py4jjavaerror pyspark jupyter

github.com › jupyterlab › jupyterlab › issues › 17484

Error (Py4JJavaError) running pyspark notebook in VSC · Issue #17484 · jupyterlab/jupyterlab

April 17, 2025 - When I execute the last line I get an error, which is the following error: --------------------------------------------------------------------------- Py4JJavaError Traceback (most recent call last) Cell In[10], line 1 ----> 1 df.filter(col('doc_entry')==8253).orderBy(col('line_num'),ascending=True).show(30,False) File c:\ProgramData\miniforge3\Lib\site-packages\pyspark\sql\dataframe.py:947, in DataFrame.show(self, n, truncate, vertical) 887 def show(self, n: int = 20, truncate: Union[bool, int] = True, vertical: bool = False) -> None: 888 """Prints the first ``n`` rows to the console.

Author fcarub

Apache JIRA

issues.apache.org › jira › browse › SPARK-24612

[SPARK-24612] Running into "Py4JJavaError" while converting list to Dataframe using Pyspark, Jupyter notebook - ASF JIRA

December 12, 2019 - >java -version java version "1.8.0_144" Java(TM) SE Runtime Environment (build 1.8.0_144-b01) Java HotSpot(TM) 64-Bit Server VM (build 25.144-b01, mixed mode) >jupyter --version 4.4.0 >conda -V conda 4.5.4 spark-2.3.0-bin-hadoop2.7 SparkContext Spark UI Version v2.3.1 Master local [*] AppName PySparkShell · rdd=sc.parallelize([[1, "Alice", 50],[2,'Amanda','35']]) rdd.collect() [[1, 'Alice', 50], [2, 'Amanda', '35']] However, when i run df=rdd.toDF() i run into the following error: Any help resolving this error is greatly appreciated. -----------------------------------------------------------

Discussions

apache spark - Py4JJavaError when testing Pyspark in Jupyter notebook on a single machine - Stack Overflow

I am new to Spark and recently installed it on a mac (with Python 2.7 in the system) using homebrew: brew install apache-spark and then installed Pyspark using pip3 in my virtual environment where I More on stackoverflow.com

stackoverflow.com

April 4, 2021

python - PySpark in iPython notebook raises Py4JJavaError when using count() and first() - Stack Overflow

I am using PySpark(v.2.1.0) in iPython notebook (python v.3.6) over virtualenv in my Mac(Sierra 10.12.3 Beta). 1.I launched iPython notebook by shooting this in Terminal - PYSPARK_PYTHON=python3 More on stackoverflow.com

stackoverflow.com

python - Py4J error when creating a spark dataframe using pyspark - Stack Overflow

I had the same issue and this worked for me. Oddly enough, it worked with different versions of Spark and PySpark, but after a restart of JupyterLab, it stopped working, until I ensured that PySpark had the same version as Spark. More on stackoverflow.com

stackoverflow.com

Py4JJavaError: An error occurred while calling lemmatizer = LemmatizerModel.pretrained()

Hi, I am new to spark-nlp. As my first project, I tried to replicate the analysis here: https://towardsdatascience.com/natural-language-processing-with-pyspark-and-spark-nlp-b5b29f8faba. I was able to set up Spark, following the instruct... More on github.com

github.com

July 5, 2021

Apache

spark.apache.org › docs › latest › api › python › development › debugging.html

Debugging PySpark — PySpark 4.1.1 documentation

... Py4JError is raised when any other error occurs such as when the Python client program tries to access an object that no longer exists on the Java side. ... >>> from pyspark.ml.linalg import Vectors >>> from pyspark.ml.regression import LinearRegression >>> df = spark.createDataFrame( ...

stackoverflow.com › questions › 65385569 › py4jjavaerror-when-testing-pyspark-in-jupyter-notebook-on-a-single-machine

apache spark - Py4JJavaError when testing Pyspark in Jupyter notebook on a single machine - Stack Overflow

