In my case, the installed Java was lower than required for version >=3.4.0. As stated in the docs:
Spark runs on Java 8/11/17, Scala 2.12/2.13, Python 3.7+, and R 3.5+. Python 3.7 support is deprecated as of Spark 3.4.0. Java 8 prior to version 8u362 support is deprecated as of Spark 3.4.0. [...]
After updating Java to 11, the error was gone with both pyspark 3.4.1 and 3.5.0.
Apache
spark.apache.org › docs › latest › api › python › development › debugging.html
Debugging PySpark - Apache Spark
... 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( ...
Top answer 1 of 3
1
In my case, the installed Java was lower than required for version >=3.4.0. As stated in the docs:
Spark runs on Java 8/11/17, Scala 2.12/2.13, Python 3.7+, and R 3.5+. Python 3.7 support is deprecated as of Spark 3.4.0. Java 8 prior to version 8u362 support is deprecated as of Spark 3.4.0. [...]
After updating Java to 11, the error was gone with both pyspark 3.4.1 and 3.5.0.
2 of 3
0
Looks like you might have inconsistencies with your Spark versions installed.
You have your Pyspark code that tries to call the legacyInferArrayTypeFromFirstElement method of the underlying SQLConf object, which has only been introduced since since v3.4.0.
But since your error is
py4j.Py4JException: Method legacyInferArrayTypeFromFirstElement([]) does not exist
I would think that your underlying Spark installation is not on version 3.4.0. This is of course dependent on how you have Spark installed so it's hard to say exactly. Try to verify which version your Pyspark is using (should be 3.4.0) and which version of Spark the executors start up with.
Running pyspark gives Py4JJavaError
The code looks correct. What versions of Spark, and Java and Python are you using? More on reddit.com
7
5
October 19, 2024python - Configuration of pyspark: Py4JJavaError - Stack Overflow
I am new to PySpark and I encounter a configuration problem in using it. I tried to create a dataframe using the below code snippet: from pyspark.sql import SparkSession # Create a SparkSession ob... More on stackoverflow.com
python - Error from PySpark code to showdataFrame : py4j.protocol.Py4JJavaError - Stack Overflow
import os import sys from pyspark.sql ... df=spark.createDataFrame(date_list).toDF("Name","Age") df.printSchema() df.show() spark_practice() ... File "C:\Program Files\Hadoop\spark-3.5.1\python\lib\py4j-0.10.9.7-src.zip\py4j\protocol.py", line 326, in get_return_value py4j.protocol.Py4JJavaError: An error ... More on stackoverflow.com
How to fix DataFrame function issues in PySpark - Py4JJavaError - Stack Overflow
I am trying to create and analyze dataframe in PySpark and in Notebook. Below are my codes in Jupyter Notebook. from pyspark.sql import SparkSession spark = SparkSession.builder \ .master("... More on stackoverflow.com
Top answer 1 of 11
17
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
10
For me
import findspark
findspark.init()
import pyspark
solved the problem
Databricks Community
community.databricks.com › t5 › data-engineering › i-created-a-data-frame-but-was-not-able-to-see-the-data › td-p › 14720
Solved: I created a data frame but was not able to see the... - Databricks Community - 14720
June 17, 2023 - df=spark.createDataFrame(rdd,schema=StructType([StructField("name",StringType(),True),StructField("loc",StringType(),True)])) Trying to see the data but face below error: df.show() Error: --------------------------------------------------------------------------- Py4JJavaError Traceback (most recent call last) <ipython-input-2-1a6ce2362cd4> in <module> ----> 1 df.show() c:\program files (x86)\python38-32\lib\site-packages\pyspark\sql\dataframe.py in show(self, n, truncate, vertical) 438 """ 439 if isinstance(truncate, bool) and truncate: --> 440 print(self._jdf.showString(n, 20, vertical)) 441 else: 442 print(self._jdf.showString(n, int(truncate), vertical)) c:\program files (x86)\python38-32\lib\site-packages\py4j\java_gateway.py in __call__(self, *args) 1302 ·
Reddit
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 Top answer 1 of 2
1
The code looks correct. What versions of Spark, and Java and Python are you using?
