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?
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.
Set Env PYSPARK_PYTHON=python To Fix It.
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
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
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.
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 ?
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 :)
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.
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.
Related
This question already has answers here:
Python worker failed to connect back
(9 answers)
Closed last year.
So I've read a dozens of tutorials on how to set up pyspark.
I've set all enviremental variables like HADOOP_HOME, SPARK_HOME e.t.c.
I've downloaded winutils and put it to %SPARK_HOME%/bin.
I've checked that the version of pyspark is the same as spark, that I have downloaded from official site (3.2.1).
I am using Java JDK 8.
I've tried different versions of Java, Spark/Pyspark but everytime I use collect method on rdd I'm getting a tons of errors.
This is my sample program:
from pyspark.sql import SparkSession
ss = SparkSession.builder.master('local').appName('name').getOrCreate()
rd = ss.sparkContext.parallelize([1, 2, 3, 4, 5])
rd1 = rd.map(lambda x: x** 2).collect()
print(rd1)
And this is what I am getting. (I am sorry I have no idea how to put everything under spoiler)
Any help would be very appreciated!
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
22/02/05 21:03:53 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
22/02/05 21:04:06 WARN ProcfsMetricsGetter: Exception when trying to compute pagesize, as a result reporting of ProcessTree metrics is stopped
22/02/05 21:04:06 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:188)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:108)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:121)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:162)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(DualStackPlainSocketImpl.java:131)
at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:535)
at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:189)
at java.net.ServerSocket.implAccept(ServerSocket.java:545)
at java.net.ServerSocket.accept(ServerSocket.java:513)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:175)
... 14 more
22/02/05 21:04:06 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0) (WIN-CH4BAQ3PTMC executor driver): org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:188)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:108)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:121)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:162)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(DualStackPlainSocketImpl.java:131)
at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:535)
at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:189)
at java.net.ServerSocket.implAccept(ServerSocket.java:545)
at java.net.ServerSocket.accept(ServerSocket.java:513)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:175)
... 14 more
22/02/05 21:04:06 ERROR TaskSetManager: Task 0 in stage 0.0 failed 1 times; aborting job
Traceback (most recent call last):
File "C:\Users\user\PycharmProjects\pythonProject\spark.py", line 6, in <module>
print(rd.map(lambda x: x ** 2).collect())
File "C:\Users\user\PycharmProjects\pythonProject\venv\lib\site-packages\pyspark\rdd.py", line 950, in collect
sock_info = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
File "C:\Users\user\PycharmProjects\pythonProject\venv\lib\site-packages\py4j\java_gateway.py", line 1321, in __call__
return_value = get_return_value(
File "C:\Users\user\PycharmProjects\pythonProject\venv\lib\site-packages\pyspark\sql\utils.py", line 111, in deco
return f(*a, **kw)
File "C:\Users\user\PycharmProjects\pythonProject\venv\lib\site-packages\py4j\protocol.py", line 326, in get_return_value
raise Py4JJavaError(
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) (WIN-CH4BAQ3PTMC executor driver): org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:188)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:108)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:121)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:162)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(DualStackPlainSocketImpl.java:131)
at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:535)
at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:189)
at java.net.ServerSocket.implAccept(ServerSocket.java:545)
at java.net.ServerSocket.accept(ServerSocket.java:513)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:175)
... 14 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2454)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2403)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2402)
at scala.collection.immutable.List.foreach(List.scala:333)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2402)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1160)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1160)
at scala.Option.foreach(Option.scala:437)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1160)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2642)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2584)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2573)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:938)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2214)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2235)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2254)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2279)
at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1030)
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:414)
at org.apache.spark.rdd.RDD.collect(RDD.scala:1029)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:180)
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.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:188)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:108)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:121)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:162)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(DualStackPlainSocketImpl.java:131)
at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:535)
at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:189)
at java.net.ServerSocket.implAccept(ServerSocket.java:545)
at java.net.ServerSocket.accept(ServerSocket.java:513)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:175)
... 14 more
Nothing wrong with your program.