April 4, 2021 - When I ran the code below in my Jupyter Notebook to test if Spark functions on a single machine: from pyspark.context import SparkContext sc = SparkContext.getOrCreate() import random num_samples = 100000000 def inside(p): x, y = random.random(), random.random() return x*x + y*y < 1 count = sc.parallelize(range(0, num_samples)).filter(inside).count() pi = 4 * count / num_samples print(pi) sc.stop() I ran into the following error with sc.parallelize: Py4JJavaError Traceback (most recent call last) <ipython-input-3-482026ac7386> in <module> 8 return x*x + y*y < 1 9 ---> 10 count = sc.parallelize

stackoverflow.com › questions › 41840296 › pyspark-in-ipython-notebook-raises-py4jjavaerror-when-using-count-and-first

python - PySpark in iPython notebook raises Py4JJavaError when using count() and first() - Stack Overflow

sparkbyexamples.com › home › pyspark › solved: py4j.protocol.py4jerror: org.apache.spark.api.python.pythonutils.getencryptionenabled does not exist in the jvm

1 of 4

conda install -c cyclus java-jdk

https://anaconda.org/cyclus/java-jdk

2 of 4

Pyspark 2.1.0 is not compatible with python 3.6, see https://issues.apache.org/jira/browse/SPARK-19019.

You need to use earlier python version or you can try building master or 2.1 branch from github and it should work.

Spark By {Examples}

SOLVED: py4j.protocol.Py4JError: org.apache.spark.api.python.PythonUtils.getEncryptionEnabled does not exist in the JVM - Spark By {Examples}

March 27, 2024 - Sometimes after changing/upgrading the Spark version, you may get this error due to the version incompatible between pyspark version and pyspark available at anaconda lib.

stackoverflow.com › questions › 49063058 › py4j-error-when-creating-a-spark-dataframe-using-pyspark

python - Py4J error when creating a spark dataframe using pyspark - Stack Overflow

1 of 11

I am happy now because I have been having exactly the same issue with my pyspark and I found "the solution". In my case, I am running on Windows 10. After many searches via Google, I found the correct way of setting the required environment variables: PYTHONPATH=$SPARK_HOME$\python;$SPARK_HOME$\python\lib\py4j-<version>-src.zip The version of Py4J source package changes between the Spark versions, thus, check what you have in your Spark and change the placeholder accordingly. For a complete reference to the process look at this site: how to install spark locally

2 of 11

For me

import findspark
findspark.init()

import pyspark

solved the problem

github.com › JohnSnowLabs › spark-nlp › issues › 5774

Py4JJavaError: An error occurred while calling lemmatizer = LemmatizerModel.pretrained() · Issue #5774 · JohnSnowLabs/spark-nlp

July 5, 2021 - --------------------------------------------------------------------------- Py4JJavaError Traceback (most recent call last) <ipython-input-21-60e5ca4666d8> in <module> ----> 1 lemmatizer = LemmatizerModel().load("lemma_nl_2.5.0_2.4_1588532720582")\ 2 .setInputCols(['normalized']) \ 3 .setOutputCol('lemma') ~\miniconda3\envs\nlpspark\lib\site-packages\pyspark\ml\util.py in load(cls, path) 330 def load(cls, path): 331 """Reads an ML instance from the input path, a shortcut of `read().load(path)`.""" --> 332 return cls.read().load(path) 333 334 ~\miniconda3\envs\nlpspark\lib\site-packages\pyspark

Author dkaenzig

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Wikimedia Phabricator

phabricator.wikimedia.org › T256997

T256997 PySpark Error in JupyterHub: Python in worker has different version

elukey edited projects, added Analytics-Clusters; removed Analytics, Jupyter-Hub.Jul 10 2020, 6:10 AM2020-07-10 06:10:04 (UTC+0) diego added a comment.Jul 10 2020, 10:46 AM2020-07-10 10:46:23 (UTC+0)Comment Actions · @elukey apparently no changes (I've restarted the server), I'm getting this error: Py4JJavaError: An error occurred while calling o75.count.

stackoverflow.com › questions › 49742065 › py4jjavaerror-in-spark-wordcount-python-3-5-on-jupyter-notebook

Py4JJavaError in spark wordcount python 3.5 on jupyter notebook - Stack Overflow

PySpark Error: Py4JJavaError For Python version being incorrect - YouTube

1 of 2

Are you using standalone spark?

Your error is : Exception: Python in worker has different version 2.7 than that in driver 3.5, PySpark cannot run with different minor versions.Please check environment variables PYSPARK_PYTHON and PYSPARK_DRIVER_PYTHON are correctly set.

