我刚刚在 Windows 7 机器上构建了 Spark（使用sbt），并且正在快速启动。Spark 作业在调用时失败first()。
我是 Java 新手，不清楚堆栈跟踪向我显示的错误信息，尽管它似乎与给java.net.SocketException定的消息传递有关。注意我没有使用 Hadoop 安装。另请注意，在 Scala 中运行此示例时，没有错误。
环境：
Windows 7
Spark 1.2.1
Anaconda Python 2.7.8
Scala 2.10.4
sbt 0.13.7
jdk 1.7.0.75
In [2]: path = u'C:\\Users\\striji\\Documents\\Personal\\python\\pyspark-flights\\2001.csv.bz2'
In [3]: textFile = sc.textFile(path)
In [4]: textFile
Out[4]: C:\Users\striji\Documents\Personal\python\pyspark-flights\2001.csv.bz2 MappedRDD[1] at textFile at NativeMethodAccessorImpl.java:-2
In [5]: textFile.count()
...
Out[5]: 5967781
In [6]: textFile.first()
15/02/19 08:52:01 INFO SparkContext: Starting job: runJob at PythonRDD.scala:344
15/02/19 08:52:01 INFO DAGScheduler: Got job 1 (runJob at PythonRDD.scala:344) with 1 output partitions (allowLocal=true)
15/02/19 08:52:01 INFO DAGScheduler: Final stage: Stage 1(runJob at PythonRDD.scala:344)
15/02/19 08:52:01 INFO DAGScheduler: Parents of final stage: List()
15/02/19 08:52:01 INFO DAGScheduler: Missing parents: List()
15/02/19 08:52:01 INFO DAGScheduler: Submitting Stage 1 (PythonRDD[3] at RDD at PythonRDD.scala:43), which has no missing parents
15/02/19 08:52:01 INFO MemoryStore: ensureFreeSpace(4560) called with curMem=46832, maxMem=278302556
15/02/19 08:52:01 INFO MemoryStore: Block broadcast_2 stored as values in memory (estimated size 4.5 KB, free 265.4 MB)
15/02/19 08:52:01 INFO MemoryStore: ensureFreeSpace(3417) called with curMem=51392, maxMem=278302556
15/02/19 08:52:01 INFO MemoryStore: Block broadcast_2_piece0 stored as bytes in memory (estimated size 3.3 KB, free 265.4 MB)
15/02/19 08:52:01 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on localhost:51106 (size: 3.3 KB, free: 265.4 MB)
15/02/19 08:52:01 INFO BlockManagerMaster: Updated info of block broadcast_2_piece0
15/02/19 08:52:01 INFO SparkContext: Created broadcast 2 from broadcast at DAGScheduler.scala:838
15/02/19 08:52:01 INFO DAGScheduler: Submitting 1 missing tasks from Stage 1 (PythonRDD[3] at RDD at PythonRDD.scala:43)
15/02/19 08:52:01 INFO TaskSchedulerImpl: Adding task set 1.0 with 1 tasks
15/02/19 08:52:01 INFO TaskSetManager: Starting task 0.0 in stage 1.0 (TID 1, localhost, PROCESS_LOCAL, 1341 bytes)
15/02/19 08:52:01 INFO Executor: Running task 0.0 in stage 1.0 (TID 1)
15/02/19 08:52:04 INFO HadoopRDD: Input split: file:/C:/Users/striji/Documents/Personal/python/pyspark-flights/2001.csv.bz2:0+83478700
15/02/19 08:52:04 ERROR Executor: Exception in task 0.0 in stage 1.0 (TID 1)
java.net.SocketException: Connection reset
at java.net.SocketInputStream.read(SocketInputStream.java:196)
at java.net.SocketInputStream.read(SocketInputStream.java:122)
at java.io.BufferedInputStream.fill(BufferedInputStream.java:235)
at java.io.BufferedInputStream.read(BufferedInputStream.java:254)
at java.io.DataInputStream.readInt(DataInputStream.java:387)
at org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:110)
at org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:174)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:96)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:280)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:247)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:56)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:200)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
15/02/19 08:52:05 WARN TaskSetManager: Lost task 0.0 in stage 1.0 (TID 1, localhost): java.net.SocketException: Connection reset
at java.net.SocketInputStream.read(SocketInputStream.java:196)
at java.net.SocketInputStream.read(SocketInputStream.java:122)
at java.io.BufferedInputStream.fill(BufferedInputStream.java:235)
at java.io.BufferedInputStream.read(BufferedInputStream.java:254)
at java.io.DataInputStream.readInt(DataInputStream.java:387)
