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Question

While using the following code:

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()

I get the following error:

--------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
Cell In[10], line 1
----> 1 simple_data.count()

File ~anaconda3Libsite-packagespysparkrdd.py:2316, in RDD.count(self)
   2295 def count(self) -> int:
   2296     """
   2297     Return the number of elements in this RDD.
   2298 
   (...)
   2314     3
   2315     """
-> 2316     return self.mapPartitions(lambda i: [sum(1 for _ in i)]).sum()

File ~anaconda3Libsite-packagespysparkrdd.py:2291, in RDD.sum(self)
   2270 def sum(self: "RDD[NumberOrArray]") -> "NumberOrArray":
   2271     """
   2272     Add up the elements in this RDD.
   2273 
   (...)
   2289     6.0
   2290     """
-> 2291     return self.mapPartitions(lambda x: [sum(x)]).fold(  # type: ignore[return-value]
   2292         0, operator.add
   2293     )

File ~anaconda3Libsite-packagespysparkrdd.py:2044, in RDD.fold(self, zeroValue, op)
   2039     yield acc
   2041 # collecting result of mapPartitions here ensures that the copy of
   2042 # zeroValue provided to each partition is unique from the one provided
   2043 # to the final reduce call
-> 2044 vals = self.mapPartitions(func).collect()
   2045 return reduce(op, vals, zeroValue)

File ~anaconda3Libsite-packagespysparkrdd.py:1833, in RDD.collect(self)
   1831 with SCCallSiteSync(self.context):
   1832     assert self.ctx._jvm is not None
-> 1833     sock_info = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
   1834 return list(_load_from_socket(sock_info, self._jrdd_deserializer))

File ~anaconda3Libsite-packagespy4jjava_gateway.py:1322, 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 ~anaconda3Libsite-packagespysparkerrorsexceptionscaptured.py:179, 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 ~anaconda3Libsite-packagespy4jprotocol.py:326, 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}.n".
    328         format(target_id, ".", name), value)
    329 else:
    330     raise Py4JError(
    331         "An error occurred while calling {0}{1}{2}. Trace:n{3}n".
    332         format(target_id, ".", name, value))

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) (DESKTOP-JC7CP9I executor driver): org.apache.spark.SparkException: Python worker failed to connect back.
    at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:203)
    at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:109)
    at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:124)
    at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:174)
    at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:67)
    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.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:190)
    ... 17 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$1.run(EventLoop.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:989)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2398)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2419)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2438)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2463)
    at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1049)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:410)
    at org.apache.spark.rdd.RDD.collect(RDD.scala:1048)
    at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:195)
    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: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.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:203)
    at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:109)
    at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:124)
    at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:174)
    at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:67)
    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.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:190)
    ... 17 more

java version “1.8.0_421”, Python 3.11.8, pyspark 3.5.1

I installed pyspark in anaconda powershell using “conda install -c conda-forge pyspark”.

It is the first time I use spark in jupyter and I don’t know how to fix it. What can I do to fix this?

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Danh mục

While in Jupyter notebook, while using pyspark, get Py4JJavaError when using simple .count