Your error has been addressed here : How do I set the driver's python version in spark?

2 of 2

UPDATE THE SPARK ENVIRONMENT TO USE PYTHON 3.7:

Open a new terminal and type the following command: export PYSPARK_PYTHON=python3.7 This will ensure that the worker nodes use Python 3.7 (same as the Driver) and not the default Python 3.4

DEPENDING ON VERSIONS OF PYTHON YOU HAVE, YOU MAY HAVE TO DO SOME INSTALL/UPDATE ANACONDA:

(To install see: https://www.digitalocean.com/community/tutorials/how-to-install-anaconda-on-ubuntu-18-04-quickstart)

Make sure you have anaconda 4.1.0 or higher. Open a new terminal and check your conda version by typing into a new terminal:

conda --version

checking conda version

if you are below anaconda 4.1.0, type conda update conda

Next we check to see if we have the library nb_conda_kernels by typing

conda list

Checking if we have nb_conda_kernels

If you don’t see nb_conda_kernels type

conda install nb_conda_kernels

Installing nb_conda_kernels

If you are using Python 2 and want a separate Python 3 environment please type the following

conda create -n py36 python=3.6 ipykernel

py35 is the name of the environment. You could literally name it anything you want.

Alternatively, If you are using Python 3 and want a separate Python 2 environment, you could type the following.

conda create -n py27 python=2.7 ipykernel

py27 is the name of the environment. It uses python 2.7.

Ensure the versions of python are installed successfully and close the terminal. Open a new terminal and type pyspark. You should see the new environments appearing.

YouTube

youtube.com › watch

05:46

Advance note: Audio was bad because I was traveling. haha_____The error in my case was: PySpark was running python 2.7 from my environment's default library....

Published October 10, 2018

stackoverflow.com › questions › 69644114 › pyspark-py4jjavaerror

python - Pyspark Py4JJavaError: - Stack Overflow

from pyspark import SparkContext, SparkConf conf = SparkConf().setAppName("Collinear Points") sc = SparkContext('local',conf=conf) from pyspark.rdd import RDD numbRDD=sc.parallelize([1,2,3,4,5,-1,-4,-6]) # Create map() transformation to cube numbers cubedRDD = numbRDD.map(lambda x: x**3) # Collect the results numbers_all = cubedRDD.collect() I get the following error. Could you please give any hints that would fix it? ... Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.

reddit.com › r/apachespark › running pyspark gives py4jjavaerror

r/apachespark on Reddit: Running pyspark gives Py4JJavaError

October 19, 2024 -

Hi All, i just installed Pyspark in my laptop and im facing this error while trying to run the below code, These are my envionment variables:

HADOOP_HOME = C:\Programs\hadoop

JAVA_HOME = C:\Programs\Java

PYSPARK_DRIVER_PYTHON = C:\Users\Asus\AppData\Local\Programs\Python\Python313\python.exe

PYSPARK_HOME = C:\Users\Asus\AppData\Local\Programs\Python\Python313\python.exe

PYSPARK_PYTHON = C:\Users\Asus\AppData\Local\Programs\Python\Python313\python.exe

SPARK_HOME = C:\Programs\Spark

from pyspark.sql import SparkSession

spark = SparkSession.builder.master("local").appName("PySpark Installation Test").getOrCreate()
df = spark.createDataFrame([(1, "Hello"), (2, "World")], ["id", "message"])
df.show()

Error logs:

Py4JJavaError                             Traceback (most recent call last)
Cell In[1], line 5
      3 spark = SparkSession.builder.master("local").appName("PySpark Installation Test").getOrCreate()
      4 df = spark.createDataFrame([(1, "Hello"), (2, "World")], ["id", "message"])
----> 5 df.show()

File , in DataFrame.show(self, n, truncate, vertical)
    887 def show(self, n: int = 20, truncate: Union[bool, int] = True, vertical: bool = False) -> None:
    888     """Prints the first ``n`` rows to the console.
    889 
    890     .. versionadded:: 1.3.0
   (...)
    945     name | Bob
    946     """
--> 947     print(self._show_string(n, truncate, vertical))

