You probably have to increase jvm/jdk memory size

https://stackoverflow.com/questions/1565388/increase-heap-size-in-java


On Mon, Jul 29, 2024 at 9:36 PM mike Jadoo <mikejad...@gmail.com> wrote:

> Thanks.   I just downloaded the corretto  but I got this error message,
> which was the same as before. [It was shared with me that this saying that
> I have limited resources, i think]
>
> ---------------------------------------------------------------------------Py4JJavaError
>                              Traceback (most recent call last)
> Cell In[3], line 13      8 squared_rdd = rdd.map(lambda x: x * x)     10 # 
> Persist the DataFrame in memory     11 
> #squared_rdd.persist(StorageLevel.MEMORY_ONLY)     12 # Collect the results 
> into a list---> 13 result = squared_rdd.collect()     15 # Print the result   
>   16 print(result)
>
> File 
> C:\spark\spark-3.5.1-bin-hadoop3\python\lib\pyspark.zip\pyspark\rdd.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 ~\anaconda3\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 
> C:\spark\spark-3.5.1-bin-hadoop3\python\lib\pyspark.zip\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 ~\anaconda3\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 
> z:org.apache.spark.api.python.PythonRDD.collectAndServe.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 7 
> in stage 0.0 failed 1 times, most recent failure: Lost task 7.0 in stage 0.0 
> (TID 7) (mjadoo.myfiosgateway.com executor driver): java.io.IOException: 
> Cannot run program "C:\Users\mikej\AppData\Local\Programs\Python\Python312": 
> CreateProcess error=5, Access is denied
>       at java.base/java.lang.ProcessBuilder.start(ProcessBuilder.java:1128)
>       at java.base/java.lang.ProcessBuilder.start(ProcessBuilder.java:1071)
>       at 
> org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:181)
>       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.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
>       at 
> java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
>       at java.base/java.lang.Thread.run(Thread.java:829)
> Caused by: java.io.IOException: CreateProcess error=5, Access is denied
>       at java.base/java.lang.ProcessImpl.create(Native Method)
>       at java.base/java.lang.ProcessImpl.<init>(ProcessImpl.java:492)
>       at java.base/java.lang.ProcessImpl.start(ProcessImpl.java:153)
>       at java.base/java.lang.ProcessBuilder.start(ProcessBuilder.java:1107)
>       ... 19 more
>
> Driver stacktrace:
>       at 
> org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2856)
>       at 
> org.apache.spark.scheduler.DAGScheduler.$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 
> java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>       at 
> java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
>       at 
> java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>       at java.base/java.lang.reflect.Method.invoke(Method.java:566)
>       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:829)
> Caused by: java.io.IOException: Cannot run program 
> "C:\Users\mikej\AppData\Local\Programs\Python\Python312": CreateProcess 
> error=5, Access is denied
>       at java.base/java.lang.ProcessBuilder.start(ProcessBuilder.java:1128)
>       at java.base/java.lang.ProcessBuilder.start(ProcessBuilder.java:1071)
>       at 
> org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:181)
>       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.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
>       at 
> java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
>       ... 1 more
>
>
> On Mon, Jul 29, 2024 at 4:34 PM Sadha Chilukoori <sage.quoti...@gmail.com>
> wrote:
>
>> Hi Mike,
>>
>> I'm not sure about the minimum requirements of a machine for running
>> Spark. But to run some Pyspark scripts (and Jupiter notbebooks) on a local
>> machine, I found the following steps are the easiest.
>>
>>
>> I installed Amazon corretto and updated the java_home variable as
>> instructed here
>> https://docs.aws.amazon.com/corretto/latest/corretto-11-ug/downloads-list.html
>> (Any other java works too, I'm used to corretto from work).
>>
>> Then installed the Pyspark module using pip, which enabled me run Pyspark
>> on my machine.
>>
>> -Sadha
>>
>> On Mon, Jul 29, 2024, 12:51 PM mike Jadoo <mikejad...@gmail.com> wrote:
>>
>>> Hello,
>>>
>>> I am trying to run Pyspark on my computer without success.  I follow
>>> several different directions from online sources and it appears that I need
>>> to get a faster computer.
>>>
>>> I wanted to ask what are some recommendations for computer
>>> specifications to run PySpark (Apache Spark).
>>>
>>> Any help would be greatly appreciated.
>>>
>>> Thank you,
>>>
>>> Mike
>>>
>>

Reply via email to