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https://issues.apache.org/jira/browse/SPARK-21999?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16192732#comment-16192732
]
Steve Loughran commented on SPARK-21999:
----------------------------------------
Apache projects are all open source, with an open community. The ASF welcomes
contributions, and does request that people follow an etiquette of constructive
discourse: https://community.apache.org/contributors/etiquette
Personally, I've always found Sean to be helpful and polite, even when I've
turned out to be utterly wrong. I'd advise listening to his feedback, and not
view it as a personal criticism. Whatever problem you have, faulting him isn't
going to fix it.
Like I said, projects welcomes contributors and their contributions.
# One key area where people can get their hands dirty in a project is
documentation. Do you think some content in the spark streaming guide could be
improved? Why not add that section & submit a patch for review?
# Because you'll need the latest source tree to hand to do it, before you even
worry about documenting a problem, why not see if it "has gone away", or at
least "moved somewhere else"? Working with the latest versions of the code may
seem leading edge, but its the best way to get your problems fixed, and the
only way to pick up an immediate patch.
# For any issue in a project, it doesn't get fixed ASAP, at least not in a form
you can pick up and use unless you have that build environment yourself. If you
are using a software product built on spark, well, you'll need to wait for that
supplier to update their release, which happens on their release schedule. For
the ASF releases, there's a release process and timetable.
# Which means: for now, you have to come up with a solution to your problem.
Given it's related to structure serialization, well, you can implement your own
{{readObject}} and {{writeObject}} methods, and so perhaps wrap the structures
being serialized with something which implements a broader locking structure
across your data. It's what I'd try first, as it would be an interesting little
problem: A datastructure which can have mutating operations invoked while
serialization is in progress. Testing this would be fun...you'd need some kind
of mock OutputStream which could block on a write() so you could guarantee the
writer thread was blocking at the correct place for the mutation call to
trigger the failure.
As to whether it's architectural, well, that's something which could be
debated. Checkpointing the state of streaming applications is one of those
challenging problems, especially if the notion of "where you are" across
multiple input streams is hard, and, if the cost of preserving state is high,
any attempt to block for the operation will hurt throughput. And changing
checkpoint architectures is so fundamental that its not some one-line patch.
If you can fix your structures up to be robustly serializable during
asynchronous writes, you'll get performance as well as robustness.
> ConcurrentModificationException - Spark Streaming
> -------------------------------------------------
>
> Key: SPARK-21999
> URL: https://issues.apache.org/jira/browse/SPARK-21999
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.1.0
> Reporter: Michael N
> Priority: Critical
>
> Hi,
> I am using Spark Streaming v2.1.0 with Kafka 0.8. I am getting
> ConcurrentModificationException intermittently. When it occurs, Spark does
> not honor the specified value of spark.task.maxFailures. So Spark aborts the
> current batch and fetch the next batch, so it results in lost data. Its
> exception stack is listed below.
> This instance of ConcurrentModificationException is similar to the issue at
> https://issues.apache.org/jira/browse/SPARK-17463, which was about
> Serialization of accumulators in heartbeats. However, my Spark stream app
> does not use accumulators.
> The stack trace listed below occurred on the Spark master in Spark streaming
> driver at the time of data loss.
> From the line of code in the first stack trace, can you tell which object
> Spark was trying to serialize ? What is the root cause for this issue ?
> Because this issue results in lost data as described above, could you have
> this issue fixed ASAP ?
> Thanks.
