Python工作进程无法连接回

我是Spark的新手，正在尝试完成Spark教程：

在本地计算机（Win10 64、Python 3、Spark 2.4.0）上安装它并设置所有环境变量（HADOOP_HOME、Spark_HOME等）后，我尝试通过WordCount.py文件运行一个简单的Spark作业：

from pyspark import SparkContext, SparkConf

if __name__ == "__main__":
    conf = SparkConf().setAppName("word count").setMaster("local[2]")
    sc = SparkContext(conf = conf)

    lines = sc.textFile("C:/Users/mjdbr/Documents/BigData/python-spark-tutorial/in/word_count.text")
    words = lines.flatMap(lambda line: line.split(" "))
    wordCounts = words.countByValue()

    for word, count in wordCounts.items():
        print("{} : {}".format(word, count))

从终端运行后：

spark-submit WordCount.py

我得到下面的错误。 我检查（通过逐行注释）它在

wordCounts = words.countByValue()

知道我应该检查什么才能让它工作吗

Traceback (most recent call last):
  File "C:\Users\mjdbr\Anaconda3\lib\runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "C:\Users\mjdbr\Anaconda3\lib\runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "C:\Spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py", line 25, in <module>
ModuleNotFoundError: No module named 'resource'
18/11/10 23:16:58 ERROR Executor: Exception in task 0.0 in stage 0.0 (TID 0)
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(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:164)
        ... 14 more
18/11/10 23:16:58 ERROR TaskSetManager: Task 0 in stage 0.0 failed 1 times; aborting job
Traceback (most recent call last):
  File "C:/Users/mjdbr/Documents/BigData/python-spark-tutorial/rdd/WordCount.py", line 19, in <module>
    wordCounts = words.countByValue()
  File "C:\Spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py", line 1261, in countByValue
  File "C:\Spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py", line 844, in reduce
  File "C:\Spark\spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py", line 816, in collect
  File "C:\Spark\spark-2.4.0-bin-hadoop2.7\python\lib\py4j-0.10.7-src.zip\py4j\java_gateway.py", line 1257, in __call__
  File "C:\Spark\spark-2.4.0-bin-hadoop2.7\python\lib\py4j-0.10.7-src.zip\py4j\protocol.py", line 328, in get_return_value
py4j.protocol.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): 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$TaskRunner.run(Executor.scala:408)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
        at java.util.concurrent.ThreadPoolExecutor$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: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.SparkContext.runJob(SparkContext.scala:2126)
        at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:945)
        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:363)
        at org.apache.spark.rdd.RDD.collect(RDD.scala:944)
        at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:166)
        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: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(Unknown Source)
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$TaskRunner.run(Executor.scala:408)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
        at java.util.concurrent.ThreadPoolExecutor$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:164)
        ... 14 more

