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Posted to issues@spark.apache.org by "Dmitry Goldenberg (JIRA)" <ji...@apache.org> on 2019/04/25 15:01:00 UTC

[jira] [Created] (SPARK-27567) Spark Streaming consumers (from Kafka) intermittently die with 'SparkException: Couldn't find leaders for Set'

Dmitry Goldenberg created SPARK-27567:
-----------------------------------------

             Summary: Spark Streaming consumers (from Kafka) intermittently die with 'SparkException: Couldn't find leaders for Set'
                 Key: SPARK-27567
                 URL: https://issues.apache.org/jira/browse/SPARK-27567
             Project: Spark
          Issue Type: Bug
          Components: DStreams
    Affects Versions: 1.5.0
         Environment: GCP / 170~14.04.1-Ubuntu
            Reporter: Dmitry Goldenberg


Some of our consumers intermittently die with the stack traces I'm including. Once restarted they run for a while then die again.

I can't find any cohesive documentation on what this error means and how to go about troubleshooting it. Any help would be appreciated.

Some of the errors seen look like this:

ERROR org.apache.spark.scheduler.TaskSchedulerImpl: Lost executor 2 on 10.150.0.54: remote Rpc client disassociated

Main error stack trace:
{noformat}
2019-04-23 20:36:54,323 ERROR org.apache.spark.streaming.scheduler.JobScheduler: Error g

enerating jobs for time 1556066214000 ms

org.apache.spark.SparkException: ArrayBuffer(org.apache.spark.SparkException: Couldn't find leaders for Set([hdfs.hbase.acme.attachments,49], [hdfs.hbase.acme.attachmen

ts,63], [hdfs.hbase.acme.attachments,31], [hdfs.hbase.acme.attachments,9], [hdfs.hbase.acme.attachments,25], [hdfs.hbase.acme.attachments,55], [hdfs.hbase.acme.attachme

nts,5], [hdfs.hbase.acme.attachments,37], [hdfs.hbase.acme.attachments,7], [hdfs.hbase.acme.attachments,47], [hdfs.hbase.acme.attachments,13], [hdfs.hbase.acme.attachme

nts,43], [hdfs.hbase.acme.attachments,19], [hdfs.hbase.acme.attachments,15], [hdfs.hbase.acme.attachments,23], [hdfs.hbase.acme.attachments,53], [hdfs.hbase.acme.attach

ments,1], [hdfs.hbase.acme.attachments,27], [hdfs.hbase.acme.attachments,57], [hdfs.hbase.acme.attachments,39], [hdfs.hbase.acme.attachments,11], [hdfs.hbase.acme.attac

hments,29], [hdfs.hbase.acme.attachments,33], [hdfs.hbase.acme.attachments,35], [hdfs.hbase.acme.attachments,51], [hdfs.hbase.acme.attachments,45], [hdfs.hbase.acme.att

achments,21], [hdfs.hbase.acme.attachments,3], [hdfs.hbase.acme.attachments,59], [hdfs.hbase.acme.attachments,41], [hdfs.hbase.acme.attachments,17], [hdfs.hbase.acme.at

tachments,61]))

at org.apache.spark.streaming.kafka.DirectKafkaInputDStream.latestLeaderOffsets(DirectKafkaInputDStream.scala:123) ~[acmedsc-ingest-kafka-spark-2.0.0-SNAPSHOT.j

ar:?]

at org.apache.spark.streaming.kafka.DirectKafkaInputDStream.compute(DirectKafkaInputDStream.scala:145) ~[acmedsc-ingest-kafka-spark-2.0.0-SNAPSHOT.jar:?]

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350) ~[spark-assembly-1.5.0-hadoop2.4.0.ja

r:1.5.0]

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350) ~[spark-assembly-1.5.0-hadoop2.4.0.ja

r:1.5.0]

at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57) ~[acmedsc-ingest-kafka-spark-2.0.0-SNAPSHOT.jar:?]

