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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2020/10/24 06:51:16 UTC

[GitHub] [spark] HeartSaVioR opened a new pull request #27333: [SPARK-29438][SS][FOLLOWUP] Add regression tests for Streaming Aggregation and flatMapGroupsWithState

HeartSaVioR opened a new pull request #27333:
URL: https://github.com/apache/spark/pull/27333


   ### What changes were proposed in this pull request?
   
   This patch adds new UTs to prevent SPARK-29438 for streaming aggregation as well as flatMapGroupsWithState, as we agree about the review comment quote here:
   
   https://github.com/apache/spark/pull/26162#issuecomment-576929692
   
   > LGTM for this PR. But on a additional note, this is a very subtle and easy-to-make bug with TaskContext.getPartitionId. I wonder if this bug is present in any other stateful operation. I wonder if this bug is present in any other stateful operation. Can you please verify how partitionId is used in the other stateful operations?
   
   For now they're not broken, but even better if we have UTs to prevent the case for the future.
   
   ### Why are the changes needed?
   
   New UTs will prevent streaming aggregation and flatMapGroupsWithState to be broken in future where it is placed on the right side of UNION and the number of partition is changing on the left side of UNION. Please refer SPARK-29438 for more details.
   
   ### Does this PR introduce any user-facing change?
   
   No.
   
   ### How was this patch tested?
   
   Added UTs.


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Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/spark/pull/27333#issuecomment-675252970


   **[Test build #127536 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/127536/testReport)** for PR 27333 at commit [`466363e`](https://github.com/apache/spark/commit/466363edb22ea83a81e21a72f1b983dc7b5a733e).


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[GitHub] [spark] viirya closed pull request #27333: [SPARK-29438][SS][FOLLOWUP] Add regression tests for Streaming Aggregation and flatMapGroupsWithState

Posted by GitBox <gi...@apache.org>.
viirya closed pull request #27333:
URL: https://github.com/apache/spark/pull/27333


   


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[GitHub] [spark] viirya commented on pull request #27333: [SPARK-29438][SS][FOLLOWUP] Add regression tests for Streaming Aggregation and flatMapGroupsWithState

Posted by GitBox <gi...@apache.org>.
viirya commented on pull request #27333:
URL: https://github.com/apache/spark/pull/27333#issuecomment-716032349


   Will merge this once jenkins pass.


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[GitHub] [spark] HeartSaVioR commented on pull request #27333: [SPARK-29438][SS][FOLLOWUP] Add regression tests for Streaming Aggregation and flatMapGroupsWithState

Posted by GitBox <gi...@apache.org>.
HeartSaVioR commented on pull request #27333:
URL: https://github.com/apache/spark/pull/27333#issuecomment-643729369


   retest this, please


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[GitHub] [spark] HeartSaVioR commented on pull request #27333: [SPARK-29438][SS][FOLLOWUP] Add regression tests for Streaming Aggregation and flatMapGroupsWithState

Posted by GitBox <gi...@apache.org>.
HeartSaVioR commented on pull request #27333:
URL: https://github.com/apache/spark/pull/27333#issuecomment-643706079


   retest this, please


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[GitHub] [spark] HeartSaVioR commented on pull request #27333: [SPARK-29438][SS][FOLLOWUP] Add regression tests for Streaming Aggregation and flatMapGroupsWithState

Posted by GitBox <gi...@apache.org>.
HeartSaVioR commented on pull request #27333:
URL: https://github.com/apache/spark/pull/27333#issuecomment-634491784


   retest this, please


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[GitHub] [spark] HeartSaVioR commented on pull request #27333: [SPARK-29438][SS][FOLLOWUP] Add regression tests for Streaming Aggregation and flatMapGroupsWithState

Posted by GitBox <gi...@apache.org>.
HeartSaVioR commented on pull request #27333:
URL: https://github.com/apache/spark/pull/27333#issuecomment-634420114


   retest this, please


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[GitHub] [spark] SparkQA commented on pull request #27333: [SPARK-29438][SS][FOLLOWUP] Add regression tests for Streaming Aggregation and flatMapGroupsWithState

Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #27333:
URL: https://github.com/apache/spark/pull/27333#issuecomment-643756712


   **[Test build #124001 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/124001/testReport)** for PR 27333 at commit [`466363e`](https://github.com/apache/spark/commit/466363edb22ea83a81e21a72f1b983dc7b5a733e).
    * This patch passes all tests.
    * This patch merges cleanly.
    * This patch adds no public classes.


