Apache Spark：线程driver-heartbeater中未捕获的异常

时间：2015-11-25 10:44:10

标签： scala apache-spark apache-spark-sql spark-streaming

我在下面写了简单的火花程序，使用了Spark的StreamingContext和SQLContext。

注意：即使没有streamingContext，问题也是可重现的。更新了程序以反映相同的内容。

注意：将spark版本降级到1.4.1（我使用1.5.2）似乎已经解决了我的问题。火花也1.5.1这个问题我们可以重现。 

def main(args: Array[String]) {
    val sc = new SparkContext("local[*]", "test")
    val sqc = new SQLContext(sc)

    val dataFrame = sqc.read.json(sc.textFile("<dir>"))
    println(dataFrame.groupBy("Product.SerialNumber").count().count())
    sc.stop()
}

这在开头给出了以下异常，但执行正在进行并且打印结果。

15/11/25 15:48:55 ERROR Utils: Uncaught exception in thread driver-heartbeater
java.io.IOException: java.lang.ClassCastException: cannot assign instance of scala.collection.immutable.HashMap$SerializationProxy to field org.apache.spark.executor.TaskMetrics._accumulatorUpdates of type scala.collection.immutable.Map in instance of org.apache.spark.executor.TaskMetrics
        at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1163)
        at org.apache.spark.executor.TaskMetrics.readObject(TaskMetrics.scala:219)
        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:497)
        at java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1017)
        at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1900)
        at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
        at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
        at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
        at org.apache.spark.util.Utils$.deserialize(Utils.scala:91)
        at org.apache.spark.executor.Executor$$anonfun$org$apache$spark$executor$Executor$$reportHeartBeat$1$$anonfun$apply$6.apply(Executor.scala:440)
        at org.apache.spark.executor.Executor$$anonfun$org$apache$spark$executor$Executor$$reportHeartBeat$1$$anonfun$apply$6.apply(Executor.scala:430)
        at scala.Option.foreach(Option.scala:257)
        at org.apache.spark.executor.Executor$$anonfun$org$apache$spark$executor$Executor$$reportHeartBeat$1.apply(Executor.scala:430)
        at org.apache.spark.executor.Executor$$anonfun$org$apache$spark$executor$Executor$$reportHeartBeat$1.apply(Executor.scala:428)
        at scala.collection.Iterator$class.foreach(Iterator.scala:742)
        at scala.collection.AbstractIterator.foreach(Iterator.scala:1194)
        at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
        at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
        at org.apache.spark.executor.Executor.org$apache$spark$executor$Executor$$reportHeartBeat(Executor.scala:428)
        at org.apache.spark.executor.Executor$$anon$1$$anonfun$run$1.apply$mcV$sp(Executor.scala:472)
        at org.apache.spark.executor.Executor$$anon$1$$anonfun$run$1.apply(Executor.scala:472)
        at org.apache.spark.executor.Executor$$anon$1$$anonfun$run$1.apply(Executor.scala:472)
        at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1699)
        at org.apache.spark.executor.Executor$$anon$1.run(Executor.scala:472)
        at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
        at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:308)
        at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:180)
        at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:294)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.ClassCastException: cannot assign instance of scala.collection.immutable.HashMap$SerializationProxy to field org.apache.spark.executor.TaskMetrics._accumulatorUpdates of type scala.collection.immutable.Map in instance of org.apache.spark.executor.TaskMetrics
        at java.io.ObjectStreamClass$FieldReflector.setObjFieldValues(ObjectStreamClass.java:2089)
        at java.io.ObjectStreamClass.setObjFieldValues(ObjectStreamClass.java:1261)
        at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2006)
        at java.io.ObjectInputStream.defaultReadObject(ObjectInputStream.java:501)
        at org.apache.spark.executor.TaskMetrics$$anonfun$readObject$1.apply$mcV$sp(TaskMetrics.scala:220)
        at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1160)
        ... 33 more