at org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:110)
at org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:174)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:96)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:280)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:247)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:56)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:200)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
15/02/19 08:52:05 ERROR TaskSetManager: Task 0 in stage 1.0 failed 1 times; aborting job
15/02/19 08:52:05 INFO TaskSchedulerImpl: Removed TaskSet 1.0, whose tasks have all completed, from pool
15/02/19 08:52:05 INFO TaskSchedulerImpl: Cancelling stage 1
15/02/19 08:52:05 INFO DAGScheduler: Job 1 failed: runJob at PythonRDD.scala:344, took 3.796728 s
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<ipython-input-6-674a86098a8f> in <module>()
----> 1 textFile.first()
c:\spark-1.2.1\python\pyspark\rdd.pyc in first(self)
1137 ValueError: RDD is empty
1138 """
-> 1139 rs = self.take(1)
1140 if rs:
1141 return rs[0]
c:\spark-1.2.1\python\pyspark\rdd.pyc in take(self, num)
1119
1120 p = range(partsScanned, min(partsScanned + numPartsToTry, totalParts))
-> 1121 res = self.context.runJob(self, takeUpToNumLeft, p, True)
1122
1123 items += res
c:\spark-1.2.1\python\pyspark\context.pyc in runJob(self, rdd, partitionFunc, partitions, allowLocal)
825 # SparkContext#runJob.
826 mappedRDD = rdd.mapPartitions(partitionFunc)
--> 827 it = self._jvm.PythonRDD.runJob(self._jsc.sc(), mappedRDD._jrdd, javaPartitions, allowLocal)
828 return list(mappedRDD._collect_iterator_through_file(it))
829
c:\spark-1.2.1\python\lib\py4j-0.8.2.1-src.zip\py4j\java_gateway.py in __call__(self, *args)
536 answer = self.gateway_client.send_command(command)
537 return_value = get_return_value(answer, self.gateway_client,
--> 538 self.target_id, self.name)
539
540 for temp_arg in temp_args:
c:\spark-1.2.1\python\lib\py4j-0.8.2.1-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 z:org.apache.spark.api.python.PythonRDD.runJob.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 1 times, most recent failure: Lost task 0.0
in stage 1.0 (TID 1, localhost): java.net.SocketException: Connection reset
at java.net.SocketInputStream.read(SocketInputStream.java:196)
at java.net.SocketInputStream.read(SocketInputStream.java:122)
at java.io.BufferedInputStream.fill(BufferedInputStream.java:235)
at java.io.BufferedInputStream.read(BufferedInputStream.java:254)
at java.io.DataInputStream.readInt(DataInputStream.java:387)
at org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:110)
at org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:174)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:96)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:280)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:247)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:56)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:200)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1
214)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1203)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1202)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1202)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:696)
at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1420)
at akka.actor.Actor$class.aroundReceive(Actor.scala:465)
at org.apache.spark.scheduler.DAGSchedulerEventProcessActor.aroundReceive(DAGScheduler.scala:1375)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)
at akka.actor.ActorCell.invoke(ActorCell.scala:487)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238)
at akka.dispatch.Mailbox.run(Mailbox.scala:220)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:393)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)