我正在尝试配置zeppelin以使用HDP 2.3(Spark 1.3)。我已经通过Ambari成功安装了zeppelin并且zeppelin服务正在运行。
但是当我尝试运行任何%pyspark
命令时,我收到以下错误。
我读了很少的博客,但似乎在Java和Java 7上编译的jar存在一些问题,这些问题在Python和Spark之间共享。
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 4 times, most recent failure: Lost task 0.3 in stage 1.0 (TID 7, sandbox.hortonworks.com): org.apache.spark.SparkException:
Error from python worker:
/usr/bin/python: No module named pyspark
PYTHONPATH was:
/opt/incubator-zeppelin/interpreter/spark/zeppelin-spark-0.6.0-incubating-SNAPSHOT.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:105)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
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:61)
at org.apache.spark.scheduler.Task.run(Task.scala:64)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$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$$failJobAndIndependentStages(DAGScheduler.scala:1204)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1193)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1192)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1393)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1354)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
(<class 'py4j.protocol.Py4JJavaError'>, Py4JJavaError(u'An error occurred while calling z:org.apache.spark.api.python.PythonRDD.runJob.\n', JavaObject id=o68), <traceback object at 0x2618bd8>)
Took 0 seconds
答案 0 :(得分:2)
如果你有下面一行,你可以检查你的zeppelin-env.sh吗?
export PYTHONPATH=${SPARK_HOME}/python
如果缺少,可以通过Zeppelin下的Ambari添加&gt;配置&gt;高级zeppelin-env&gt; zeppelin-env模板
虽然,如果您使用最新版本的Ambari service for zeppelin安装,那么它应该为您完成此操作: https://github.com/hortonworks-gallery/ambari-zeppelin-service/blob/master/configuration/zeppelin-env.xml#L63
答案 1 :(得分:0)
我刚刚使用Ambari 2.1在Centos 6.5上设置了一个全新的HDP 2.3设置(2.3.0.0-2557),并使用Ambari zeppelin服务安装了zeppelin(使用默认配置)。 Pyspark似乎对我来说很好。
根据您的错误,听起来PYTHONPATH没有设置为正确的值:
PYTHONPATH was:
/opt/incubator-zeppelin/interpreter/spark/zeppelin-spark-0.6.0-incubating-SNAPSHOT.jar
在zeppelin中,您可以在单元格中输入以下内容并运行它并提供输出吗?
System.getenv().get("MASTER")
System.getenv().get("SPARK_YARN_JAR")
System.getenv().get("HADOOP_CONF_DIR")
System.getenv().get("JAVA_HOME")
System.getenv().get("SPARK_HOME")
System.getenv().get("PYSPARK_PYTHON")
System.getenv().get("PYTHONPATH")
System.getenv().get("ZEPPELIN_JAVA_OPTS")
以下是我的设置输出:
res41: String = yarn-client
res42: String = hdfs:///apps/zeppelin/zeppelin-spark-0.6.0-SNAPSHOT.jar
res43: String = /etc/hadoop/conf
res44: String = /usr/java/default
res45: String = /usr/hdp/current/spark-client/
res46: String = null
res47: String = /usr/hdp/current/spark-client//python:/usr/hdp/current/spark-client//python/lib/pyspark.zip:/usr/hdp/current/spark-client//python/lib/py4j-0.8.2.1-src.zip
res48: String = -Dhdp.version=2.3.0.0-2557 -Dspark.executor.memory=512m -Dspark.yarn.queue=default