回溯（最近一次呼叫最后一次）：
文件“C:\Users\mjdbr\Anaconda3\lib\runpy.py”，第193行，位于作为主模块的运行模块中
“\uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu
文件“C:\Users\mjdbr\Anaconda3\lib\runpy.py”，第85行，在运行代码中
exec（代码、运行\全局）
文件“C:\Spark\Spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\worker.py”，第25行，在
ModuleNotFoundError:没有名为“资源”的模块
10月18日11月23:16:58错误执行者：任务0.0在阶段0.0（TID 0）中出现异常
org.apache.spark.SparkException:Python工作者无法连接回。
位于org.apache.spark.api.PythonWorkerFactory.createSimpleWorker（PythonWorkerFactory.scala:170）
位于org.apache.spark.api.python.PythonWorkerFactory.create（PythonWorkerFactory.scala:97）
位于org.apache.spark.SparkEnv.createPythonWorker（SparkEnv.scala:117）
位于org.apache.spark.api.python.BasePythonRunner.compute（PythonRunner.scala:108）
位于org.apache.spark.api.python.PythonRDD.compute（PythonRDD.scala:65）
在org.apache.spark.rdd.rdd.computeOrReadCheckpoint（rdd.scala:324）
位于org.apache.spark.rdd.rdd.iterator（rdd.scala:288）
位于org.apache.spark.scheduler.ResultTask.runTask（ResultTask.scala:90）
位于org.apache.spark.scheduler.Task.run（Task.scala:121）
位于org.apache.spark.executor.executor$TaskRunner$$anonfun$10.apply（executor.scala:402）
位于org.apache.spark.util.Utils$.tryWithSafeFinally（Utils.scala:1360）
位于org.apache.spark.executor.executor$TaskRunner.run（executor.scala:408）
位于java.util.concurrent.ThreadPoolExecutor.runWorker（未知源）
位于java.util.concurrent.ThreadPoolExecutor$Worker.run（未知源）
位于java.lang.Thread.run（未知源）
原因：java.net.SocketTimeoutException:接受超时
位于java.net.DualStackPlainSocketImpl.waitForNewConnection（本机方法）
位于java.net.DualStackPlainSocketImpl.socketAccept（未知源）
位于java.net.AbstractPlainSocketImpl.accept（未知源）
位于java.net.PlainSocketImpl.accept（未知源）
位于java.net.ServerSocket.implacpt（未知源）
位于java.net.ServerSocket.accept（未知源）
位于org.apache.spark.api.PythonWorkerFactory.createSimpleWorker（PythonWorkerFactory.scala:164）
... 14多
18/11/10 23:16:58错误TaskSetManager:阶段0.0中的任务0失败1次；中止工作
回溯（最近一次呼叫最后一次）：
文件“C:/Users/mjdbr/Documents/BigData/pythonspark tutorial/rdd/WordCount.py”，第19行，在
wordCounts=words.countByValue（）
文件“C:\Spark\Spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py”，第1261行，countByValue中
文件“C:\Spark\Spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py”，reduce中第844行
文件“C:\Spark\Spark-2.4.0-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\rdd.py”，第816行，在collect中
文件“C:\Spark\Spark-2.4.0-bin-hadoop2.7\python\lib\py4j-0.10.7-src.zip\py4j\java_gateway.py”，第1257行，在u调用中__
文件“C:\Spark\Spark-2.4.0-bin-hadoop2.7\python\lib\py4j-0.10.7-src.zip\py4j\protocol.py”，第328行，在get\u返回值中
py4j.protocol.Py4JJavaError:调用z:org.apache.spark.api.python.PythonRDD.collectAndServe时出错。
：org.apache.spark.sparkeexception:作业因阶段失败而中止：阶段0.0中的任务0失败1次，最近一次失败：
在阶段0.0中丢失了任务0.0（TID 0，localhost，executor driver）：org.apache.spark.SparkException:Python worker无法重新连接。
位于org.apache.spark.api.PythonWorkerFactory.createSimpleWorker（PythonWorkerFactory.scala:170）
位于org.apache.spark.api.python.PythonWorkerFactory.create（PythonWorkerFactory.scala:97）
位于org.apache.spark.SparkEnv.createPythonWorker（SparkEnv.scala:117）
位于org.apache.spark.api.python.BasePythonRunner.compute（PythonRunner.scala:108）
位于org.apache.spark.api.python.PythonRDD.compute（PythonRDD.scala:65）
在org.apache.spark.rdd.rdd.computeOrReadCheckpoint（rdd.scala:324）
位于org.apache.spark.rdd.rdd.iterator（rdd.scala:288）
位于org.apache.spark.scheduler.ResultTask.runTask（ResultTask.scala:90）
位于org.apache.spark.scheduler.Task.run（Task.scala:121）
位于org.apache.spark.executor.executor$TaskRunner$$anonfun$10.apply（executor.scala:402）
位于org.apache.spark.util.Utils$.tryWithSafeFinally（Utils.scala:1360）
位于org.apache.spark.executor.executor$TaskRunner.run（executor.scala:408）
位于java.util.concurrent.ThreadPoolExecutor.runWorker（未知源）
位于java.util.concurrent.ThreadPoolExecutor$Worker.run（未知源）
位于java.lang.Thread.run（未知源）
原因：java.net.SocketTimeoutException:接受超时
位于java.net.DualStackPlainSocketImpl.waitForNewConnection（本机方法）
位于java.net.DualStackPlainSocketImpl.socketAccept（未知源）
位于java.net.AbstractPlainSocketImpl.accept（未知源）
位于java.net.PlainSocketImpl.accept（未知源）
位于java.net.ServerSocket.implacpt（未知源）
位于java.net.ServerSocket.accept（未知源）
位于org.apache.spark.api.PythonWorkerFactory.createSimpleWorker（PythonWorkerFactory.scala:164）
... 14多
驱动程序堆栈跟踪：
位于org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages（DAGScheduler.scala:1887）
位于org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply（DA
>>> import resource
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ModuleNotFoundError: No module named 'resource'

sc = spark.sparkContext