> Michael N.,
> ----------------
> Stack trace of Spark Streaming driver
> ERROR JobScheduler:91: Error generating jobs for time 1505224930000 ms
> org.apache.spark.SparkException: Task not serializable
> at
> org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:298)
> at
> org.apache.spark.util.ClosureCleaner$.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:793)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1.apply(RDD.scala:792)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
> at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
> at org.apache.spark.rdd.RDD.mapPartitions(RDD.scala:792)
> at
> org.apache.spark.streaming.dstream.MapPartitionedDStream$$anonfun$compute$1.apply(MapPartitionedDStream.scala:37)
> at
> org.apache.spark.streaming.dstream.MapPartitionedDStream$$anonfun$compute$1.apply(MapPartitionedDStream.scala:37)
> at scala.Option.map(Option.scala:146)
> at
> org.apache.spark.streaming.dstream.MapPartitionedDStream.compute(MapPartitionedDStream.scala:37)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:341)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:341)
> at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:340)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:340)
> at
> org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:415)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:335)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:333)
> at scala.Option.orElse(Option.scala:289)
> at
> org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:330)
> at
> org.apache.spark.streaming.dstream.TransformedDStream$$anonfun$6.apply(TransformedDStream.scala:42)
> at
> org.apache.spark.streaming.dstream.TransformedDStream$$anonfun$6.apply(TransformedDStream.scala:42)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
> at scala.collection.immutable.List.map(List.scala:285)
> at
> org.apache.spark.streaming.dstream.TransformedDStream.compute(TransformedDStream.scala:42)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:341)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:341)
> at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:340)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:340)
> at
> org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:415)
> at
> org.apache.spark.streaming.dstream.TransformedDStream.createRDDWithLocalProperties(TransformedDStream.scala:65)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:335)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:333)
> at scala.Option.orElse(Option.scala:289)
> at
> org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:330)
> at
> org.apache.spark.streaming.dstream.ForEachDStream.generateJob(ForEachDStream.scala:48)
> at
> org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:117)
> at
> org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:116)
> at
> scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
> at
> scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
> at
> scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
> at scala.collection.AbstractTraversable.flatMap(Traversable.scala:104)
> at
> org.apache.spark.streaming.DStreamGraph.generateJobs(DStreamGraph.scala:116)
> at
> org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$3.apply(JobGenerator.scala:249)
> at
> org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$3.apply(JobGenerator.scala:247)
> at scala.util.Try$.apply(Try.scala:192)
> at
> org.apache.spark.streaming.scheduler.JobGenerator.generateJobs(JobGenerator.scala:247)
> at
> org.apache.spark.streaming.scheduler.JobGenerator.org$apache$spark$streaming$scheduler$JobGenerator$$processEvent(JobGenerator.scala:183)
> at
> org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:89)
> at
> org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:88)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> Caused by: java.util.ConcurrentModificationException
> at java.util.ArrayList.writeObject(ArrayList.java:766)
> at sun.reflect.GeneratedMethodAccessor21.invoke(Unknown Source)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at
> java.io.ObjectStreamClass.invokeWriteObject(ObjectStreamClass.java:1028)
> at
> java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1496)
> 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.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)
> ... 60 more
> 2017-09-12 07:02:10.029 ERROR
> org.apache.spark.SparkException: Task not serializable
> at
> org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:298)
> 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$$anonfun$mapPartitions$1.apply(RDD.scala:793)
> at
> org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1.apply(RDD.scala:792)
> at
> org.apache.spark.rdd.RDDOperationScope$.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:792)
> at
> org.apache.spark.streaming.dstream.MapPartitionedDStream$$anonfun$compute$1.apply(MapPartitionedDStream.scala:37)
> at
> org.apache.spark.streaming.dstream.MapPartitionedDStream$$anonfun$compute$1.apply(MapPartitionedDStream.scala:37)
> at scala.Option.map(Option.scala:146)
> at
> org.apache.spark.streaming.dstream.MapPartitionedDStream.compute(MapPartitionedDStream.scala:37)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:341)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:341)
> at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:340)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:340)
> at
> org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:415)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:335)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:333)
> at scala.Option.orElse(Option.scala:289)
> at
> org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:330)
> at
> org.apache.spark.streaming.dstream.TransformedDStream$$anonfun$6.apply(TransformedDStream.scala:42)
> at
> org.apache.spark.streaming.dstream.TransformedDStream$$anonfun$6.apply(TransformedDStream.scala:42)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
> at scala.collection.immutable.List.map(List.scala:285)
> at
> org.apache.spark.streaming.dstream.TransformedDStream.compute(TransformedDStream.scala:42)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:341)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:341)
> at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:340)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:340)
> at
> org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:415)
> at
> org.apache.spark.streaming.dstream.TransformedDStream.createRDDWithLocalProperties(TransformedDStream.scala:65)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:335)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:333)
> at scala.Option.orElse(Option.scala:289)
> at
> org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:330)
> at
> org.apache.spark.streaming.dstream.ForEachDStream.generateJob(ForEachDStream.scala:48)
> at
> org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:117)
> at
> org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:116)
> at
> scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
> at
> scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
> at
> scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
> at scala.collection.AbstractTraversable.flatMap(Traversable.scala:104)
> at
> org.apache.spark.streaming.DStreamGraph.generateJobs(DStreamGraph.scala:116)
> at
> org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$3.apply(JobGenerator.scala:249)
> at
> org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$3.apply(JobGenerator.scala:247)
> at scala.util.Try$.apply(Try.scala:192)
> at
> org.apache.spark.streaming.scheduler.JobGenerator.generateJobs(JobGenerator.scala:247)
> at
> org.apache.spark.streaming.scheduler.JobGenerator.org$apache$spark$streaming$scheduler$JobGenerator$$processEvent(JobGenerator.scala:183)
> at
> org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:89)
> at
> org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:88)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> Caused by: java.util.ConcurrentModificationException
> at java.util.ArrayList.writeObject(ArrayList.java:766)
> at sun.reflect.GeneratedMethodAccessor21.invoke(Unknown Source)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498)
> at
> java.io.ObjectStreamClass.invokeWriteObject(ObjectStreamClass.java:1028)
> at
> java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1496)
> 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.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)
> ... 60 more
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