长时间运行的Streaming应用程序中出现"java.io.IOException:Class not found"

Question

我在长期运行的Spark Streaming应用程序中获得了以下异常.异常可能在几分钟后发生,但也可能不会发生几天.这是非常一致的输入数据.

我见过这张Jira票,但我不认为这是同一个问题.就是java.lang.IllegalArgumentException这样java.io.IOException: Class not found.

我的应用程序是流数据并使用Spark SQL写入Parquet.

我正在使用Spark 1.5.2.有任何想法吗？

28-01-2016 09:36:00 ERROR JobScheduler:96 - Error generating jobs for time 1453973760000 ms
java.io.IOException: Class not found
        at com.esotericsoftware.reflectasm.shaded.org.objectweb.asm.ClassReader.a(Unknown Source)
        at com.esotericsoftware.reflectasm.shaded.org.objectweb.asm.ClassReader.<init>(Unknown Source)
        at org.apache.spark.util.ClosureCleaner$.getClassReader(ClosureCleaner.scala:40)
        at org.apache.spark.util.ClosureCleaner$.getInnerClosureClasses(ClosureCleaner.scala:81)
        at org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:187)
        at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:122)
        at org.apache.spark.SparkContext.clean(SparkContext.scala:2032)
        at org.apache.spark.rdd.RDD$$anonfun$map$1.apply(RDD.scala:318)
        at org.apache.spark.rdd.RDD$$anonfun$map$1.apply(RDD.scala:317)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
        at org.apache.spark.rdd.RDD.withScope(RDD.scala:310)
        at org.apache.spark.rdd.RDD.map(RDD.scala:317)
        at org.apache.spark.streaming.dstream.MappedDStream$$anonfun$compute$1.apply(MappedDStream.scala:35)
        at org.apache.spark.streaming.dstream.MappedDStream$$anonfun$compute$1.apply(MappedDStream.scala:35)
        at scala.Option.map(Option.scala:145)
        at org.apache.spark.streaming.dstream.MappedDStream.compute(MappedDStream.scala:35)
        at org.apache.spark.streaming.dstream.DStream$$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$$anonfun$getOrCompute$1.apply(DStream.scala:342)
        at scala.Option.orElse(Option.scala:257)
        at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339)
        at org.apache.spark.streaming.dstream.FilteredDStream.compute(FilteredDStream.scala:35)
        at org.apache.spark.streaming.dstream.DStream$$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$$anonfun$getOrCompute$1.apply(DStream.scala:342)
        at scala.Option.orElse(Option.scala:257)
        at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339)
        at org.apache.spark.streaming.dstream.MappedDStream.compute(MappedDStream.scala:35)
        at org.apache.spark.streaming.dstream.DStream$$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)

Answer 1

我将发布我自己的问题的答案。我认为当您启动流应用程序，然后删除或替换 Spark-Submit 中使用的 jar 文件时，就会发生这种情况。正在运行的 JVM Spark Driver 应用程序很可能会尝试从不再存在或已被替换的 jar 文件中加载某些类。

我不知道这是真的，但我看到有人对这个问题感兴趣，所以我认为最好发表我目前的想法。