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From andrewor14 <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-6847][Core][Streaming]Fix stack overflo...
Date Mon, 01 Feb 2016 19:01:24 GMT
Github user andrewor14 commented on a diff in the pull request:

    https://github.com/apache/spark/pull/10934#discussion_r51463360
  
    --- Diff: streaming/src/test/scala/org/apache/spark/streaming/CheckpointSuite.scala ---
    @@ -821,6 +821,75 @@ class CheckpointSuite extends TestSuiteBase with DStreamCheckpointTester
         checkpointWriter.stop()
       }
     
    +  test("SPARK-6847: stack overflow when updateStateByKey is followed by a checkpointed
dstream") {
    +    // In this test, there are two updateStateByKey operators. The RDD DAG is as follows:
    +    //
    +    //     batch 1            batch 2            batch 3     ...
    +    //
    +    // 1) input rdd          input rdd          input rdd
    +    //       |                  |                  |
    +    //       v                  v                  v
    +    // 2) cogroup rdd   ---> cogroup rdd   ---> cogroup rdd  ...
    +    //       |         /        |         /        |
    +    //       v        /         v        /         v
    +    // 3)  map rdd ---        map rdd ---        map rdd     ...
    +    //       |                  |                  |
    +    //       v                  v                  v
    +    // 4) cogroup rdd   ---> cogroup rdd   ---> cogroup rdd  ...
    +    //       |         /        |         /        |
    +    //       v        /         v        /         v
    +    // 5)  map rdd ---        map rdd ---        map rdd     ...
    +    //
    +    // Every batch depends on its previous batch, so "updateStateByKey" needs to do checkpoint
to
    +    // break the RDD chain. However, before SPARK-6847, when the state RDD (layer 5)
of the second
    +    // "updateStateByKey" does checkpoint, it won't checkpoint the state RDD (layer 3)
of the first
    +    // "updateStateByKey" (Note: "updateStateByKey" has already marked that its state
RDD (layer 3)
    +    // should be checkpointed). Hence, the connections between layer 2 and layer 3 won't
be broken
    +    // and the RDD chain will grow infinitely and cause StackOverflow.
    +    //
    +    // Therefore SPARK-6847 introduces "spark.checkpoint.checkpointAllMarked" to force
checkpointing
    +    // all marked RDDs in the DAG to resolve this issue. (For the previous example, it
will break
    +    // connections between layer 2 and layer 3)
    +    ssc = new StreamingContext(master, framework, batchDuration)
    +    val batchCounter = new BatchCounter(ssc)
    +    ssc.checkpoint(checkpointDir)
    +    val inputDStream = new CheckpointInputDStream(ssc)
    +    val updateFunc = (values: Seq[Int], state: Option[Int]) => {
    +      Some(values.sum + state.getOrElse(0))
    +    }
    +    @volatile var shouldCheckpointAllMarkedRDDs = false
    +    @volatile var rddsCheckpointed = false
    +    inputDStream.map(i => (i, i))
    +      .updateStateByKey(updateFunc).checkpoint(batchDuration)
    +      .updateStateByKey(updateFunc).checkpoint(batchDuration)
    +      .foreachRDD { rdd =>
    +        /**
    +         * Find all RDDs that are marked for checkpointing in the specified RDD and its
ancestors.
    +         */
    +        def findAllMarkedRDDs(rdd: RDD[_]): List[RDD[_]] = {
    --- End diff --
    
    oh I see... that's unfortunate


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