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[GitHub] [spark] HeartSaVioR commented on pull request #27333: [SPARK-29438][SS][FOLLOWUP] Add regression tests for Streaming Aggregation and flatMapGroupsWithState

Posted by GitBox <gi...@apache.org>.
HeartSaVioR commented on pull request #27333:
URL: https://github.com/apache/spark/pull/27333#issuecomment-715810779


   Accidentally closed this - don't get the UX on Github mobile app. (Don't know how to reopen in the app.) Will reopen soon.


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Posted by GitBox <gi...@apache.org>.
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Posted by GitBox <gi...@apache.org>.
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    * This patch **fails due to an unknown error code, -9**.
    * This patch merges cleanly.
    * This patch adds no public classes.


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[GitHub] [spark] viirya commented on a change in pull request #27333: [SPARK-29438][SS][FOLLOWUP] Add regression tests for Streaming Aggregation and flatMapGroupsWithState

Posted by GitBox <gi...@apache.org>.
viirya commented on a change in pull request #27333:
URL: https://github.com/apache/spark/pull/27333#discussion_r511492575



##########
File path: sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsWithStateSuite.scala
##########
@@ -1019,6 +1019,56 @@ class FlatMapGroupsWithStateSuite extends StateStoreMetricsTest {
       spark.createDataset(Seq(("a", 2), ("b", 1))).toDF)
   }
 
+  testWithAllStateVersions("SPARK-29438: ensure UNION doesn't lead (flat)MapGroupsWithState" +
+    " to use shifted partition IDs") {
+    val stateFunc = (key: String, values: Iterator[String], state: GroupState[RunningCount]) => {
+      val count = state.getOption.map(_.count).getOrElse(0L) + values.size
+      state.update(RunningCount(count))
+      (key, count.toString)
+    }
+
+    def constructUnionDf(desiredPartitionsForInput1: Int)
+      : (MemoryStream[String], MemoryStream[String], DataFrame) = {
+      val input1 = MemoryStream[String](desiredPartitionsForInput1)
+      val input2 = MemoryStream[String]
+      val df1 = input1.toDF()
+        .select($"value", $"value")
+      val df2 = input2.toDS()
+        .groupByKey(x => x)
+        .mapGroupsWithState(stateFunc) // Types = State: MyState, Out: (Str, Str)
+        .toDF()
+
+      // Unioned DF would have columns as (String, String)
+      (input1, input2, df1.union(df2))
+    }
+
+    withTempDir { checkpointDir =>
+      val (input1, input2, unionDf) = constructUnionDf(2)
+      testStream(unionDf, Update)(
+        StartStream(checkpointLocation = checkpointDir.getAbsolutePath),
+        MultiAddData(input1, "input1-a")(input2, "input2-a"),
+        CheckNewAnswer(("input1-a", "input1-a"), ("input2-a", "1")),
+        StopStream
+      )
+
+      // We're restoring the query with different number of partitions in left side of UNION,
+      // which may lead right side of union to have mismatched partition IDs (e.g. if it relies on
+      // TaskContext.partitionId()). This test will verify (flat)MapGroupsWithState doesn't have
+      // such issue.
+
+      val (newInput1, newInput2, newUnionDf) = constructUnionDf(3)
+
+      newInput1.addData("input1-a")
+      newInput2.addData("input2-a")

Review comment:
       Oh I got it. We reuse the same checkpoint directory and so we need to fill same batches of previous stream query. Actually we even don't need to put the same data.
   
   Then the new query begins from the new added data, and read the same state store.




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[GitHub] [spark] viirya commented on a change in pull request #27333: [SPARK-29438][SS][FOLLOWUP] Add regression tests for Streaming Aggregation and flatMapGroupsWithState

Posted by GitBox <gi...@apache.org>.
viirya commented on a change in pull request #27333:
URL: https://github.com/apache/spark/pull/27333#discussion_r511309080



##########
File path: sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsWithStateSuite.scala
##########
@@ -1019,6 +1019,56 @@ class FlatMapGroupsWithStateSuite extends StateStoreMetricsTest {
       spark.createDataset(Seq(("a", 2), ("b", 1))).toDF)
   }
 