Its looks like the issue in your spark setup. in the command prompt check if you are able to get pyspark prompt without any error.
and also check python version and env variable.
BIG thanks to #blackbishop for the tip!
Python worker failed to connect back
All I did is just added
import findspark
findspark.init()
Everything works now!
I am setting up Spark framework.
I did put winutils.exe in C:\hadoop\bin folder and updated the binaries by editing the PATH variable. Still when I launch Spark, I get following error.
Could not locate executable null\bin\winutils.exe in the Hadoop binaries.
However, I can launch the Spark successfully despite of this above error. Please advise if the above error can cause any issues while running spark jobs.
next when I try to run wordcount.py file..get following error:
C:\python-spark\python-spark-tutorial>spark-submit rdd\WordCount.py
19/03/10 11:51:10 ERROR Shell: Failed to locate the winutils binary in the
hadoop binary path
java.io.IOException: Could not locate executable null\bin\winutils.exe in
the Hadoop binaries.
at org.apache.hadoop.util.Shell.getQualifiedBinPath(Shell.java:379)
at org.apache.hadoop.util.Shell.getWinUtilsPath(Shell.java:394)
at org.apache.hadoop.util.Shell.<clinit>(Shell.java:387)
at org.apache.hadoop.util.StringUtils.<clinit>(StringUtils.java:80)
at org.apache.hadoop.security.SecurityUtil.getAuthenticationMethod(SecurityUtil.java:611)
at org.apache.hadoop.security.UserGroupInformation.initialize(UserGroupInformation.java:273)
at org.apache.hadoop.security.UserGroupInformation.ensureInitialized(UserGroupInformation.java:261)
at org.apache.hadoop.security.UserGroupInformation.loginUserFromSubject(UserGroupInformation.java:791)
at org.apache.hadoop.security.UserGroupInformation.getLoginUser(UserGroupInformation.java:761)
at org.apache.hadoop.security.UserGroupInformation.getCurrentUser(UserGroupInformation.java:634)
at org.apache.spark.util.Utils$$anonfun$getCurrentUserName$1.apply(Utils.scala:2422)
at org.apache.spark.util.Utils$$anonfun$getCurrentUserName$1.apply(Utils.scala:2422)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.util.Utils$.getCurrentUserName(Utils.scala:2422)
at org.apache.spark.SecurityManager.<init>(SecurityManager.scala:79)
at org.apache.spark.deploy.SparkSubmit.secMgr$lzycompute$1(SparkSubmit.scala:359)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$secMgr$1(SparkSubmit.scala:359)
at org.apache.spark.deploy.SparkSubmit$$anonfun$prepareSubmitEnvironment$7.apply(SparkSubmit.scala:367)
at org.apache.spark.deploy.SparkSubmit$$anonfun$prepareSubmitEnvironment$7.apply(SparkSubmit.scala:367)
at scala.Option.map(Option.scala:146)
at org.apache.spark.deploy.SparkSubmit.prepareSubmitEnvironment(SparkSubmit.scala:366)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:143)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:86)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:924)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:933)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
19/03/10 11:51:10 WARN NativeCodeLoader: Unable to load native-hadoop
library for your platform... using builtin-java classes where applicable
Traceback (most recent call last):
File "C:\Users\gabs\AppData\Local\Programs\Python\Python37-32\lib\runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "C:\Users\gabs\AppData\Local\Programs\Python\Python37-32\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "C:\python-spark\spark-2.4.0-bin-
hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 25, in <module>
ModuleNotFoundError: No module named 'resource'
19/03/10 11:51:26 ERROR Executor: Exception in task 0.0 in stage 0.0 (TID 0)
org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:170)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:97)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:108)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$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
19/03/10 11:51:26 ERROR TaskSetManager: Task 0 in stage 0.0 failed 1 times; aborting job
Traceback (most recent call last):
File "C:/python-spark/python-spark-tutorial/rdd/WordCount.py", line 12, in <module>
wordCounts = words.countByValue()
File "C:\python-spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py", line 1261, in countByValue
File "C:\python-spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py", line 844, in reduce
File "C:\python-spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py", line 816, in collect
File "C:\python-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:\python-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
You need to set the HADOOP_HOME environment variable to C:\hadoop.