2 of 2
1
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.
Top answer 1 of 2
1
I hope it works for your solution,
findspark adds pyspark to your sys.path at runtime
pip install findspark
Restart the kernel
import findspark
findspark.init()
findspark.find()
from pyspark.sql import SparkSession
# Create a SparkSession object
spark = SparkSession.builder.appName("CreateDataFrame").getOrCreate()
# Use the SparkSession object to create a DataFrame
df_day_of_week = spark.createDataFrame([(0, "Sunday"), (1, "Monday"),
(2, "Tuesday"), (3, "Wednesday"),
(4, "Thursday"), (5, "Friday"),
(6, "Saturday")],
["day_of_week_num", "day_of_week"])
# Show the DataFrame
df_day_of_week.show()
2 of 2
0
It shouldn't be surprising that both createDataFrame() and read.csv() don't give an error. The reason is that they are transformations, hence Spark is just saving them "for later" but not actually doing anything in accordance with the lazy evaluation paradigm.
You can see this for instance by changing the csv file after createDataFrame().
show() on the contrary is an action and this is where the Spark engine gets activated.
The relevant error message in your log is: "Python worker failed to connect back". This hints at some malconfiguration in your Spark architecture.
You will find some possible solutions in: Python worker failed to connect back
Stack Overflow
stackoverflow.com › questions › 61833935 › graphframes-py4j-protocol-py4jjavaerror-an-error-occurred-while-calling-o100-c
apache spark - Graphframes: py4j.protocol.Py4JJavaError: An error occurred while calling o100.createGraph - Stack Overflow
Traceback (most recent call last): File "/home/hadoop/scripts/tst.py", line 32, in <module> g = GraphFrame(vertices, edges) File "/root/.ivy2/jars/graphframes_graphframes-0.7.0-spark2.4-s_2.11.jar/graphframes/graphframe.py", line 89, in __init__ File "/usr/lib/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__ File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 63, in deco File "/usr/lib/spark/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 o100.createGraph.
Reddit
reddit.com › r/apachespark › error with pyspark and py4j
r/apachespark on Reddit: Error with PySpark and Py4J
September 5, 2024 -
Hey everyone!
I recently started working with Apache Spark, and its PySpark implementation in a professional environment, thus I am by no means an expert, and I am facing an error with Py4J.
In more details, I have installed Apache Spark, and already set up the SPARK_HOME, HADOOP_HOME, JAVA_HOME environment variables. As I want to run PySpark without using pip install pyspark, I have set up a PYTHONPATH environment variable, with values pointing to the python folder of Apache Spark and inside the py4j.zip.
My issue is that when I create a dataframe from scratch and use the command df.show() I get the Error
*"*Py4JJavaError: An error occurred while calling o143.showString. : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 4.0 failed 1 times, most recent failure: Lost task 0.0 in stage 4.0 (TID 4) (xxx-yyyy.mshome.net executor driver): org.apache.spark.SparkException: Python worker failed to connect back".
However, the command works as it should when the dataframe is created, for example, by reading a csv file. Other commands that I have also tried, works as they should.
The version of the programs that I use are:
Python 3.11.9 (always using venv, so Python is not in path)
Java 11
Apache Spark 3.5.1 (and Hadoop 3.3.6 for the win.utls file and hadoop.dll)
Visual Studio Code
Windows 11
I have tried other version of Python (3.11.8, 3.12.4) and Apache Spark (3.5.2), with the same response
Any help would be greatly appreciated!
The following two pictures just show an example of the issue that I am facing.
----------- UPDATED SOLUTION -----------
In the end, also thanks to the suggestions in the comments, I figured out a way to make PySpark work with the following implementation. After running this code in a cell, PySpark is recognized as it should and the code runs without issues even for the manually created dataframe, Hopefully, it can also be helpful to others!