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:399) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:344) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at scala.Option.orElse(Option.scala:257) ~[acmedsc-ingest-kafka-spark-2.0.0-SNAPSHOT.jar:?]

at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.dstream.MappedDStream.compute(MappedDStream.scala:35) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350) ~[spark-assembly-1.5.0-hadoop2.4.0.ja

r:1.5.0]

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350) ~[spark-assembly-1.5.0-hadoop2.4.0.ja

r:1.5.0]

at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57) ~[acmedsc-ingest-kafka-spark-2.0.0-SNAPSHOT.jar:?]

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:399) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:344) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at scala.Option.orElse(Option.scala:257) ~[acmedsc-ingest-kafka-spark-2.0.0-SNAPSHOT.jar:?]

at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.dstream.ForEachDStream.generateJob(ForEachDStream.scala:38) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:120) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:120) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251) ~[acmedsc-ingest-kafka-spark-2.0.0-SNAPSHOT.jar:?]

at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251) ~[acmedsc-ingest-kafka-spark-2.0.0-SNAPSHOT.jar:?]

at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) ~[acmedsc-ingest-kafka-spark-2.0.0-SNAPSHOT.jar:?]

at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) ~[acmedsc-ingest-kafka-spark-2.0.0-SNAPSHOT.jar:?]

at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:251) ~[acmedsc-ingest-kafka-spark-2.0.0-SNAPSHOT.jar:?]

at scala.collection.AbstractTraversable.flatMap(Traversable.scala:105) ~[acmedsc-ingest-kafka-spark-2.0.0-SNAPSHOT.jar:?]

at org.apache.spark.streaming.DStreamGraph.generateJobs(DStreamGraph.scala:120) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$2.apply(JobGenerator.scala:247) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$2.apply(JobGenerator.scala:245) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at scala.util.Try$.apply(Try.scala:161) ~[acmedsc-ingest-kafka-spark-2.0.0-SNAPSHOT.jar:?]

at org.apache.spark.streaming.scheduler.JobGenerator.generateJobs(JobGenerator.scala:245) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.scheduler.JobGenerator.org$apache$spark$streaming$scheduler$JobGenerator$$processEvent(JobGenerator.scala:181) ~[spark-assembly-1.

5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:87) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:86) ~[spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) [spark-assembly-1.5.0-hadoop2.4.0.jar:1.5.0]

Exception in thread "main" org.apache.spark.SparkException: ArrayBuffer(org.apache.spark.SparkException: Couldn't find leaders for Set([hdfs.hbase.acme.attachments,49],

[hdfs.hbase.acme.attachments,63], [hdfs.hbase.acme.attachments,31], [hdfs.hbase.acme.attachments,9], [hdfs.hbase.acme.attachments,25], [hdfs.hbase.acme.attachments,55]

, [hdfs.hbase.acme.attachments,5], [hdfs.hbase.acme.attachments,37], [hdfs.hbase.acme.attachments,7], [hdfs.hbase.acme.attachments,47], [hdfs.hbase.acme.attachments,13]

, [hdfs.hbase.acme.attachments,43], [hdfs.hbase.acme.attachments,19], [hdfs.hbase.acme.attachments,15], [hdfs.hbase.acme.attachments,23], [hdfs.hbase.acme.attachments,5

3], [hdfs.hbase.acme.attachments,1], [hdfs.hbase.acme.attachments,27], [hdfs.hbase.acme.attachments,57], [hdfs.hbase.acme.attachments,39], [hdfs.hbase.acme.attachments,