SET HADOOP_HOME=C:\hadoop
spark-submit rdd\WordCount.py
The error is mostly annoying but can disrupt things that need to use your local filesystem instead of HDFS.
I have small piece code in PySpark, but I keep getting errors. I'm new to this so im not sure where to start.
from pyspark import SparkContext, SparkConf
conf = SparkConf().setAppName("Open json").setMaster("local[3]")
sc = SparkContext(conf = conf)
print("Done")
I ran this in cmd with the command :
spark-submit .\PySpark\Open.py
I then get the following error statement:
C:\Users\Abdullah\Documents\Master Thesis>spark-submit
.\PySpark\Open.py
18/06/30 15:21:58 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-Java classes where applicable
18/06/30 15:22:01 ERROR SparkContext: Error initializing SparkContext. java.io.FileNotFoundException: File file:/C:/Users/Abdullah/Documents/Master%20Thesis/PySpark/Open.py does not exist
at org.apache.hadoop.fs.RawLocalFileSystem.deprecatedGetFileStatus(RawLocalFileSystem.java:611)
at org.apache.hadoop.fs.RawLocalFileSystem.getFileLinkStatusInternal(RawLocalFileSystem.java:824)
at org.apache.hadoop.fs.RawLocalFileSystem.getFileStatus(RawLocalFileSystem.java:601)
at org.apache.hadoop.fs.FilterFileSystem.getFileStatus(FilterFileSystem.java:421)
at org.apache.spark.SparkContext.addFile(SparkContext.scala:1529)
at org.apache.spark.SparkContext.addFile(SparkContext.scala:1499)
at org.apache.spark.SparkContext$$anonfun$13.apply(SparkContext.scala:461)
at org.apache.spark.SparkContext$$anonfun$13.apply(SparkContext.scala:461)
at scala.collection.immutable.List.foreach(List.scala:381)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:461)
at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(Unknown Source)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(Unknown Source)
at java.lang.reflect.Constructor.newInstance(Unknown Source)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:238)
at py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)
at py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Unknown Source) Traceback (most recent call last): File "C:/Users/Abdullah/Documents/Master Thesis/./PySpark/Open.py", line 12, i n <module>
sc = SparkContext(conf = conf) File "C:\apache-spark\spark-2.2.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark
\context.py", line 118, in __init__ File
"C:\apache-spark\spark-2.2.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark
\context.py", line 180, in _do_init File
"C:\apache-spark\spark-2.2.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark
\context.py", line 282, in _initialize_context File
"C:\apache-spark\spark-2.2.0-bin-hadoop2.7\python\lib\py4j-0.10.7-src.zip
\py4j\java_gateway.py", line 1525, in __call__ File
"C:\apache-spark\spark-2.2.0-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
None.org.apache.spa rk.api.java.JavaSparkContext. :
java.io.FileNotFoundException: File
file:/C:/Users/Abdullah/Documents/Master%2 0Thesis/PySpark/Open.py
does not exist
at org.apache.hadoop.fs.RawLocalFileSystem.deprecatedGetFileStatus(RawLo
calFileSystem.java:611)
at org.apache.hadoop.fs.RawLocalFileSystem.getFileLinkStatusInternal(RawLocalFileSystem.java:824)
at org.apache.hadoop.fs.RawLocalFileSystem.getFileStatus(RawLocalFileSystem.java:601)
at org.apache.hadoop.fs.FilterFileSystem.getFileStatus(FilterFileSystem.java:421)
at org.apache.spark.SparkContext.addFile(SparkContext.scala:1529)
at org.apache.spark.SparkContext.addFile(SparkContext.scala:1499)
at org.apache.spark.SparkContext$$anonfun$13.apply(SparkContext.scala:461)
at org.apache.spark.SparkContext$$anonfun$13.apply(SparkContext.scala:461)
at scala.collection.immutable.List.foreach(List.scala:381)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:461)
at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:58)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(Unknown Source)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(Unknown Source)
at java.lang.reflect.Constructor.newInstance(Unknown Source)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:247)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:238)
at py4j.commands.ConstructorCommand.invokeConstructor(ConstructorCommand.java:80)
at py4j.commands.ConstructorCommand.execute(ConstructorCommand.java:69)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Unknown Source)
As per your logs you are trying to run Apache Spark on window machine.