# Import the necessary libraries
import os, sys
# Add the necessary environment variables
os.environ["PYSPARK_PYTHON"] = sys.executable
os.environ["spark_python"] = os.getenv('SPARK_HOME') + "\\python"
os.environ["py4j"] = os.getenv('SPARK_HOME') + "\\python\lib\py4j-0.10.9.7-src.zip"
# Retrieve the values from the environment variables
spark_python_path = os.environ["spark_python"]
py4j_zip_path = os.environ["py4j"]
# Add the paths to sys.path
for path in [spark_python_path, py4j_zip_path]:
if path not in sys.path:
sys.path.append(path)
# Verify that the paths have been added to sys.path
print("sys.path:", sys.path) Top answer 1 of 5
3
I was learning Spark and during the installation I got the error of 'Java gateway process exited'. After trying a lot of solutions I finally found a way. I changed the location of my Temp directory under my User Environment Variables. So, the problem was that I had a space in my username, so it was working properly. Don't know if this helps in your case.😅
2 of 5
2
I don't have access to windows computer, and I checked your code is correct. I have found this stack overflow question that contains many possible causes and fixes in the answers. One of them might apply to you: https://stackoverflow.com/questions/53252181/python-worker-failed-to-connect-back Hope this helps.
GitHub
github.com › awslabs › python-deequ › issues › 108
Py4JJavaError creating a SparkSession with pydeequ configurations · Issue #108 · awslabs/python-deequ
September 17, 2022 - Describe the bug A clear and concise description of what the bug is. Py4JJavaError thrown with SparkSession configurations To Reproduce Steps to reproduce the behavior: Create anaconda environment Install openjdk, pypsark 3.0.0, findspar...
Author norhther
Top answer 1 of 4
12
before running the above code you can manually set the env variable like this
import os
import sys
os.environ['PYSPARK_PYTHON'] = sys.executable
os.environ['PYSPARK_DRIVER_PYTHON'] = sys.executable
this worked in jupyter notebook for me.
2 of 4
4
The key is in this part of the error message:
RuntimeError: Python in worker has different version 3.9 than that in driver 3.10, PySpark cannot run with different minor versions. Please check environment variables PYSPARK_PYTHON and PYSPARK_DRIVER_PYTHON are correctly set.
You need to have exactly the same Python versions in driver and worker nodes.
Probably a quick solution would be to downgrade your Python version to 3.9 (assuming driver is running on the client you're using).
Stack Overflow
stackoverflow.com › questions › 77946279 › pyspark-py4jjavaerror-caused-by-java-io-eofexception
jupyter notebook - PySpark, Py4JJavaError, Caused by: java.io.EOFException - Stack Overflow
This is the code: # Set the PySpark ... 30), ("Charlie", 35)] df = spark.createDataFrame(data, ["Name", "Age"]) # Show the DataFrame df.show() ... --------------------------------------------------------------------------- Py4JJavaError Traceback (most recent call last) Cell ...
Stack Overflow
stackoverflow.com › questions › 67533296 › pysprk-3-1-1-py4javaerror
java - Pysprk 3.1.1 Py4JavaError - Stack Overflow
Invalid port number: 458961458 (0x1b5b3232) Python command to execute the daemon was: ipython3 -m pyspark.daemon Check that you don't have any unexpected modules or libraries in your PYTHONPATH: /home/ahowe42/spark-3.1.1-bin-hadoop2.7/python/lib/pyspark.zip:/home/ahowe42/spark-3.1.1-bin-hadoop2.7/python/lib/py4j-0.10.9-src.zip:/home/ahowe42/spark-3.1.1-bin-hadoop2.7/jars/spark-core_2.12-3.1.1.jar:/home/ahowe42/spark-3.1.1-bin-hadoop2.7/python: Also, check if you have a sitecustomize.py module in your python path, or in your python installation, that is printing to standard output at org.apache
GitHub
github.com › jupyterlab › jupyterlab › issues › 17281
Py4JJavaError: An error occurred while calling o87.showString. : org.apache.spark.SparkException: Job aborted due to stage failure · Issue #17281 · jupyterlab/jupyterlab
February 12, 2025 - import findspark findspark.init() from pyspark.sql import SparkSession import pyspark.sql.functions as F spark = SparkSession.builder.appName("my_app_name").getOrCreate() data_tuples = [(1, "abc"), (2, "def")] schema = "id int, value string" df = spark.createDataFrame(data_tuples, schema) df.show() Py4JJavaError: An error occurred while calling o87.showString.
