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Pyspark show dataframe results in "Accept timed out" exception

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I am trying to use Spark NLP locally on my Windows 10. Following the instructions from sparknlp.org for installation didn't work and gave me many errors, so I used a different guide. So, to start the work I installed Java, Scala, Apache Spark, then pyspark and spark-nlp packages using pip.

Versions check:

  • python --version is 3.12.0
  • java -version is 1.8.0_391
  • scala -version is 2.12.18
  • spark-shell results in:
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
23/12/24 22:49:08 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Spark context Web UI available at http://host.docker.internal:4040
Spark context available as 'sc' (master = local[*], app id = local-1703447349616).
Spark session available as 'spark'.
Welcome to
__
_____/ /__
__/  '_/
version 3.5.0
      /_/

Using Scala version 2.12.18 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_391)
Type in expressions to have them evaluated.
Type :help for more information.

spark-nlp version is 5.1.2 and pyspark version is 3.5.0

Running this code in my python notebook

import sparknlp

print("Spark NLP version: ", sparknlp.version())
spark = sparknlp.start()
spark

gives me

Spark NLP version:  5.1.2

SparkSession - in-memory
SparkContext
Spark UI
Version v3.5.0
Master local[*]
AppName Spark NLP

So it seems that everything should be ok in terms of compatibility!

But the simplest code

text = 'Peter Parker is a nice guy and lives in New York'
spark_df = spark.createDataFrame([[text]]).toDF("text")

spark_df.show(truncate=60)

gives me an java.net.SocketTimeoutException: Accept timed out error in the last line. The logs are below.

At the same time spark_df.printSchema() works fine and gives me

root
 |-- text: string (nullable = true)

I really cannot understand what the issue is about. Couldn't find a solution in similar questions here. Would be grateful for your help.

Error logs:

--------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
Cell In[4], line 1
----> 1 spark_df.show(truncate=60)

File ...\venv\Lib\site-packages\pyspark\sql\dataframe.py:972, in DataFrame.show(self, n, truncate, vertical)
    963 except ValueError:
    964     raise PySparkTypeError(
    965         error_class="NOT_BOOL",
    966         message_parameters={
   (...)
    969         },
    970     )
--> 972 print(self._jdf.showString(n, int_truncate, vertical))

File ...\venv\Lib\site-packages\py4j\java_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 ...\venv\Lib\site-packages\pyspark\errors\exceptions\captured.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 ...\venv\Lib\site-packages\py4j\protocol.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 o62.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) (host.docker.internal 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:364)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)
    at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:161)
    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)
    ... 32 more

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2844)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2780)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2779)
    at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
    at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2779)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1242)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1242)
    at scala.Option.foreach(Option.scala:407)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1242)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:3048)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2982)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2971)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:984)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2398)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2419)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2438)
    at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:530)
    at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:483)
    at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:61)
    at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:4344)
    at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:3326)
    at org.apache.spark.sql.Dataset.$anonfun$withAction$2(Dataset.scala:4334)
    at org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:546)
    at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:4332)
    at org.apache.spark.sql.execution.SQLExecution$.$anonfun$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:4332)
    at org.apache.spark.sql.Dataset.head(Dataset.scala:3326)
    at org.apache.spark.sql.Dataset.take(Dataset.scala:3549)
    at org.apache.spark.sql.Dataset.getRows(Dataset.scala:280)
    at org.apache.spark.sql.Dataset.showString(Dataset.scala:315)
    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:364)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)
    at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:161)
    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)
    ... 32 more

I've tried looking for any reasons, the only ones I found were due to versioning problems, but I already solved it and it didn't help. Also I've tried increasing the heartbeat interval for the session.

upd. Logs after setting PYSPARK_PYTHON and increasing notebook buffer size:

---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
Cell In[6], line 1
----> 1 spark_df.show(truncate=1)

File d:\ai_pipeline\venv\Lib\site-packages\pyspark\sql\dataframe.py:972, in DataFrame.show(self, n, truncate, vertical)
    963 except ValueError:
    964     raise PySparkTypeError(
    965         error_class="NOT_BOOL",
    966         message_parameters={
   (...)
    969         },
    970     )
--> 972 print(self._jdf.showString(n, int_truncate, vertical))

File d:\ai_pipeline\venv\Lib\site-packages\py4j\java_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 d:\ai_pipeline\venv\Lib\site-packages\pyspark\errors\exceptions\captured.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 d:\ai_pipeline\venv\Lib\site-packages\py4j\protocol.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 o62.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1.0 (TID 1) (host.docker.internal 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$2(RDD.scala:890)
    at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:890)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)
    at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:161)
    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.io.EOFException
    at java.io.DataInputStream.readInt(Unknown Source)
    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:2844)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2780)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2779)
    at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
    at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2779)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1242)
    at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1242)
    at scala.Option.foreach(Option.scala:407)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1242)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:3048)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2982)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2971)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:984)
    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.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:4344)
    at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:3326)
    at org.apache.spark.sql.Dataset.$anonfun$withAction$2(Dataset.scala:4334)
    at org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:546)
    at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:4332)
    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:4332)
    at org.apache.spark.sql.Dataset.head(Dataset.scala:3326)
    at org.apache.spark.sql.Dataset.take(Dataset.scala:3549)
    at org.apache.spark.sql.Dataset.getRows(Dataset.scala:280)
    at org.apache.spark.sql.Dataset.showString(Dataset.scala:315)
    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 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$$anon$1.hasNext(WholeStageCodegenEvaluatorFactory.scala:43)
    at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:388)
    at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:890)
    at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:890)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:328)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)
    at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:161)
    at org.apache.spark.scheduler.Task.run(Task.scala:141)
    at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:620)
    at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64)
    at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:94)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:623)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
    ... 1 more
Caused by: java.io.EOFException
    at java.io.DataInputStream.readInt(Unknown Source)
    at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:774)
    ... 26 more
python windows pyspark johnsnowlabs-spark-nlp
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