You need to add win util and add path in env variable
Download the executable winutils from the Hortonworks repository, or from Amazon AWS platform or github winutils.
Create a directory where you place the executable winutils.exe. For example, C:\SparkDev\x64. Add the environment variable %HADOOP_HOME% which points to this directory, then add %HADOOP_HOME%\bin to PATH.
I Started getting the following error anytime I try to collect my rdd's. It happened after I installed Java 10.1 So of course I took it out and reinstalled it, same error. I then installed Java 9.04 same error. I then ripped out python 2.7.14, apache spark 2.3.0 and Hadoop 2.7, same error. Does anyone have any one have any other reasons why I keep getting the error?
>>> from operator import add
>>> from pyspark import SparkConf, SparkContext
>>> import string
>>> import sys
>>> import re
>>>
>>> sc = SparkContext(appName="NEW")
2018-04-21 22:28:45 WARN Utils:66 - Service 'SparkUI' could not bind on port 4040. Attempting port 4041.
>>> rdd = sc.parallelize(xrange(1,10))
>>> new =rdd.collect()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "C:\spark\spark-2.3.0-bin-hadoop2.7\python\pyspark\rdd.py", line 824, in collect
port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
File "C:\spark\spark-2.3.0-bin-hadoop2.7\python\lib\py4j-0.10.6-src.zip\py4j\java_gateway.py", line 1160, in __call__
File "C:\spark\spark-2.3.0-bin-hadoop2.7\python\pyspark\sql\utils.py", line 63, in deco
return f(*a, **kw)
File "C:\spark\spark-2.3.0-bin-hadoop2.7\python\lib\py4j-0.10.6-src.zip\py4j\protocol.py", line 320, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: java.lang.IllegalArgumentException
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
at org.apache.spark.util.ClosureCleaner$.getClassReader(ClosureCleaner.scala:46)
at org.apache.spark.util.FieldAccessFinder$$anon$3$$anonfun$visitMethodInsn$2.apply(ClosureCleaner.scala:449)
at org.apache.spark.util.FieldAccessFinder$$anon$3$$anonfun$visitMethodInsn$2.apply(ClosureCleaner.scala:432)
at scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:733)
at scala.collection.mutable.HashMap$$anon$1$$anonfun$foreach$2.apply(HashMap.scala:103)
at scala.collection.mutable.HashMap$$anon$1$$anonfun$foreach$2.apply(HashMap.scala:103)
at scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:230)
at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:40)
at scala.collection.mutable.HashMap$$anon$1.foreach(HashMap.scala:103)
at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:732)
at org.apache.spark.util.FieldAccessFinder$$anon$3.visitMethodInsn(ClosureCleaner.scala:432)
at org.apache.xbean.asm5.ClassReader.a(Unknown Source)
at org.apache.xbean.asm5.ClassReader.b(Unknown Source)
at org.apache.xbean.asm5.ClassReader.accept(Unknown Source)
at org.apache.xbean.asm5.ClassReader.accept(Unknown Source)
at org.apache.spark.util.ClosureCleaner$$anonfun$org$apache$spark$util$ClosureCleaner$$clean$14.apply(ClosureCleaner.scala:262)
at org.apache.spark.util.ClosureCleaner$$anonfun$org$apache$spark$util$ClosureCleaner$$clean$14.apply(ClosureCleaner.scala:261)
at scala.collection.immutable.List.foreach(List.scala:381)
at org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:261)
at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:159)
at org.apache.spark.SparkContext.clean(SparkContext.scala:2292)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2066)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2092)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:939)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.collect(RDD.scala:938)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:153)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
at java.base/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:214)
at java.base/java.lang.Thread.run(Unknown Source)
>>> print rdd.getNumPartitions()
12
>>>
>>> print(new)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
NameError: name 'new' is not defined
>>> sc.stop()
Does anyone have any one have any other reasons why I keep getting the error?
