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https://issues.apache.org/jira/browse/SPARK-23125?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sean Owen resolved SPARK-23125.
-------------------------------
Resolution: Not A Problem
Probably, but this is a Kafka config issue. If you're not using matched Kafka
versions, that's the issue too. If you are, and the config is different across
versions, I presume you just need to set a different config.
> Offset commit failed when spark-streaming batch time is more than kafkaParams
> session timeout.
> ----------------------------------------------------------------------------------------------
>
> Key: SPARK-23125
> URL: https://issues.apache.org/jira/browse/SPARK-23125
> Project: Spark
> Issue Type: Bug
> Components: DStreams
> Affects Versions: 2.2.0
> Reporter: zhaoshijie
> Priority: Major
>
> I find DirectKafkaInputDStream(kafka010) Offset commit failed when batch time
> is more than kafkaParams session.timeout.ms .log as fellow:
> {code:java}
> 2018-01-16 05:40:00,002 ERROR
> org.apache.kafka.clients.consumer.internals.ConsumerCoordinator: Offset
> commit failed.
> org.apache.kafka.clients.consumer.CommitFailedException: Commit cannot be
> completed since the group has already rebalanced and assigned the partitions
> to another member. This means that the time between subsequent calls to
> poll() was longer than the configured session.timeout.ms, which typically
> implies that the poll loop is spending too much time message processing. You
> can address this either by increasing the session timeout or by reducing the
> maximum size of batches returned in poll() with max.poll.records.
> at
> org.apache.kafka.clients.consumer.internals.ConsumerCoordinator$OffsetCommitResponseHandler.handle(ConsumerCoordinator.java:600)
> at
> org.apache.kafka.clients.consumer.internals.ConsumerCoordinator$OffsetCommitResponseHandler.handle(ConsumerCoordinator.java:541)
> at
> org.apache.kafka.clients.consumer.internals.AbstractCoordinator$CoordinatorResponseHandler.onSuccess(AbstractCoordinator.java:679)
> at
> org.apache.kafka.clients.consumer.internals.AbstractCoordinator$CoordinatorResponseHandler.onSuccess(AbstractCoordinator.java:658)
> at
> org.apache.kafka.clients.consumer.internals.RequestFuture$1.onSuccess(RequestFuture.java:167)
> at
> org.apache.kafka.clients.consumer.internals.RequestFuture.fireSuccess(RequestFuture.java:133)
> at
> org.apache.kafka.clients.consumer.internals.RequestFuture.complete(RequestFuture.java:107)
> at
> org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient$RequestFutureCompletionHandler.onComplete(ConsumerNetworkClient.java:426)
> at org.apache.kafka.clients.NetworkClient.poll(NetworkClient.java:278)
> at
> org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.clientPoll(ConsumerNetworkClient.java:360)
> at
> org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:224)
> at
> org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:192)
> at
> org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.awaitPendingRequests(ConsumerNetworkClient.java:260)
> at
> org.apache.kafka.clients.consumer.internals.AbstractCoordinator.ensureActiveGroup(AbstractCoordinator.java:222)
> at
> org.apache.kafka.clients.consumer.internals.ConsumerCoordinator.ensurePartitionAssignment(ConsumerCoordinator.java:366)
> at
> org.apache.kafka.clients.consumer.KafkaConsumer.pollOnce(KafkaConsumer.java:978)
> at
> org.apache.kafka.clients.consumer.KafkaConsumer.poll(KafkaConsumer.java:938)
> at
> org.apache.spark.streaming.kafka010.DirectKafkaInputDStream.paranoidPoll(DirectKafkaInputDStream.scala:161)
> at
> org.apache.spark.streaming.kafka010.DirectKafkaInputDStream.latestOffsets(DirectKafkaInputDStream.scala:180)
> at
> org.apache.spark.streaming.kafka010.DirectKafkaInputDStream.compute(DirectKafkaInputDStream.scala:207)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:342)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:342)
> at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:341)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:341)
> at
> org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:416)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:336)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:334)
> at scala.Option.orElse(Option.scala:289)
> at
> org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:331)
> 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$$anonfun$apply$7.apply(DStream.scala:342)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:342)
> at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:341)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:341)
> at
> org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:416)
> at
> org.apache.spark.streaming.dstream.TransformedDStream.createRDDWithLocalProperties(TransformedDStream.scala:65)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:336)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:334)
> at scala.Option.orElse(Option.scala:289)
> at
> org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:331)
> at
> org.apache.spark.streaming.dstream.MappedDStream.compute(MappedDStream.scala:36)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:342)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:342)
> at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:341)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:341)
> at
> org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:416)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:336)
> at
> org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:334)
> at scala.Option.orElse(Option.scala:289)
> at
> org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:331)
> at
> org.apache.spark.streaming.dstream.ForEachDStream.generateJob(ForEachDStream.scala:48)
> at
> org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:122)
> at
> org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:121)
> 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:121)
> 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)
> {code}
>
> Although I think it is a kafka issue，but I find kafka version 0.10.0.1 can
> not solve this issue. this issue happend bacase of kafka client
> rebalanced,kafka client rebalanced is control by param session.timeout.ms,
> but kafka Official documents are shown as follows：
> "Note that the value must be in the allowable range as configured in the
> broker configuration by {{group.min.session.timeout.ms}} and
> {{group.max.session.timeout.ms}}."
> so, if I want to commit kafka offset successed , I must guarantee my batch
> time is smaller than {{group.max.session.timeout.ms(default 300000ms)}}. it
> is unreasonable.
> I think we shoud update streaming kafka from 0.10.0.1 to 0.10.2.0?
>
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