11], [hdfs.hbase.acme.attachments,29], [hdfs.hbase.acme.attachments,33], [hdfs.hbase.acme.attachments,35], [hdfs.hbase.acme.attachments,51], [hdfs.hbase.acme.attachment

s,45], [hdfs.hbase.acme.attachments,21], [hdfs.hbase.acme.attachments,3], [hdfs.hbase.acme.attachments,59], [hdfs.hbase.acme.attachments,41], [hdfs.hbase.acme.attachmen

ts,17], [hdfs.hbase.acme.attachments,61]))

at org.apache.spark.streaming.kafka.DirectKafkaInputDStream.latestLeaderOffsets(DirectKafkaInputDStream.scala:123)

at org.apache.spark.streaming.kafka.DirectKafkaInputDStream.compute(DirectKafkaInputDStream.scala:145)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)

at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)

at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:399)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:344)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342)

at scala.Option.orElse(Option.scala:257)

at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339)

at org.apache.spark.streaming.dstream.MappedDStream.compute(MappedDStream.scala:35)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)

at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)

at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:399)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:344)

at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342)

at scala.Option.orElse(Option.scala:257)

at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339)

at org.apache.spark.streaming.dstream.ForEachDStream.generateJob(ForEachDStream.scala:38)

at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:120)

at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:120)

at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)

at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)

at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)

at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)

at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:251)

at scala.collection.AbstractTraversable.flatMap(Traversable.scala:105)

at org.apache.spark.streaming.DStreamGraph.generateJobs(DStreamGraph.scala:120)

at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$2.apply(JobGenerator.scala:247)

at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$2.apply(JobGenerator.scala:245)

at scala.util.Try$.apply(Try.scala:161)

at org.apache.spark.streaming.scheduler.JobGenerator.generateJobs(JobGenerator.scala:245)

at org.apache.spark.streaming.scheduler.JobGenerator.org$apache$spark$streaming$scheduler$JobGenerator$$processEvent(JobGenerator.scala:181)

at org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:87)

at org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:86)

at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)

2019-04-23 20:36:55,265 FATAL Unable to register shutdown hook because JVM is shutting down.

[Stage 15597:=================================>                   (41 + 6) / 64]Exception in thread "streaming-job-executor-0" java.lang.Error: java.lang.InterruptedExc

eption

at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1155)

at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)

at java.lang.Thread.run(Thread.java:748)

Caused by: java.lang.InterruptedException

at java.lang.Object.wait(Native Method)

at java.lang.Object.wait(Object.java:502)

at org.apache.spark.scheduler.JobWaiter.awaitResult(JobWaiter.scala:73)

at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:559)

at org.apache.spark.SparkContext.runJob(SparkContext.scala:1813)

at org.apache.spark.SparkContext.runJob(SparkContext.scala:1826)

at org.apache.spark.SparkContext.runJob(SparkContext.scala:1839)

at org.apache.spark.SparkContext.runJob(SparkContext.scala:1910)

at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:898)

at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:896)

at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)

at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)

at org.apache.spark.rdd.RDD.withScope(RDD.scala:306)

at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:896)

at org.apache.spark.api.java.JavaRDDLike$class.foreachPartition(JavaRDDLike.scala:222)

at org.apache.spark.api.java.AbstractJavaRDDLike.foreachPartition(JavaRDDLike.scala:47)

at com.acme.consumer.kafka.spark.KafkaSparkStreamingDriver$3.call(KafkaSparkStreamingDriver.java:218)

at com.acme.consumer.kafka.spark.KafkaSparkStreamingDriver$3.call(KafkaSparkStreamingDriver.java:207)

at org.apache.spark.streaming.api.java.JavaDStreamLike$$anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:315)

at org.apache.spark.streaming.api.java.JavaDStreamLike$$anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:315)

at org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:631)

at org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:631)

at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:42)

at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:40)

at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:40)

at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:399)

at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:40)

at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:40)

at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:40)

at scala.util.Try$.apply(Try.scala:161)

at org.apache.spark.streaming.scheduler.Job.run(Job.scala:34)

at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:207)

at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:207)

at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:207)

at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)

at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:206)

at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)

... 2 more


{noformat}



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