Author LenoreValo
GitHub
github.com › maxpumperla › elephas › issues › 183
Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe. · Issue #183 · maxpumperla/elephas
February 24, 2021 - Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.#183 ... Hi, I'm trying to use elephas for my deep learning models on spark but so far I couldn't even get anything to work on 3 different machines and on multiple notebooks. "ml_pipeline_otto.py" crashes on the load_data_frame function, more specifically on return sqlContext.createDataFrame(data, ['features', 'category']) with the error : Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.runJob.
Author diogoribeiro09
Stack Overflow
stackoverflow.com › questions › 69263358 › df-show-is-not-working-py4jjavaerror-an-error-occurred-while-calling-o95-sh
apache spark - df.show() is not working - Py4JJavaError: An error occurred while calling o95.showString - Stack Overflow
from pyspark.sql.types import * ... defined above blogs_df = spark.createDataFrame(data, schema) But when I am trying to execute .show(), I am getting java error. Can somebody help me on how do I resolve this error ? ... Error : Py4JJavaError: An error occurred while calling ...
GitHub
github.com › JohnSnowLabs › spark-nlp › issues › 13995
Py4JJavaError: An error occurred while calling z:com.johnsnowlabs.nlp.pretrained.PythonResourceDownloader.downloadModel. · Issue #13995 · JohnSnowLabs/spark-nlp
September 19, 2023 - I have also tried to implement Spark NLP offline by downloading the .jar and the preprocessing part runs fine, but when I load the model I get the error. Py4JJavaError Traceback (most recent call last) [c:\Users\cristian.castro.rios\OneDrive](file:///C:/Users/cristian.castro.rios/OneDrive) - Accenture\Pruebas_Spark\Clasificacion_Emociones.ipynb Cell 17 line 9 [1](vscode-notebook-cell:/c:/Users/cristian.castro.rios/OneDrive - Accenture/Pruebas_Spark/Clasificacion_Emociones.ipynb#X33sZmlsZQ==?line=0) document_assembler = DocumentAssembler() \ [2](vscode-notebook-cell:/c:/Users/cristian.castro.ri
Author Criscas05
Stack Overflow
stackoverflow.com › questions › 59656781 › createdataframe-pyspark-generates-a-weird-error-py4j-error
python - createDataFrame (pyspark) generates a weird error (py4j error) - Stack Overflow
January 9, 2020 - c:\users\hp\appdata\local\programs\python\python37\lib\site-packages\pyspark\sql\utils.py in deco(*a, **kw) 61 def deco(*a, **kw): 62 try: ---> 63 return f(*a, **kw) 64 except py4j.protocol.Py4JJavaError as e: 65 s = e.java_exception.toString() c:\users\hp\appdata\local\programs\python\python37\lib\site-packages\py4j\protocol.py in get_return_value(answer, gateway_client, target_id, name) 330 raise Py4JError( 331 "An error occurred while calling {0}{1}{2}. Trace:\n{3}\n". --> 332 format(target_id, ".", name, value)) 333 else: 334 raise Py4JError( > Py4JError: An error occurred while calling None.org.apache.spark.api.python.PythonRDD.
Stack Overflow
stackoverflow.com › questions › 75526420 › py4jjavaerror-an-error-occured-while-calling-none-org-apache-spark-api-java-jav
python - Py4JJavaError: An error occured while calling None.org.apache.spark.api.java.JavaSparkContext - Stack Overflow
I was able to get the connection working with pyodbc but when I try to initiate a PySpark session, I get a Py4JJavaError with the following message: An error occurred while calling None.org.apache.spark.api.java.JavaSparkContext.\n: org.apache.hadoop.security.KerberosAuthException: failure to login: javax.security.auth.login.LoginException: No LoginModule found for com.ibm.security.auth.module.