File , in DataFrame._show_string(self, n, truncate, vertical)
    959     raise PySparkTypeError(
    960         error_class="NOT_BOOL",
    961         message_parameters={"arg_name": "vertical", "arg_type": type(vertical).__name__},
    962     )
    964 if isinstance(truncate, bool) and truncate:
--> 965     return self._jdf.showString(n, 20, vertical)
    966 else:
    967     try:

File , in JavaMember.__call__(self, *args)
   1316 command = proto.CALL_COMMAND_NAME +\
   1317     self.command_header +\
   1318     args_command +\
   1319     proto.END_COMMAND_PART
   1321 answer = self.gateway_client.send_command(command)
-> 1322 return_value = get_return_value(
   1323     answer, self.gateway_client, self.target_id, self.name)
   1325 for temp_arg in temp_args:
   1326     if hasattr(temp_arg, "_detach"):

File , in capture_sql_exception.<locals>.deco(*a, **kw)
    177 def deco(*a: Any, **kw: Any) -> Any:
    178     try:
--> 179         return f(*a, **kw)
    180     except Py4JJavaError as e:
    181         converted = convert_exception(e.java_exception)

File , in get_return_value(answer, gateway_client, target_id, name)
    324 value = OUTPUT_CONVERTER[type](answer[2:], gateway_client)
    325 if answer[1] == REFERENCE_TYPE:
--> 326     raise Py4JJavaError(
    327         "An error occurred while calling {0}{1}{2}".
    328         format(target_id, ".", name), value)
    329 else:
    330     raise Py4JError(
    331         "An error occurred while calling {0}{1}{2}. Trac{3}\n".
    332         format(target_id, ".", name, value))

Py4JJavaError: An error occurred while calling o43.showString.
: 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) (Bat-Computer executor driver): org.apache.spark.SparkException: Python worker exited unexpectedly (crashed)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator$$anonfun$1.applyOrElse(PythonRunner.scala:612)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator$$anonfun$1.applyOrElse(PythonRunner.scala:594)
at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:38)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:789)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:766)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:525)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:491)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenEvaluatorFactory$WholeStageCodegenPartitionEvaluator$$anon$1.hasNext(WholeStageCodegenEvaluatorFactory.scala:43)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:388)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:893)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:893)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:367)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:331)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)
at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:166)
at org.apache.spark.scheduler.Task.run(Task.scala:141)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:620)
at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64)
at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:94)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:623)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1144)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:642)
at java.base/java.lang.Thread.run(Thread.java:1583)
Caused by: java.io.EOFException
at java.base/java.io.DataInputStream.readFully(DataInputStream.java:210)
at java.base/java.io.DataInputStream.readInt(DataInputStream.java:385)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:774)
... 26 more

Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2856)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2792)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2791)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2791)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1247)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1247)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1247)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:3060)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2994)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2983)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:989)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2393)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2414)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2433)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:530)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:483)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:61)
at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:4333)
at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:3316)
at org.apache.spark.sql.Dataset.$anonfun$withAction$2(Dataset.scala:4323)
at org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:546)
at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:4321)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:125)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:201)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:108)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:900)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:66)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:4321)
at org.apache.spark.sql.Dataset.head(Dataset.scala:3316)
at org.apache.spark.sql.Dataset.take(Dataset.scala:3539)
at org.apache.spark.sql.Dataset.getRows(Dataset.scala:280)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:315)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:75)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:52)
at java.base/java.lang.reflect.Method.invoke(Method.java:580)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:374)
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.base/java.lang.Thread.run(Thread.java:1583)
Caused by: org.apache.spark.SparkException: Python worker exited unexpectedly (crashed)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator$$anonfun$1.applyOrElse(PythonRunner.scala:612)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator$$anonfun$1.applyOrElse(PythonRunner.scala:594)
at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:38)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:789)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:766)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:525)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:491)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenEvaluatorFactory$WholeStageCodegenPartitionEvaluator$$anon$1.hasNext(WholeStageCodegenEvaluatorFactory.scala:43)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:388)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:893)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:893)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:367)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:331)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)
at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:166)
at org.apache.spark.scheduler.Task.run(Task.scala:141)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:620)
at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64)
at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:94)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:623)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1144)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:642)
... 1 more
Caused by: java.io.EOFException
at java.base/java.io.DataInputStream.readFully(DataInputStream.java:210)
at java.base/java.io.DataInputStream.readInt(DataInputStream.java:385)
at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:774)
... 26 more~\Workspace\Projects\Python\PySpark\MyFirstPySpark_Proj\spark_venv\Lib\site-packages\pyspark\sql\dataframe.py:947~\Workspace\Projects\Python\PySpark\MyFirstPySpark_Proj\spark_venv\Lib\site-packages\pyspark\sql\dataframe.py:965~\Workspace\Projects\Python\PySpark\MyFirstPySpark_Proj\spark_venv\Lib\site-packages\py4j\java_gateway.py:1322~\Workspace\Projects\Python\PySpark\MyFirstPySpark_Proj\spark_venv\Lib\site-packages\pyspark\errors\exceptions\captured.py:179~\Workspace\Projects\Python\PySpark\MyFirstPySpark_Proj\spark_venv\Lib\site-packages\py4j\protocol.py:326.\ne:\n

