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https://issues.apache.org/jira/browse/SPARK-5051?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14293190#comment-14293190
 ] 

naveen kumar commented on SPARK-5051:
-------------------------------------

Yes i have installed python on that location and file exists on the same
location

​​
And i am executing the commands from Windows machine. Will spark support
that?

-Naveen

On Sat, Jan 24, 2015 at 6:06 AM, Sven Krasser (JIRA) <j...@apache.org>



> python: module pyspark.daemon not found
> ---------------------------------------
>
>                 Key: SPARK-5051
>                 URL: https://issues.apache.org/jira/browse/SPARK-5051
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 1.2.0
>            Reporter: naveen kumar
>
> Hi,
> I am using spark 1.2 jar. I set up a 2 node spark cluster on unix machines
> Now i am trying to connect to above mentioned cluster and execute the 
> following commands 
> lines = sc.textFile("hdfs://master/data/spark/SINGLE.TXT")
> lineLengths = lines.map(lambda s: len(s))
> totalLength = lineLengths.reduce(lambda a, b: a + b)
> It is giving following exception
> Please help me to resolve this issue.
> python: module pyspark.daemon not found
> PYTHONPATH was:
>   
> /home/npokala/data/spark-install/spark-java-1.6/spark-master/python:/home/npokala/data/spark-install/spark-java-1.6/spark-master/python/lib/py4j-0.8.2.1-src.zip:/home/npokala/data/spark-install/spark-java-1.6/spark-master/assembly/target/scala-2.10/spark-assembly-1.3.0-SNAPSHOT-hadoop2.4.0.jar:/home/npokala/data/spark-install/spark-java-1.6/spark-master/sbin/../python/lib/py4j-0.8.2.1-src.zip:/home/npokala/data/spark-install/spark-java-1.6/spark-master/sbin/../python:
> java.io.EOFException
>         at java.io.DataInputStream.readInt(DataInputStream.java:392)
>         at 
> org.apache.spark.api.python.PythonWorkerFactory.startDaemon(PythonWorkerFactory.scala:163)
>         at 
> org.apache.spark.api.python.PythonWorkerFactory.createThroughDaemon(PythonWorkerFactory.scala:86)
>         at 
> org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:62)
>         at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:102)
>         at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
>         at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:265)
>         at org.apache.spark.rdd.RDD.iterator(RDD.scala:232)
>         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$TaskRunner.run(Executor.scala:196)
>         at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
>         at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
>         at java.lang.Thread.run(Thread.java:745)
> Driver stacktrace:
>         at 
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1214)
>         at 
> org.apache.spark.scheduler.DAGScheduler$$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)



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