py4j.protocol.Py4JJavaError with PySpark [duplicate] - python-3.x

Question

I'm trying to complete this Spark tutorial.
After installing Spark on local machine (Win10 64, Python 3, Spark 2.4.0) and setting all env variables (HADOOP_HOME, SPARK_HOME, etc) I'm trying to run a simple WordCount.py Spark application:
from pyspark import SparkContext, SparkConf
if __name__ == "__main__":
conf = SparkConf().setAppName("word count").setMaster("local[2]")
sc = SparkContext(conf = conf)
lines = sc.textFile("C:/Users/mjdbr/Documents/BigData/python-spark-tutorial/in/word_count.text")
words = lines.flatMap(lambda line: line.split(" "))
wordCounts = words.countByValue()
for word, count in wordCounts.items():
print("{} : {}".format(word, count))
After running it from the command line:
spark-submit WordCount.py
I get below error.
I checked (by commenting out line by line) that it crashes at
wordCounts = words.countByValue()
Any idea what should I check to make it work?
Traceback (most recent call last):
File "C:\Users\mjdbr\Anaconda3\lib\runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "C:\Users\mjdbr\Anaconda3\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "C:\Spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 25, in <module>
ModuleNotFoundError: No module named 'resource'
18/11/10 23:16:58 ERROR Executor: Exception in task 0.0 in stage 0.0 (TID 0)
org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:170)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:97)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:108)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
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:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.lang.Thread.run(Unknown Source)
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(Unknown Source)
at java.net.AbstractPlainSocketImpl.accept(Unknown Source)
at java.net.PlainSocketImpl.accept(Unknown Source)
at java.net.ServerSocket.implAccept(Unknown Source)
at java.net.ServerSocket.accept(Unknown Source)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:164)
... 14 more
18/11/10 23:16:58 ERROR TaskSetManager: Task 0 in stage 0.0 failed 1 times; aborting job
Traceback (most recent call last):
File "C:/Users/mjdbr/Documents/BigData/python-spark-tutorial/rdd/WordCount.py", line 19, in <module>
wordCounts = words.countByValue()
File "C:\Spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py", line 1261, in countByValue
File "C:\Spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py", line 844, in reduce
File "C:\Spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py", line 816, in collect
File "C:\Spark\spark-2.4.0-bin-hadoop2.7\python\lib\py4j-0.10.7-src.zip\py4j\java_gateway.py", line 1257, in __call__
File "C:\Spark\spark-2.4.0-bin-hadoop2.7\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 1 times, most recent failure:
Lost task 0.0 in stage 0.0 (TID 0, localhost, executor driver): org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:170)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:97)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:108)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
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$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.lang.Thread.run(Unknown Source)
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(Unknown Source)
at java.net.AbstractPlainSocketImpl.accept(Unknown Source)
at java.net.PlainSocketImpl.accept(Unknown Source)
at java.net.ServerSocket.implAccept(Unknown Source)
at java.net.ServerSocket.accept(Unknown Source)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:164)
... 14 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1887)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1875)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1874)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1874)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2108)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2057)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2046)
at org.apache.spark.util.EventLoop$$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$$anonfun$collect$1.apply(RDD.scala:945)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.collect(RDD.scala:944)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:166)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
at java.lang.reflect.Method.invoke(Unknown Source)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Unknown Source)
Caused by: org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:170)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:97)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:108)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
... 1 more
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(Unknown Source)
at java.net.AbstractPlainSocketImpl.accept(Unknown Source)
at java.net.PlainSocketImpl.accept(Unknown Source)
at java.net.ServerSocket.implAccept(Unknown Source)
at java.net.ServerSocket.accept(Unknown Source)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:164)
... 14 more
As suggested by theplatypus - checked if the 'resource' module can be imported directly from terminal - apparently not:
>>> import resource
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ModuleNotFoundError: No module named 'resource'
In terms of installation resources - I followed instructions from this tutorial:
downloaded spark-2.4.0-bin-hadoop2.7.tgz from Apache Spark website
un-zipped it to my C-drive
already had Python_3 installed (Anaconda distribution) as well as Java
created local 'C:\hadoop\bin' folder to store winutils.exe
created 'C:\tmp\hive' folder and gave Spark access to it
added environment variables (SPARK_HOME, HADOOP_HOME etc)
Is there any extra resource I should install?

Answer 1

I got the same error. I solved it installing the previous version of Spark (2.3 instead of 2.4). Now it works perfectly, maybe it is an issue of the lastest version of pyspark.

Answer 2

Set Env PYSPARK_PYTHON=python To Fix It.

Answer 3

The heart of the problem is the connection between pyspark and python, solved by redefining the environment variable.
I´ve just changed the environment variable's values PYSPARK_DRIVER_PYTHON from ipython to jupyter and PYSPARK_PYTHON from python3 to python.
Now I'm using Jupyter Notebook, Python 3.7, Java JDK 11.0.6, Spark 2.4.2

Answer 4

I had the same issue. I had set all the environment variables correctly but still wasn't able to resolve it
In my case,
import findspark
findspark.init()
adding this before even creating the sparkSession helped.
I was using Visual Studio Code on Windows 10 and spark version was 3.2.0. Python version is 3.9 .
Note: Initially check if the paths for HADOOP_HOME SPARK_HOME PYSPARK_PYTHON have been set correctly

Answer 5

Downgrading Spark back to 2.3.2 from 2.4.0 was not enough for me. I don't know why but in my case I had to create SparkContext from SparkSession like
sc = spark.sparkContext
Then the very same error disappeared.

Answer 6

Looking at the source of the error (worker.py#L25), it seems that the python interpreter used to instanciate a pyspark worker doesn't have access to the resource module, a built-in module referred in Python's doc as part of "Unix Specific Services".
Are you sure you can run pyspark on Windows (without some additional software like GOW or MingW at least), and so that you didn't skip some Windows-specific installation steps ?
Could you open a python console (the one used by pyspark) and see if you can >>> import resource without getting the same ModuleNotFoundError ? If you don't, then could you provide the ressources you used to install it on W10 ?

Answer 7

When you run the python installer, on the Customize Python section, make sure that the option Add python.exe to Path is selected. If this option is not selected, some of the PySpark utilities such as pyspark and spark-submit might not work. This worked for me! Happy Sharing :)

Answer 8

There seems to be many reasons for this error to occur. I still had the same problem despite my environmental variables being all correctly set.
In my case adding this
import findspark
findspark.init()
solved the problem.
I'am withjupyter notebook on windows10 with spark-3.1.2, python3.6.

Answer 9

I had to set:
HADOOP_HOME = [..]\winutils\hadoop-3.0.0
PATH = [..]\winutils\hadoop-3.0.0\bin
PYSPARK_PYTHON = python
You can find winutils here. I use Hadoop 3.0.0 and PySpark 3.2.1.