Is this a bug? I can open an issue if it is.
On Wed, Sep 16, 2015, 4:51 PM Paulo Cheadi Haddad Filho <paulo...@gmail.com>
wrote:
> Actually, I've done this already, but I'd forgotten the outcome.
>
> I get "pyspark is not responding" message.
>
>
> On Wed, Sep 16, 2015 at 4:01 PM Felix Cheung <felixcheun...@hotmail.com>
> wrote:
>
>> Could you try setting zeppelin.pyspark.python in the interpreter setting
>> to the matching Python 3? "python3" in your example below.
>>
>>
>> _____________________________
>>
>> From: Paulo Cheadi Haddad Filho <paulo...@gmail.com>
>> Sent: Wednesday, September 16, 2015 9:21 AM
>> Subject: Fwd: Zeppelin error when trying to run pyspark using python3
>> To: <users@zeppelin.incubator.apache.org>
>>
>>
>> Hello,
>>
>> Yesterday I installed a Spark server with Zeppelin and, while testing in
>> a new notebook, I realized that pyspark is using Python 2.7.9. I have
>> Python 3.4.3 installed and some other things I can tell if you later.
>>
>> Looking for how to use python3, I found this post [1]. I tried setting
>> those env variables in .bashrc and zeppelin-env.sh as
>>
>> export PYSPARK_PYTHON="python3"
>>> export PYSPARK_DRIVER_PYTHON="ipython3"
>>
>>
>> When I run ./bin/pyspark I get
>>
>> paulo_filho@spark:~$ $SPARK_HOME/bin/pyspark
>>> Python 3.4.3 (default, Mar 26 2015, 22:03:40)
>>> Type "copyright", "credits" or "license" for more information.
>>> IPython 4.0.0 -- An enhanced Interactive Python.
>>> ...
>>> Welcome to
>>> ____ __
>>> / __/__ ___ _____/ /__
>>> _\ \/ _ \/ _ `/ __/ '_/
>>> /__ / .__/\_,_/_/ /_/\_\ version 1.5.0
>>> /_/
>>> Using Python version 3.4.3 (default, Mar 26 2015 22:03:40)
>>
>>
>> but Zeppelin didn't work. Instead, I got the error below:
>>
>> %pyspark
>> import sys
>> print(sys.version_info)
>>
>>> sys.version_info(major=2, minor=7, micro=9, releaselevel='final',
>>> serial=0)
>>
>>
>>
>> %pyspark
>> bankText = sc.textFile("/home/paulo_filho/data/bank.csv")
>> print(bankText.take(2))
>>
>>> 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 1 times, most recent failure: Lost task 0.0 in
>>> stage 0.0 (TID 0, localhost): org.apache.spark.api.python.PythonException:
>>> Traceback (most recent call last):
>>> File
>>> "/usr/local/spark-1.5.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/worker.py",
>>> line 64, in main
>>> ("%d.%d" % sys.version_info[:2], version))
>>> Exception: Python in worker has different version 3.4 than that in
>>> driver 2.7, PySpark cannot run with different minor versions
>>> at
>>> org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:138)
>>> at
>>> org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:179)
>>> at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:97)
>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
>>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
>>> at org.apache.spark.scheduler.Task.run(Task.scala:88)
>>> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
>>> 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$$failJobAndIndependentStages(DAGScheduler.scala:1280)
>>>
>>> at
>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1268)
>>>
>>> at
>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1267)
>>>
>>> at
>>> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
>>>
>>> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
>>> at
>>> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1267)
>>> at
>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697)
>>>
>>> at
>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697)
>>>
>>> at scala.Option.foreach(Option.scala:236)
>>> at
>>> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:697)
>>>
>>> at
>>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1493)
>>>
>>> at
>>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1455)
>>>
>>> at
>>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1444)
>>>
>>> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
>>> at
>>> org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:567)
>>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1813)
>>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1826)
>>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:1839)
>>> at org.apache.spark.api.python.PythonRDD$.runJob(PythonRDD.scala:361)
>>> at org.apache.spark.api.python.PythonRDD.runJob(PythonRDD.scala)
>>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>> at
>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
>>>
>>> at
>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>>>
>>> at java.lang.reflect.Method.invoke(Method.java:497)
>>> at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
>>> at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
>>> at py4j.Gateway.invoke(Gateway.java:259)
>>> at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
>>> at py4j.commands.CallCommand.execute(CallCommand.java:79)
>>> at py4j.GatewayConnection.run(GatewayConnection.java:207)
>>> at java.lang.Thread.run(Thread.java:745)
>>> Caused by: org.apache.spark.api.python.PythonException: Traceback (most
>>> recent call last):
>>> File
>>> "/usr/local/spark-1.5.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/worker.py",
>>> line 64, in main
>>> ("%d.%d" % sys.version_info[:2], version))
>>> Exception: Python in worker has different version 3.4 than that in
>>> driver 2.7, PySpark cannot run with different minor versions
>>> at
>>> org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:138)
>>> at
>>> org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:179)
>>> at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:97)
>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
>>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
>>> at org.apache.spark.scheduler.Task.run(Task.scala:88)
>>> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
>>> at
>>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
>>>
>>> at
>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
>>>
>>> ... 1 more
>>> (<class 'py4j.protocol.Py4JJavaError'>, Py4JJavaError(u'An error
>>> occurred while calling z:org.apache.spark.api.python.PythonRDD.runJob.\n',
>>> JavaObject id=o53), <traceback object at 0x7f814b4596c8>)
>>
>>
>> I noticed that in Zeppelin's "Interpreter" section there's a config
>>
>> zeppelin.pyspark.python python
>>>
>>
>> I've already tried to change that, but I got the same error always.
>>
>>
>> So, I'm here asking for your help. =)
>>
>> Thanks!
>>
>>
>> [1]
>> http://stackoverflow.com/questions/30518362/how-do-i-set-the-drivers-python-version-in-spark
>>
>>
>>
>>
