","gists_url":"https://api.github.com/users/tdas/gists{/gist_id}","starred_url":"https://api.github.com/users/tdas/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/tdas/subscriptions","organizations_url":"https://api.github.com/users/tdas/orgs","repos_url":"https://api.github.com/users/tdas/repos","events_url":"https://api.github.com/users/tdas/events{/privacy}","received_events_url":"https://api.github.com/users/tdas/received_events","type":"User","site_admin":false},"body":"The tricky thing is that we want to make the Memory Sink compatible with update internally, but we may not want public API to support update mode yet.","created_at":"2016-05-26T18:30:54Z","updated_at":"2016-05-26T18:30:54Z","html_url":"https://github.com/apache/spark/pull/13286#discussion_r64796643","pull_request_url":"https://api.github.com/repos/apache/spark/pulls/13286","_links":{"self":{"href":"https://api.github.com/repos/apache/spark/pulls/comments/64796643"},"html":{"href":"https://github.com/apache/spark/pull/13286#discussion_r64796643"},"pull_request":{"href":"https://api.github.com/repos/apache/spark/pulls/13286"}}},"pull_request":{"url":"https://api.github.com/repos/apache/spark/pulls/13286","id":71307022,"html_url":"https://github.com/apache/spark/pull/13286","diff_url":"https://github.com/apache/spark/pull/13286.diff","patch_url":"https://github.com/apache/spark/pull/13286.patch","issue_url":"https://api.github.com/repos/apache/spark/issues/13286","number":13286,"state":"open","locked":false,"title":"[SPARK-15517][SQL][STREAMING] Add support for complete output mode in Structure Streaming","user":{"login":"tdas","id":663212,"avatar_url":"https://avatars.githubusercontent.com/u/663212?v=3","gravatar_id":"","url":"https://api.github.com/users/tdas","html_url":"https://github.com/tdas","followers_url":"https://api.github.com/users/tdas/followers","following_url":"https://api.github.com/users/tdas/following{/other_user}","gists_url":"https://api.github.com/users/tdas/gists{/gist_id}","starred_url":"https://api.github.com/users/tdas/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/tdas/subscriptions","organizations_url":"https://api.github.com/users/tdas/orgs","repos_url":"https://api.github.com/users/tdas/repos","events_url":"https://api.github.com/users/tdas/events{/privacy}","received_events_url":"https://api.github.com/users/tdas/received_events","type":"User","site_admin":false},"body":"## What changes were proposed in this pull request?\r\nCurrently structured streaming only supports append output mode.  This PR adds the following.\r\n\r\n- Added support for Complete output mode in the internal state store, analyzer and planner.\r\n- Added public API in Scala and Python for users to specify output mode\r\n- Added checks for unsupported combinations of output mode and DF operations\r\n  - Plans with no aggregation should support only Append mode\r\n  - Plans with aggregation should support only Update and Complete modes\r\n  - Default output mode is Append mode (**Question: should we change this to automatically set to Complete mode when there is aggregation?**)\r\n- Added support for Complete output mode in Memory Sink. So Memory Sink supports append and complete, not update. (**Question: Should it support Update?**)\r\n\r\nTODO:\r\n- [ ] Add tests in Memory Sink to test end-to-end behavior using writer.format(\"memory\") and different output modes.\r\n\r\n## How was this patch tested?\r\nUnit tests in various test suites\r\n- StreamingAggregationSuite: tests for complete mode\r\n- MemorySinkSuite: tests for checking behavior in Append and Complete modes. \r\n- UnsupportedOperationSuite: tests for checking unsupported combinations of DF ops and output modes\r\n- DataFrameReaderWriterSuite: tests for checking that output mode cannot be called on static 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