The code looks correct. What versions of Spark, and Java and Python are you using?

1 of 2

2 of 2

u/Competitive-Estate46 , a couple of months ago I think I faced a similar error to yours and I've made a post about it here. You can check it in my profile, in case it helps you out, cause I have also added it a solution that worked for me.

Saturn Cloud

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Py4JJavaError Using Pyspark in Jupyter notebook trying to run examples using spark | Saturn Cloud Blog

October 4, 2023 - PySpark uses Py4J to communicate with the Java Virtual Machine (JVM) that runs Spark. Py4JJavaError is an error that occurs when there is a communication problem between PySpark and the JVM.

stackoverflow.com › questions › 78933636 › while-in-jupyter-notebook-while-using-pyspark-get-py4jjavaerror-when-using-sim

python 3.x - While in Jupyter notebook, while using pyspark, get Py4JJavaError when using simple .count - Stack Overflow

import pyspark from pyspark import SparkContext from pyspark.sql import SQLContext from pyspark.sql import SparkSession from pyspark.sql.types import Row from datetime import datetime sc = SparkContext() spark = SparkSession(sc) simple_data = sc.parallelize([1, "Nissan Versa", 12]) simple_data.count() ... -------------------------------------------------------------------------- Py4JJavaError Traceback (most recent call last) Cell In[10], line 1 ----> 1 simple_data.count() File ~\anaconda3\Lib\site-packages\pyspark\rdd.py:2316, in RDD.count(self) 2295 def count(self) -> int: 2296 """ 2297 Return the number of elements in this RDD.

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community.dataquest.io › q&a › dq courses

Pyspark working at the terminal but not fully in jupyter notebook - DQ Courses - Dataquest Community

September 23, 2019 - I installed everything needed to use pyspark in Jupyter notebook. While some test code I found online worked at the terminal and the notebook. The code from the course, which involves .take() and other data access methods resulted in a Py4JJavaError (see below).

github.com › jupyterlab › jupyterlab › issues › 16715

Py4JJavaError: An error occurred while calling o71.showString. · Issue #16715 · jupyterlab/jupyterlab

August 24, 2024 - ----> 2 df.show() 3 df.printSchema() ~\anaconda3\lib\site-packages\pyspark\sql\dataframe.py in show(self, n, truncate, vertical) 945 name | Bob 946 """ --> 947 print(self._show_string(n, truncate, vertical)) 948 949 def _show_string( ~\anaconda3\lib\site-packages\pyspark\sql\dataframe.py in _show_string(self, n, truncate, vertical) 963 964 if isinstance(truncate, bool) and truncate: --> 965 return self._jdf.showString(n, 20, vertical) 966 else: 967 try: ~\anaconda3\lib\site-packages\py4j\java_gateway.py in __call__(self, *args) 1320 1321 answer = self.gateway_client.send_command(command) -> 13

Author KanataD

github.com › jupyter › nbconvert › issues › 1913

"Py4JJavaError" Does not stop notebook execution. · Issue #1913 · jupyter/nbconvert

November 25, 2022 - Guys, when I'm running a jupyter-notebook that runs some spark code and the cell gives an error due to Py4JJavaError (when workers die, for example), notebook execution is not interrupted. I'm using version 7.2.5 Here is an example of tr...

Author rodolfo-nobrega