# Loading train data ---there is a trouble,please help

[aiyanzidexiaotao]

Py4JJavaError Traceback (most recent call last)
in
1 # Loading train data
2 t0 = time()
----> 3 train_df = load_dataset(train_nsl_kdd_dataset_path)

in load_dataset(path)
2 def load_dataset(path):
3 dataset_rdd = sc.textFile(path, 8).map(lambda line: line.split(','))
----> 4 dataset_df = (dataset_rdd.toDF(col_names.tolist()).select(
5 col('duration').cast(DoubleType()),
6 col('protocol_type').cast(StringType()),

c:\users\86536\appdata\local\programs\python\python36\pyspark\sql\session.py in toDF(self, schema, sampleRatio)
56 [Row(name=u'Alice', age=1)]
57 """
---> 58 return sparkSession.createDataFrame(self, schema, sampleRatio)
59
60 RDD.toDF = toDF

c:\users\86536\appdata\local\programs\python\python36\pyspark\sql\session.py in createDataFrame(self, data, schema, samplingRatio, verifySchema)
744
745 if isinstance(data, RDD):
--> 746 rdd, schema = self._createFromRDD(data.map(prepare), schema, samplingRatio)
747 else:
748 rdd, schema = self._createFromLocal(map(prepare, data), schema)

c:\users\86536\appdata\local\programs\python\python36\pyspark\sql\session.py in _createFromRDD(self, rdd, schema, samplingRatio)
388 """
389 if schema is None or isinstance(schema, (list, tuple)):
--> 390 struct = self._inferSchema(rdd, samplingRatio, names=schema)
391 converter = _create_converter(struct)
392 rdd = rdd.map(converter)

c:\users\86536\appdata\local\programs\python\python36\pyspark\sql\session.py in _inferSchema(self, rdd, samplingRatio, names)
359 :return: :class:pyspark.sql.types.StructType
360 """
--> 361 first = rdd.first()
362 if not first:
363 raise ValueError("The first row in RDD is empty, "

c:\users\86536\appdata\local\programs\python\python36\pyspark\rdd.py in first(self)
1376 ValueError: RDD is empty
1377 """
-> 1378 rs = self.take(1)
1379 if rs:
1380 return rs[0]

c:\users\86536\appdata\local\programs\python\python36\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

c:\users\86536\appdata\local\programs\python\python36\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

c:\users\86536\appdata\local\programs\python\python36\lib\site-packages\py4j\java_gateway.py in call(self, *args)
1284 answer = self.gateway_client.send_command(command)
1285 return_value = get_return_value(
-> 1286 answer, self.gateway_client, self.target_id, self.name)
1287
1288 for temp_arg in temp_args:

c:\users\86536\appdata\local\programs\python\python36\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\86536\appdata\local\programs\python\python36\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 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0, localhost, executor driver): org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:170)
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.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(DualStackPlainSocketImpl.java:135)
at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:409)
at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:199)
at java.net.ServerSocket.implAccept(ServerSocket.java:545)
at java.net.ServerSocket.accept(ServerSocket.java:513)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:164)
... 14 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: org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:170)
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.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(DualStackPlainSocketImpl.java:135)
at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:409)
at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:199)
at java.net.ServerSocket.implAccept(ServerSocket.java:545)
at java.net.ServerSocket.accept(ServerSocket.java:513)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:164)
... 14 more

[Sava Kalbachou]

Hi,

I'm sorry for the late reply. Finally got some time to provide an easier way to run a docker container via make nsl-kdd-pyspark command with the lates pyspark installed. I've run the notebook end-to-end and haven't faced any issues, so I'd advice to just use docker container.