+  testWithAllStateVersions("SPARK-29438: ensure UNION doesn't lead (flat)MapGroupsWithState" +
+    " to use shifted partition IDs") {
+    val stateFunc = (key: String, values: Iterator[String], state: GroupState[RunningCount]) => {
+      val count = state.getOption.map(_.count).getOrElse(0L) + values.size
+      state.update(RunningCount(count))
+      (key, count.toString)
+    }
+
+    def constructUnionDf(desiredPartitionsForInput1: Int)
+      : (MemoryStream[String], MemoryStream[String], DataFrame) = {
+      val input1 = MemoryStream[String](desiredPartitionsForInput1)
+      val input2 = MemoryStream[String]
+      val df1 = input1.toDF()
+        .select($"value", $"value")
+      val df2 = input2.toDS()
+        .groupByKey(x => x)
+        .mapGroupsWithState(stateFunc) // Types = State: MyState, Out: (Str, Str)
+        .toDF()
+
+      // Unioned DF would have columns as (String, String)
+      (input1, input2, df1.union(df2))
+    }
+
+    withTempDir { checkpointDir =>
+      val (input1, input2, unionDf) = constructUnionDf(2)
+      testStream(unionDf, Update)(
+        StartStream(checkpointLocation = checkpointDir.getAbsolutePath),
+        MultiAddData(input1, "input1-a")(input2, "input2-a"),
+        CheckNewAnswer(("input1-a", "input1-a"), ("input2-a", "1")),
+        StopStream
+      )
+
+      // We're restoring the query with different number of partitions in left side of UNION,
+      // which may lead right side of union to have mismatched partition IDs (e.g. if it relies on
+      // TaskContext.partitionId()). This test will verify (flat)MapGroupsWithState doesn't have
+      // such issue.
+
+      val (newInput1, newInput2, newUnionDf) = constructUnionDf(3)
+
+      newInput1.addData("input1-a")
+      newInput2.addData("input2-a")

Review comment:
       Why we need to add data here? Don't we rely on `MultiAddData` below to add more data to `newInput1` and `newInput2`?




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   Thanks. Merging to master.


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Posted by GitBox <gi...@apache.org>.
HeartSaVioR commented on a change in pull request #27333:
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##########
File path: sql/core/src/test/scala/org/apache/spark/sql/streaming/FlatMapGroupsWithStateSuite.scala
##########
@@ -1019,6 +1019,56 @@ class FlatMapGroupsWithStateSuite extends StateStoreMetricsTest {
       spark.createDataset(Seq(("a", 2), ("b", 1))).toDF)
   }
 
+  testWithAllStateVersions("SPARK-29438: ensure UNION doesn't lead (flat)MapGroupsWithState" +
+    " to use shifted partition IDs") {
+    val stateFunc = (key: String, values: Iterator[String], state: GroupState[RunningCount]) => {
+      val count = state.getOption.map(_.count).getOrElse(0L) + values.size
+      state.update(RunningCount(count))
+      (key, count.toString)
+    }
+
+    def constructUnionDf(desiredPartitionsForInput1: Int)
+      : (MemoryStream[String], MemoryStream[String], DataFrame) = {
+      val input1 = MemoryStream[String](desiredPartitionsForInput1)
+      val input2 = MemoryStream[String]
+      val df1 = input1.toDF()
+        .select($"value", $"value")
+      val df2 = input2.toDS()
+        .groupByKey(x => x)
+        .mapGroupsWithState(stateFunc) // Types = State: MyState, Out: (Str, Str)
+        .toDF()
+
+      // Unioned DF would have columns as (String, String)
+      (input1, input2, df1.union(df2))
+    }
+
+    withTempDir { checkpointDir =>
+      val (input1, input2, unionDf) = constructUnionDf(2)
+      testStream(unionDf, Update)(
+        StartStream(checkpointLocation = checkpointDir.getAbsolutePath),
+        MultiAddData(input1, "input1-a")(input2, "input2-a"),
+        CheckNewAnswer(("input1-a", "input1-a"), ("input2-a", "1")),
+        StopStream
+      )
+
+      // We're restoring the query with different number of partitions in left side of UNION,
+      // which may lead right side of union to have mismatched partition IDs (e.g. if it relies on
+      // TaskContext.partitionId()). This test will verify (flat)MapGroupsWithState doesn't have
+      // such issue.
+
+      val (newInput1, newInput2, newUnionDf) = constructUnionDf(3)
+
+      newInput1.addData("input1-a")
+      newInput2.addData("input2-a")

Review comment:
       We're initializing the different memory streams here, which are not aware of previous data and require us to fill the same data again on restore. (Each addition to the memory stream represents a batch, hence you'll need to add the same for the new memory stream.)
   
   Probably there could be the another kind of small improvement for tests if we have convenient way to push all the input rows we put before to the new memory stream. That may be dealt with minor PR.




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