pyspark的运行问题

pyspark配置完成之后在pycharm中运行失败

遇到的现象和发生背景，请写出第一个错误信息

这是代码

from pyspark import SparkConf, SparkContext

conf = SparkConf().setAppName("WordCount").setMaster("local")
sc = SparkContext(conf=conf)
inputFile = "word.txt"
textFile = sc.textFile(inputFile)
wordCount = textFile.flatMap(lambda line: line.split(" ")).map(lambda word: (word, 1)).reduceByKey(lambda a, b: a + b)
wordCount.foreach(print)
下面这一段是报错信息，有大佬帮我看看
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Traceback (most recent call last):
  File "E:\ProgramData\anaconda3\lib\runpy.py", line 187, in _run_module_as_main
    mod_name, mod_spec, code = _get_module_details(mod_name, _Error)
  File "E:\ProgramData\anaconda3\lib\runpy.py", line 110, in _get_module_details
    __import__(pkg_name)
  File "E:\hadoop\spark-2.4.3-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\__init__.py", line 51, in <module>
  File "E:\hadoop\spark-2.4.3-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\context.py", line 31, in <module>
  File "E:\hadoop\spark-2.4.3-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\accumulators.py", line 97, in <module>
  File "E:\hadoop\spark-2.4.3-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\serializers.py", line 71, in <module>
  File "E:\hadoop\spark-2.4.3-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\cloudpickle.py", line 145, in <module>
  File "E:\hadoop\spark-2.4.3-bin-hadoop2.7\python\lib\pyspark.zip\pyspark\cloudpickle.py", line 126, in _make_cell_set_template_code
TypeError: 'bytes' object cannot be interpreted as an integer
[Stage 0:>                                                          (0 + 1) / 1]23/06/01 12:52:30 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.api.python.PairwiseRDD.compute(PythonRDD.scala:103)
    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.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
    at org.apache.spark.scheduler.Task.run(Task.scala:121)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
    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:131)
    at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:535)
    at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:189)
    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)
    ... 18 more
23/06/01 12:52:30 WARN TaskSetManager: 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.api.python.PairwiseRDD.compute(PythonRDD.scala:103)
    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.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
    at org.apache.spark.scheduler.Task.run(Task.scala:121)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$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:131)
    at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:535)
    at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:189)
    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)
    ... 18 more

23/06/01 12:52:30 ERROR TaskSetManager: Task 0 in stage 0.0 failed 1 times; aborting job
Traceback (most recent call last):
  File "C:\Users\。\PycharmProjects\pythonProject7\test.py", line 8, in <module>
    wordCount.foreach(print)
  File "E:\ProgramData\anaconda3\envs\new\lib\site-packages\pyspark\rdd.py", line 789, in foreach
    self.mapPartitions(processPartition).count()  # Force evaluation
  File "E:\ProgramData\anaconda3\envs\new\lib\site-packages\pyspark\rdd.py", line 1055, in count
    return self.mapPartitions(lambda i: [sum(1 for _ in i)]).sum()
  File "E:\ProgramData\anaconda3\envs\new\lib\site-packages\pyspark\rdd.py", line 1046, in sum
    return self.mapPartitions(lambda x: [sum(x)]).fold(0, operator.add)
  File "E:\ProgramData\anaconda3\envs\new\lib\site-packages\pyspark\rdd.py", line 917, in fold
    vals = self.mapPartitions(func).collect()
  File "E:\ProgramData\anaconda3\envs\new\lib\site-packages\pyspark\rdd.py", line 816, in collect
    sock_info = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
  File "E:\ProgramData\anaconda3\envs\new\lib\site-packages\py4j\java_gateway.py", line 1323, in __call__
    answer, self.gateway_client, self.target_id, self.name)
  File "E:\ProgramData\anaconda3\envs\new\lib\site-packages\py4j\protocol.py", line 328, in get_return_value
    format(target_id, ".", name), 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.api.python.PairwiseRDD.compute(PythonRDD.scala:103)
    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.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
    at org.apache.spark.scheduler.Task.run(Task.scala:121)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$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:131)
    at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:535)
    at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:189)
    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)
    ... 18 more

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1889)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1877)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1876)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1876)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
    at scala.Option.foreach(Option.scala:257)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2110)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2059)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2048)
    at org.apache.spark.util.EventLoop$$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(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.api.python.PairwiseRDD.compute(PythonRDD.scala:103)
    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.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
    at org.apache.spark.scheduler.Task.run(Task.scala:121)
    at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
    at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$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:131)
    at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:535)
    at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:189)
    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)
    ... 18 more

本地环境变量截图看一眼

• 帮你找了个相似的问题, 你可以看下: https://ask.csdn.net/questions/7762037
• 我还给你找了一篇非常好的博客，你可以看看是否有帮助，链接：pycharm中使用pyspark
• 除此之外, 这篇博客: pycharm配置pyspark环境中的 pycharm配置pyspark环境 部分也许能够解决你的问题, 你可以仔细阅读以下内容或跳转源博客中阅读:
  

• 参考这篇博客， 比较靠谱：
  https://blog.csdn.net/ringsuling/article/details/84448369
  用到的配置环境变量：
  还没配置成功

  #spark的安装位置
  C:\file\spark_package\spark-2.4.4-bin-hadoop2.7
  将
  C:\file\spark_package\spark-2.4.4-bin-hadoop2.7\python\pyspark
  拷贝到
  C:\Users\Carry Wan\AppData\Local\Programs\Python\Python37-32\Lib\site-packages
  
  拷贝过去
  C:\Users\Carry Wan\AppData\Local\Programs\Python\Python37-32\Lib\site-packages\pyspark
  
  SPARK_HOME   C:\file\spark_package\spark-2.4.4-bin-hadoop2.7
  PYTHONPATH   C:\file\spark_package\spark-2.4.4-bin-hadoop2.7\python
  
  pip install py4j 
  
  
  JAVA_HOME    C:\Program Files\Java\jdk1.8.0_162\bin
  
  添加
  C:\file\spark_package\spark-2.4.4-bin-hadoop2.7\python\lib\py4j-0.10.7-src.zip
  C:\file\spark_package\spark-2.4.4-bin-hadoop2.7\python\lib\pyspark.zip
  
  
  
  

• 您还可以看一下 任大勇老师的PySpark机器学习从入门到精通课程中的 特征选取：卡方选择器小节, 巩固相关知识点