我有一个从地图获取的RDD对象（出价），然后我只做一个简单的bid.count（）。然后我收到以下错误。有人能告诉我这个错误可能是什么吗？我试着谷歌意味着什么，但没有得到答案。
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<ipython-input-10-0283df3b1938> in <module>()
----> 1 bid.count()
/home/username/spark-1.0.0-bin-hadoop2/python/pyspark/rdd.pyc in count(self)
706 3
707 """
--> 708 return self.mapPartitions(lambda i: [sum(1 for _ in i)]).sum()
709
710 def stats(self):
/home/username/spark-1.0.0-bin-hadoop2/python/pyspark/rdd.pyc in sum(self)
697 6.0
698 """
--> 699 return self.mapPartitions(lambda x: [sum(x)]).reduce(operator.add)
700
701 def count(self):
/home/username/spark-1.0.0-bin-hadoop2/python/pyspark/rdd.pyc in reduce(self, f)
617 if acc is not None:
618 yield acc
--> 619 vals = self.mapPartitions(func).collect()
620 return reduce(f, vals)
621
/home/username/spark-1.0.0-bin-hadoop2/python/pyspark/rdd.pyc in collect(self)
581 """
582 with _JavaStackTrace(self.context) as st:
--> 583 bytesInJava = self._jrdd.collect().iterator()
584 return list(self._collect_iterator_through_file(bytesInJava))
585
/home/username/spark-1.0.0-bin-hadoop2/python/lib/py4j-0.8.1-src.zip/py4j/java_gateway.py in __call__(self, *args)
535 answer = self.gateway_client.send_command(command)
536 return_value = get_return_value(answer, self.gateway_client,
--> 537 self.target_id, self.name)
538
539 for temp_arg in temp_args:
/home/username/spark-1.0.0-bin-hadoop2/python/lib/py4j-0.8.1-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
298 raise Py4JJavaError(
299 'An error occurred while calling {0}{1}{2}.\n'.
--> 300 format(target_id, '.', name), value)
301 else:
302 raise Py4JError(
Py4JJavaError: An error occurred while calling o148.collect.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 1.0:9 failed 4 times, most recent failure: TID 7 on host 08.bm-hadoope-datanode.dev.lax1 failed for unknown reason
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1033)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1017)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1015)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1015)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:633)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:633)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:633)
at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1207)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
然后我将bid表与另一个表一起加入，然后获得一个新的RDD。它看起来很顺利，但是当我为这个新的RDD做第一个（）时。我收到以下错误：
Py4JJavaError: An error occurred while calling o274.collectPartitions.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 9.0:6 failed 4 times, most recent failure: Exception failure in TID 32 on host 05.bm-hadoope-datanode.dev.lax1: java.io.IOException: Filesystem closed
org.apache.hadoop.hdfs.DFSClient.checkOpen(DFSClient.java:629)
org.apache.hadoop.hdfs.DFSInputStream.readWithStrategy(DFSInputStream.java:735)
org.apache.hadoop.hdfs.DFSInputStream.read(DFSInputStream.java:793)
java.io.DataInputStream.readFully(DataInputStream.java:195)
java.io.DataInputStream.readFully(DataInputStream.java:169)
parquet.hadoop.ParquetFileReader$ConsecutiveChunkList.readAll(ParquetFileReader.java:599)
parquet.hadoop.ParquetFileReader.readNextRowGroup(ParquetFileReader.java:360)
parquet.hadoop.InternalParquetRecordReader.checkRead(InternalParquetRecordReader.java:100)
parquet.hadoop.InternalParquetRecordReader.nextKeyValue(InternalParquetRecordReader.java:172)
parquet.hadoop.ParquetRecordReader.nextKeyValue(ParquetRecordReader.java:130)
org.apache.spark.rdd.NewHadoopRDD$$anon$1.hasNext(NewHadoopRDD.scala:122)
org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
org.apache.spark.api.python.PythonRDD$.writeIteratorToStream(PythonRDD.scala:293)
org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply$mcV$sp(PythonRDD.scala:200)
org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:175)
org.apache.spark.api.python.PythonRDD$WriterThread$$anonfun$run$1.apply(PythonRDD.scala:175)
org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1160)
org.apache.spark.api.python.PythonRDD$WriterThread.run(PythonRDD.scala:174)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1033)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1017)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1015)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1015)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:633)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:633)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:633)
at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1207)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)