Python 工作人员无法重新连接

Question

我是 Spark 新手，正在尝试完成 Spark 教程： link to tutorial

在本地机器（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，我正在尝试通过 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))

在从终端运行连接它之后：

spark-submit WordCount.py

我遇到以下错误。我检查（通过逐行注释）它在

处崩溃

wordCounts = words.countByValue()

知道我应该检查什么才能使其正常工作吗？

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.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.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.apply(DAGScheduler.scala:1875)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage.apply(DAGScheduler.scala:1874)
        at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
        at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1874)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed.apply(DAGScheduler.scala:926)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed.apply(DAGScheduler.scala:926)
        at scala.Option.foreach(Option.scala:257)
        at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2108)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2057)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2046)
        at org.apache.spark.util.EventLoop$$anon.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.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.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

根据 theplatypus 的建议 - 检查 'resource' 模块是否可以直接从终端导入 - 显然不能：

>>> import resource
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ModuleNotFoundError: No module named 'resource'

关于安装资源 - 我遵循了 this tutorial:

的说明

已从 Apache Spark website
解压到我的 C 盘
已经安装了 Python_3（Anaconda 发行版）以及 Java
创建了本地 'C:\hadoop\bin' 文件夹来存储 winutils.exe
创建了 'C:\tmp\hive' 文件夹并授予 Spark 访问权限
添加了环境变量（SPARK_HOME、HADOOP_HOME 等）

我应该安装任何额外的资源吗？

Answer 1

查看错误源（worker.py#L25), it seems that the python interpreter used to instanciate a pyspark worker doesn't have access to the resource module, a built-in module referred in Python's doc 作为 "Unix Specific Services" 的一部分。

你确定你可以运行在 Windows 上使用 pyspark（至少不需要一些额外的软件，比如 GOW 或 MingW），这样你就不会跳过一些 Windows-具体安装步骤 ?

你能打开一个 python 控制台（pyspark 使用的那个），看看你是否可以 >>> import resource 而不会得到相同的 ModuleNotFoundError ？如果你不这样做，那么你能提供你用来在 W10 上安装它的资源吗？

Answer 2

我遇到了同样的错误。我解决了它安装以前版本的 Spark（2.3 而不是 2.4）。现在完美运行了，可能是pyspark最新版本的问题。

Answer 3

将 Spark 从 2.4.0 降级回 2.3.2 对我来说还不够。我不知道为什么，但在我的例子中，我必须从 SparkSession 创建 SparkContext，比如

sc = spark.sparkContext

然后同样的错误消失了。

Answer 4

问题的核心是pyspark和python之间的连接问题，通过重新定义环境变量解决

我刚刚将环境变量的值 PYSPARK_DRIVER_PYTHON 从 ipython 更改为 jupyter，将 PYSPARK_PYTHON 从 python3 更改为 python。

现在我正在使用 Jupyter Notebook，Python 3.7，Java JDK 11.0.6，Spark 2.4.2

Answer 5

设置环境 PYSPARK_PYTHON=python 进行修复。

Answer 6

当您运行安装 python 安装程序时，在自定义 Python 部分，确保选择添加 python.exe 到路径选项。如果未选择此选项，则某些 PySpark 实用程序（例如 pyspark 和 spark-submit）可能无法运行。这对我有用！分享快乐:)

Answer 7

出现这个错误的原因似乎有很多。尽管我的 environmental variables 设置正确，但我仍然遇到同样的问题。

在我的例子中添加这个

import findspark
findspark.init()

解决了问题。

我和 jupyter notebook 在 windows10 和 spark-3.1.2, python3.6。

Answer 8

我遇到了同样的问题。我已经正确设置了所有 environment variables 但仍然无法解决它

就我而言，

import findspark
findspark.init()

在创建 sparkSession 之前添加这个很有帮助。

我在 Windows 10 上使用 Visual Studio Code，spark 版本是 3.2.0。 Python 版本是 3.9 .

注意：首先检查 HADOOP_HOME SPARK_HOME PYSPARK_PYTHON 的路径是否设置正确

Python 工作人员无法重新连接

Python worker failed to connect back

python

windows

local

apache-spark

pyspark