来自python worker的错误:/ bin/python:没有名为pyspark的模块

我正在尝试使用ipython建立一个漂亮的spark开发环境.首先启动ipython,然后:

import findspark
findspark.init()

from pyspark.conf import SparkConf
from pyspark.context import SparkContext
conf = SparkConf()
conf.setMaster('yarn-client')
sc = SparkContext(conf=conf)

这是来自应用程序UI,我可以看到执行程序在工作节点上.

但是,当我尝试这个:

rdd = sc.textFile("/LOGS/201511/*/*")
rdd.first()

我明白了:

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 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3, d142.dtvhadooptest.com): org.apache.spark.SparkException:
Error from python worker:
  /bin/python: No module named pyspark
PYTHONPATH was:
  /data/sdb/hadoop/yarn/local/usercache/hdfs/filecache/64/spark-assembly-1.4.1.2.3.2.0-2950-hadoop2.7.1.2.3.2.0-2950.jar
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:130)
        at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:73)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:63)
        at org.apache.spark.scheduler.Task.run(Task.scala:70)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at java.util.concurrent.ThreadPoolExecutor$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$$failJobAndIndependentStages(DAGScheduler.scala:1273)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1264)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1263)
        at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
        at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1263)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730)
        at scala.Option.foreach(Option.scala:236)
        at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:730)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1457)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1418)
        at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)

谁能帮我吗？

因此,设置这两个额外配置就可以了.

conf.set('spark.yarn.dist.files','file:/usr/hdp/2.3.2.0-2950/spark/python/lib/pyspark.zip,file:/usr/hdp/2.3.2.0-2950/spark/python/lib/py4j-0.8.2.1-src.zip')
conf.setExecutorEnv('PYTHONPATH','pyspark.zip:py4j-0.8.2.1-src.zip')