I am trying to  transport a python environment with a  PySpark according to:   https://community.cloudera.com/t5/Community-Articles/Running-PySpark-with-Conda-Env/ta-p/247551 https://henning.kropponline.de/2014/07/18/virtualenv-hadoop-streaming/ https://community.cloudera.com/t5/Community-Articles/Using-VirtualEnv-with-PySpark/ta-p/245932   Last try I issued the following commands:       #Creating my relocatable environment: conda create -y -n py35 python=3.5 numpy pandas scikit-learn conda activate py35 cd /opt/cloudera/parcels/Anaconda/envs/ zip -r py35.zip py35 #Runing the job: PYSPARK_DRIVER_PYTHON=/opt/cloudera/parcels/Anaconda/envs/py35/bin/python \ PYSPARK_PYTHON=/opt/cloudera/parcels/Anaconda/envs/py35/bin/python \ pyspark2 \ --conf spark.yarn.appMasterEnv.PYSPARK_PYTHON=/opt/cloudera/parcels/Anaconda/envs/py35/bin/python \ --master yarn \ --deploy-mode client \ --archives /opt/cloudera/parcels/Anaconda/envs/py35.zip#py35 test.py       test.py:       #!./py35/bin/python # -*- coding: utf-8 -*- from pyspark import SparkConf from pyspark import SparkContext conf = SparkConf() conf.setAppName('spark-yarn') sc = SparkContext(conf=conf) def some_function(x): # Packages are imported and available from your bundled environment. import sklearn import pandas import numpy as np # Use the libraries to do work return np.sin(x)**2 + 2 rdd = (sc.parallelize(range(1000)) .map(some_function) .take(10)) print(rdd)         The unexpected result: Exception: Python in worker has different version 2.7 than that in driver 3.7, PySpark cannot run with different minor versions.Please check environment variables PYSPARK_PYTHON and PYSPARK_DRIVER_PYTHON are correctly set. Full log:       21/04/12 18:23:17 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, server, executor 1): org.apache.spark.api.python.PythonException: Traceback (most recent call last): File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/pyspark/worker.py", line 267, in main ("%d.%d" % sys.version_info[:2], version)) Exception: Python in worker has different version 2.7 than that in driver 3.7, PySpark cannot run with different minor versions.Please check environment variables PYSPARK_PYTHON and PYSPARK_DRIVER_PYTHON are correctly set. at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:452) at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:588) at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:571) at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:406) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at scala.collection.Iterator$class.foreach(Iterator.scala:891) at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28) at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59) at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104) at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48) at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310) at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28) at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302) at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28) at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289) at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28) at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:945) at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:945) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2101) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2101) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:121) at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1405) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) 21/04/12 18:23:17 ERROR scheduler.TaskSetManager: Task 0 in stage 0.0 failed 4 times; aborting job Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/pyspark/rdd.py", line 1055, in count return self.mapPartitions(lambda i: [sum(1 for _ in i)]).sum() File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/pyspark/rdd.py", line 1046, in sum return self.mapPartitions(lambda x: [sum(x)]).fold(0, operator.add) File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/pyspark/rdd.py", line 917, in fold vals = self.mapPartitions(func).collect() File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/pyspark/rdd.py", line 816, in collect sock_info = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd()) File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__ File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/pyspark/sql/utils.py", line 63, in deco return f(*a, **kw) File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe. : 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, server, executor 1): org.apache.spark.api.python.PythonException: Traceback (most recent call last): File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/pyspark/worker.py", line 267, in main ("%d.%d" % sys.version_info[:2], version)) Exception: Python in worker has different version 2.7 than that in driver 3.7, PySpark cannot run with different minor versions.Please check environment variables PYSPARK_PYTHON and PYSPARK_DRIVER_PYTHON are correctly set. at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:452) at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:588) at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:571) at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:406) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at scala.collection.Iterator$class.foreach(Iterator.scala:891) at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28) at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59) at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104) at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48) at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310) at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28) at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302) at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28) at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289) at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28) at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:945) at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:945) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2101) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2101) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:121) at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1405) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1889) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1877) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1876) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1876) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926) at scala.Option.foreach(Option.scala:257) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2110) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2059) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2048) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2126) at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:945) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) at org.apache.spark.rdd.RDD.withScope(RDD.scala:363) at org.apache.spark.rdd.RDD.collect(RDD.scala:944) at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:166) at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) at py4j.Gateway.invoke(Gateway.java:282) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.GatewayConnection.run(GatewayConnection.java:238) at java.lang.Thread.run(Thread.java:748) Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last): File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/pyspark/worker.py", line 267, in main ("%d.%d" % sys.version_info[:2], version)) Exception: Python in worker has different version 2.7 than that in driver 3.7, PySpark cannot run with different minor versions.Please check environment variables PYSPARK_PYTHON and PYSPARK_DRIVER_PYTHON are correctly set. at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:452) at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:588) at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:571) at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:406) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at scala.collection.Iterator$class.foreach(Iterator.scala:891) at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28) at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59) at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104) at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48) at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310) at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28) at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302) at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28) at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289) at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28) at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:945) at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:945) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2101) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2101) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:121) at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1405) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) ... 1 more       I’m running Spark 2.4.0,  Base python is 2.7.16 GCC 7.3.0 / OL6 CDH5.13.3 - Yes it's old.. Any Ideas would be appreciated. ... View more