2分钟后，发生以下异常并终止执行。直到两分钟，执行完美无缺，并且没有报告任何问题/异常。

15/11/25 15:51:44 WARN HeartbeatReceiver: Removing executor driver with no recent heartbeats: 179219 ms exceeds timeout 120000 ms^M
15/11/25 15:51:44 ERROR TaskSchedulerImpl: Lost executor driver on localhost: Executor heartbeat timed out after 179219 ms^M
15/11/25 15:51:44 WARN TaskSetManager: Lost task 4.0 in stage 193.0 (TID 7688, localhost): ExecutorLostFailure (executor driver lost)^M
15/11/25 15:51:44 ERROR TaskSetManager: Task 4 in stage 193.0 failed 1 times; aborting job^M
15/11/25 15:51:44 WARN TaskSetManager: Lost task 7.0 in stage 193.0 (TID 7691, localhost): ExecutorLostFailure (executor driver lost)^M
15/11/25 15:51:44 WARN TaskSetManager: Lost task 6.0 in stage 193.0 (TID 7690, localhost): ExecutorLostFailure (executor driver lost)^M
15/11/25 15:51:44 WARN TaskSetManager: Lost task 5.0 in stage 193.0 (TID 7689, localhost): ExecutorLostFailure (executor driver lost)^M
15/11/25 15:51:44 WARN SparkContext: Killing executors is only supported in coarse-grained mode^M
15/11/25 15:51:45 ERROR JobScheduler: Error running job streaming job 1448446890000 ms.0^M
org.apache.spark.SparkException: Job aborted due to stage failure: Task 4 in stage 193.0 failed 1 times, most recent failure: Lost task 4.0 in stage 193.0 (TID 7688, localhost): ExecutorLostFailure (executor driver lost)^M
Driver stacktrace:^M
        at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1283)^M
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1271)^M
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1270)^M
        at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)^M
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)^M
        at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1270)^M
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697)^M
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697)^M
        at scala.Option.foreach(Option.scala:257)^M
        at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:697)^M
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1496)^M
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1458)^M
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1447)^M
        at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)^M
        at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:567)^M
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:1824)^M
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:1837)^M
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:1850)^M
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:1921)^M
        at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:909)^M
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)^M
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)^M
        at org.apache.spark.rdd.RDD.withScope(RDD.scala:310)^M
        at org.apache.spark.rdd.RDD.collect(RDD.scala:908)^M
        at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:177)^M
        at org.apache.spark.sql.DataFrame$$anonfun$collect$1.apply(DataFrame.scala:1385)^M
        at org.apache.spark.sql.DataFrame$$anonfun$collect$1.apply(DataFrame.scala:1385)^M
        at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:56)^M
        at org.apache.spark.sql.DataFrame.withNewExecutionId(DataFrame.scala:1903)^M
        at org.apache.spark.sql.DataFrame.collect(DataFrame.scala:1384)^M
        at org.apache.spark.sql.DataFrame.count(DataFrame.scala:1402)^M
        at main$$anonfun$main$1.apply(Main.scala:72)^M
        at main$$anonfun$main$1.apply(Main.scala:68)^M
        at org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:631)^M
        at org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:631)^M
        at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:42)^M
        at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:40)^M
        at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:40)^M
        at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:399)^M
        at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:40)^M
        at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:40)^M
        at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:40)^M
        at scala.util.Try$.apply(Try.scala:192)^M
        at org.apache.spark.streaming.scheduler.Job.run(Job.scala:34)^M
        at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:218)^M
        at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:218)^M
        at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:218)^M
        at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)^M
        at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:217)^M
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)^M
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)^M
        at java.lang.Thread.run(Thread.java:745)^M
[error] (run-main-0) org.apache.spark.SparkException: Job aborted due to stage failure: Task 4 in stage 193.0 failed 1 times, most recent failure: Lost task 4.0 in stage 193.0 (TID 7688, localhost): ExecutorLostFailure (executor driver lost)^M

3 个答案:

答案 0 :(得分：2)

提交spark作业时，您可能会忘记添加一些依赖关系jar。 在将项目提交给spark之前，尝试组装项目（以便包含所有依赖项）：

sbt assembly

BTW，我跑的时候

sbt console

并在scala解释器中运行命令，我将遇到与您相同的问题。但是，如果我先组装它并通过

运行工作 
spark submit --class className target/scala-2.10/xxx-assembly-0.1.0.jar someArgs

有效：）

参考：Apache Spark 1.5 with Cassandra : Class cast exception

答案 1 :(得分：0)

尝试

val dataFrame = sqc.read.json(sc.textFile("<dir>")).cache()

我遇到了同样的问题;在同一数据帧上运行.count()次操作次数太多导致此错误。

如果这没有用，请试试这个：

val dataFrame = sqc.read.json(sc.textFile("<dir>"))
val serialNumberDF = dataFrame.groupBy("Product.SerialNumber").cache()
println(serialNumberDF.count().count())

我的猜测是不得不一遍又一遍地重新评估数据帧（因为数据帧被懒惰地评估）在某处导致了错误。此外，对于大量数据，在没有缓存的情况下，在多个位置使用数据帧可能会非常昂贵。

答案 2 :(得分：0)

在我们的案例中（Spark 1.6.1），在通过sbt运行测试时，这些相同的错误在某种程度上随机出现。问题实际上似乎是sbt issue。解决方法（在上面的链接中提到）是在分叉的jvm中运行测试：

fork in test := true

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