Ошибка PySpark при вызове PythonRDD - DecisionTree trainClassifier - PullRequest
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Ошибка PySpark при вызове PythonRDD - DecisionTree trainClassifier

0 голосов
/ 09 марта 2019

Я довольно новичок в питоне с ноутбуком Jupyter. У меня есть данные, которые я предположил, чтобы обучить и запустить алгоритм классификации, например, дерево решений, Наивный байк и KNN. С первой миссией я должен был сделать это с пандами, я нашел много информации в интернете, и мне это удалось. Моя следующая миссия - сделать ту же классификацию с PySpark вместо панд. У меня ошибка при выполнении: 

treeModel = DecisionTree.trainClassifier(training, numClasses=4, categoricalFeaturesInfo={},
                                     impurity='gini', maxDepth=20, maxBins=32)

Поэтому я подумал, что проблема в моем коде, поэтому я нашел простую программу, которая должна работать в интернете: 

import findspark
findspark.init()
import pyspark
import random
sc.stop()
sc = pyspark.SparkContext(appName="Pi")
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()

В них обоих я получаю одинаковую ошибку: 

---------------------------------------------------------------------------
Py4JJavaError                             Traceback (most recent call last)
<ipython-input-2-4b916c422527> in <module>()
      1 treeModel = DecisionTree.trainClassifier(training, numClasses=4, categoricalFeaturesInfo={},
----> 2                                      impurity='gini', maxDepth=20, maxBins=32)
      3 predictions1 = treeModel.predict(test.map(lambda x: x.features))
      4 labelsAndPredictions = test.map(lambda lp: lp.label).zip(predictions1)
      5 printStatistics(labelsAndPredictions, test)

~\Anaconda3\lib\site-packages\pyspark\mllib\tree.py in trainClassifier(cls, data, numClasses, categoricalFeaturesInfo, impurity, maxDepth, maxBins, minInstancesPerNode, minInfoGain)
    215         """
    216         return cls._train(data, "classification", numClasses, categoricalFeaturesInfo,
--> 217                           impurity, maxDepth, maxBins, minInstancesPerNode, minInfoGain)
    218 
    219     @classmethod

~\Anaconda3\lib\site-packages\pyspark\mllib\tree.py in _train(cls, data, type, numClasses, features, impurity, maxDepth, maxBins, minInstancesPerNode, minInfoGain)
    139     def _train(cls, data, type, numClasses, features, impurity="gini", maxDepth=5, maxBins=32,
    140                minInstancesPerNode=1, minInfoGain=0.0):
--> 141         first = data.first()
    142         assert isinstance(first, LabeledPoint), "the data should be RDD of LabeledPoint"
    143         model = callMLlibFunc("trainDecisionTreeModel", data, type, numClasses, features,

~\Anaconda3\lib\site-packages\pyspark\rdd.py in first(self)
   1376         ValueError: RDD is empty
   1377         """
-> 1378         rs = self.take(1)
   1379         if rs:
   1380             return rs[0]

~\Anaconda3\lib\site-packages\pyspark\rdd.py in take(self, num)
   1358 
   1359             p = range(partsScanned, min(partsScanned + numPartsToTry, totalParts))
-> 1360             res = self.context.runJob(self, takeUpToNumLeft, p)
   1361 
   1362             items += res

~\Anaconda3\lib\site-packages\pyspark\context.py in runJob(self, rdd, partitionFunc, partitions, allowLocal)
   1049         # SparkContext#runJob.
   1050         mappedRDD = rdd.mapPartitions(partitionFunc)
-> 1051         sock_info = self._jvm.PythonRDD.runJob(self._jsc.sc(), mappedRDD._jrdd, partitions)
   1052         return list(_load_from_socket(sock_info, mappedRDD._jrdd_deserializer))
   1053 

~\Anaconda3\lib\site-packages\py4j\java_gateway.py in __call__(self, *args)
   1255         answer = self.gateway_client.send_command(command)
   1256         return_value = get_return_value(
-> 1257             answer, self.gateway_client, self.target_id, self.name)
   1258 
   1259         for temp_arg in temp_args:

~\Anaconda3\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()

~\Anaconda3\lib\site-packages\py4j\protocol.py in get_return_value(answer, gateway_client, target_id, name)
    326                 raise Py4JJavaError(
    327                     "An error occurred while calling {0}{1}{2}.\n".
--> 328                     format(target_id, ".", name), value)
    329             else:
    330                 raise Py4JError(

Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.runJob.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 14.0 failed 1 times, most recent failure: Lost task 0.0 in stage 14.0 (TID 53, localhost, executor driver): java.io.IOException: Cannot run program "D:\spark\spark-2.4.0-bin-hadoop2.7\python": CreateProcess error=5, Access is denied
    at java.lang.ProcessBuilder.start(ProcessBuilder.java:1048)
    at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:155)
    at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:97)
    at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
    at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:108)
    at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:121)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)
Caused by: java.io.IOException: CreateProcess error=5, Access is denied
    at java.lang.ProcessImpl.create(Native Method)
    at java.lang.ProcessImpl.<init>(ProcessImpl.java:386)
    at java.lang.ProcessImpl.start(ProcessImpl.java:137)
    at java.lang.ProcessBuilder.start(ProcessBuilder.java:1029)
    ... 15 more

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1887)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1875)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1874)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1874)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
    at scala.Option.foreach(Option.scala:257)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2108)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2057)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2046)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
    at org.apache.spark.api.python.PythonRDD$.runJob(PythonRDD.scala:153)
    at org.apache.spark.api.python.PythonRDD.runJob(PythonRDD.scala)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    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.GatewayConnection.run(GatewayConnection.java:238)
    at java.lang.Thread.run(Thread.java:748)
Caused by: java.io.IOException: Cannot run program "D:\spark\spark-2.4.0-bin-hadoop2.7\python": CreateProcess error=5, Access is denied
    at java.lang.ProcessBuilder.start(ProcessBuilder.java:1048)
    at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:155)
    at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:97)
    at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
    at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:108)
    at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
    at org.apache.spark.scheduler.Task.run(Task.scala:121)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    ... 1 more
Caused by: java.io.IOException: CreateProcess error=5, Access is denied
    at java.lang.ProcessImpl.create(Native Method)
    at java.lang.ProcessImpl.<init>(ProcessImpl.java:386)
    at java.lang.ProcessImpl.start(ProcessImpl.java:137)
    at java.lang.ProcessBuilder.start(ProcessBuilder.java:1029)
    ... 15 more

Простая программа выглядит как та же ошибка со всем текстом после: 

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, localhost, executor driver): java.io.IOException: Cannot run program "D:\spark\spark-2.4.0-bin-hadoop2.7\python": CreateProcess error=5, Access is denied

У меня есть тест еще несколько дней, я надеюсь найти решение здесь.

Редактировать: последняя версия Spark 2.4.0 и python 3.7.1. С точки зрения ресурсов установки - я следовал инструкциям из этого урока:

скачал spark-2.4.0-bin-hadoop2.7.tgz с веб-сайта Apache Spark

распаковал его на мой C-диск

уже имеет установленный Python_3 (дистрибутив Anaconda), а также Java

создал локальную папку 'C: \ hadoop \ bin' для хранения winutils.exe

создал папку 'C: \ tmp \ hive' и дал Spark доступ к ней

добавлены переменные окружения (SPARK_HOME, HADOOP_HOME и т. Д.)

Кроме того, я попытался изменить версии Java (8+) и версию spark (2.3, 2.2.4) - но ошибка все еще существует.

Спасибо заранее, Бен.

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