Current Apache Spark versions don't support Java 9 or later. The support for these (or later versions) is planned for 3.0 release.
For the time being to run Spark you'll have to use JDK 8.
Source:
time for Apache Spark 3.0?
SPARK-24417 Build and Run Spark on JDK11
The issue can be resolved by updating Java to version 8, and modifying to JDK 8. The problem goes away with this configuration:
JAVA JDK: jdk-8u92-windows-x64
java version 1.8.0_181
The above is for your reference
I have been recently trying to debug the pyspark.streaming.kafka class in Pycharm so that it is easier to troubleshoot compared to working on that on the linux box.
Here is my sample code:
from pyspark import SparkContext
from pyspark.streaming import StreamingContext
from pyspark.streaming.kafka import KafkaUtils, TopicAndPartition
sc = SparkContext(appName="sample app")
ssc = StreamingContext(sc, 1)
kafkaParams = {"metadata.broker.list": "{broker list}",
"auto.offset.reset": "smallest"}
kafka_stream = KafkaUtils.createDirectStream(ssc, {topic list}, kafkaParams)
However, i got the error below:
Traceback (most recent call last):
File "C:\Program Files (x86)\JetBrains\PyCharm 5.0.3\helpers\pydev\pydevd.py", line 2411, in <module>
globals = debugger.run(setup['file'], None, None, is_module)
File "C:\Program Files (x86)\JetBrains\PyCharm 5.0.3\helpers\pydev\pydevd.py", line 1802, in run
launch(file, globals, locals) # execute the script
File "{script path}", line 30, in <module> {topic}], kafkaParams)
File "C:\spark-1.6.0-bin- hadoop2.6\python\lib\pyspark.zip\pyspark\streaming\kafka.py", line 152, in createDirectStream
py4j.protocol.Py4JJavaError: An error occurred while calling o20.loadClass.
: java.lang.ClassNotFoundException: org.apache.spark.streaming.kafka.KafkaUtilsPythonHelper
at java.net.URLClassLoader.findClass(Unknown Source)
at java.lang.ClassLoader.loadClass(Unknown Source)
at java.lang.ClassLoader.loadClass(Unknown Source)
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:231)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
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:209)
at java.lang.Thread.run(Unknown Source)
16/02/22 11:45:49 INFO SparkContext: Invoking stop() from shutdown hook
I would appreciate if someone can provide some guidance on how to debug the PySpark Kafka streaming module in PyCharm
Kafka support depends on external spark-streaming-kafka JAR which is not shipped with Spark binaries. Typically this can be specified on submit with --packages argument.
For local development using PyCharm the simplest solution I can think off is to add it to $SPARK_HOME/conf/spark-defaults.conf. Assuming you use Spark 1.6.0 built with Scala 2.10:
spark.jars.packages org.apache.spark:spark-streaming-kafka_2.10:1.6.0
Keep in mind that you won't be able to use PyCharm debugger with Python worker process. See How can pyspark be called in debug mode?