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https://issues.apache.org/jira/browse/BEAM-6771?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16786162#comment-16786162
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Alex Amato commented on BEAM-6771:
----------------------------------
I noticed as well that equals was not implemented properly.
MetricsContainerImpl does not implement it. It will also be an expensive
operation to call it. Is it necessary to compare MetricContainerStepMaps for
equality? Perhaps for unit tests, but is it necessary for production code?
https://issues.apache.org/jira/browse/BEAM-6546?filter=-2
> Spark Runner Fails on Certain Versions of Spark 2.X
> ---------------------------------------------------
>
> Key: BEAM-6771
> URL: https://issues.apache.org/jira/browse/BEAM-6771
> Project: Beam
> Issue Type: Bug
> Components: runner-spark
> Affects Versions: 2.11.0
> Reporter: Kyle Winkelman
> Priority: Critical
>
> When updating to Beam 2.11.0, I ran into the exception at the bottom of this
> issue while running a pipeline on the Spark Runner (which worked in 2.9.0).
> My cluster uses Spark 2.2.1.
> Related Issues:
> SPARK-23697 (Proof that equals must be implemented for items being
> accumulated.)
> BEAM-1920 (In PR#3808, equals was implemented on MetricsContainerStepMap to
> get Spark to run on 2.X.)
> My analysis has lead me to believe that BEAM-6138 is the reason for this
> issue.
> Before this change, versions of Spark that are affected by SPARK-23697 would
> create a new MetricsContainerStepMap and make sure that the copied and reset
> instance (the one serialized for distribution) is equal to the initial empty
> MetricsContainerStepMap that is passed in. This would effectively check if
> two empty ConcurrentHashMaps were equal. This results in true.
> After this change, versions of Spark that are affected by SPARK-23697 would
> effectively be checking if two empty ConcurrentHashMaps were equal _*AND*_ if
> two different instances of the MetricsContainerImpl are equal. Because
> MetricsContainerImpl doesn't implement equals, this results in false.
> I believe BEAM-6546 will fix this issue, but I wanted to raise a red flag. I
> am also hoping someone can verify my analysis.
> {noformat}
> ERROR ApplicationMaster: User class threw exception:
> java.lang.RuntimeException: java.lang.AssertionError: assertion failed:
> copyAndReset must return a zero value copy
> java.lang.RuntimeException: java.lang.AssertionError: assertion failed:
> copyAndReset must return a zero value copy
> at
> org.apache.beam.runners.spark.SparkPipelineResult.runtimeExceptionFrom(SparkPipelineResult.java:54)
> at
> org.apache.beam.runners.spark.SparkPipelineResult.beamExceptionFrom(SparkPipelineResult.java:71)
> at
> org.apache.beam.runners.spark.SparkPipelineResult.waitUntilFinish(SparkPipelineResult.java:98)
> at com.optum.analyticstore.execution.Exec.run(Exec.java:276)
> at com.optum.analyticstore.execution.Exec.main(Exec.java:364)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at
> org.apache.spark.deploy.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:637)
> Caused by: java.lang.AssertionError: assertion failed: copyAndReset must
> return a zero value copy
> at scala.Predef$.assert(Predef.scala:170)
> at
> org.apache.spark.util.AccumulatorV2.writeReplace(AccumulatorV2.scala:163)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at
> java.io.ObjectStreamClass.invokeWriteReplace(ObjectStreamClass.java:1218)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1136)
> at
> java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
> at
> java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
> at
> java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
> at
> java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
> at
> java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
> at
> java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
> at
> java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1548)
> at
> java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1509)
> at
> java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1432)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1178)
> at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:348)
> at
> org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:43)
> at
> org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:100)
> at
> org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:295)
> at
> org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:288)
> at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:108)
> at org.apache.spark.SparkContext.clean(SparkContext.scala:2094)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1.apply(RDD.scala:794)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1.apply(RDD.scala:793)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
> at org.apache.spark.rdd.RDD.mapPartitions(RDD.scala:793)
> at
> org.apache.spark.api.java.JavaRDDLike$class.mapPartitionsToPair(JavaRDDLike.scala:188)
> at
> org.apache.spark.api.java.AbstractJavaRDDLike.mapPartitionsToPair(JavaRDDLike.scala:45)
> at
> org.apache.beam.runners.spark.translation.TransformTranslator$6.evaluate(TransformTranslator.java:388)
> at
> org.apache.beam.runners.spark.translation.TransformTranslator$6.evaluate(TransformTranslator.java:339)
> at
> org.apache.beam.runners.spark.SparkRunner$Evaluator.doVisitTransform(SparkRunner.java:440)
> at
> org.apache.beam.runners.spark.SparkRunner$Evaluator.visitPrimitiveTransform(SparkRunner.java:428)
> at
> org.apache.beam.sdk.runners.TransformHierarchy$Node.visit(TransformHierarchy.java:665)
> at
> org.apache.beam.sdk.runners.TransformHierarchy$Node.visit(TransformHierarchy.java:657)
> at
> org.apache.beam.sdk.runners.TransformHierarchy$Node.visit(TransformHierarchy.java:657)
> at
> org.apache.beam.sdk.runners.TransformHierarchy$Node.access$600(TransformHierarchy.java:317)
> at
> org.apache.beam.sdk.runners.TransformHierarchy.visit(TransformHierarchy.java:251)
> at org.apache.beam.sdk.Pipeline.traverseTopologically(Pipeline.java:458)
> at
> org.apache.beam.runners.spark.SparkRunner.lambda$run$1(SparkRunner.java:224)
> at
> java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
> at java.util.concurrent.FutureTask.run(FutureTask.java:266)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> at java.lang.Thread.run(Thread.java:748)
> {noformat}
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