Python worker 连接失败

问题描述 投票：0回答：10

我正在尝试完成这个 Spark 教程。

在本地机器（Win10 64、Python 3、Spark 2.4.0）上安装 Spark 并设置所有环境变量（HADOOP_HOME、SPARK_HOME 等）后，我正在尝试运行一个简单的

WordCount.py
Spark 应用程序：

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))

从命令行运行后：

spark-submit WordCount.py

我得到以下错误。 我检查（通过逐行注释）它崩溃了

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$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

正如 theplatypus 所建议的那样 - 检查是否可以直接从终端导入“资源”模块 - 显然不是：

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

在安装资源方面-我遵循了本教程的说明：

  1. 从 Apache Spark 网站下载 spark-2.4.0-bin-hadoop2.7.tgz
  2. 解压缩到我的 C 盘
  3. 已经安装了 Python_3（Anaconda 发行版）以及 Java
  4. 创建本地“C:\hadoop in”文件夹来存储 winutils.exe
  5. 创建“C: mp\hive”文件夹并授予 Spark 访问权限
  6. 添加环境变量（SPARK_HOME、HADOOP_HOME 等）

我应该安装任何额外的资源吗？

python windows apache-spark pyspark local
10个回答
20
投票

设置 Env PYSPARK_PYTHON=python 来修复它。

18
投票

我得到了同样的错误。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

15
投票

问题的核心是pyspark和python的连接，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
和 
PYSPARK_PYTHON
从 
python3
到 
python
.

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

14
投票

我有同样的问题。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 之前添加这个有帮助。

我在

Visual Studio Code
上使用
Windows 10
，而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

3
投票

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。

1
投票

查看错误源（worker.py#L25），似乎用于实例化pyspark worker的python解释器无法访问

resource
模块，这是中提到的内置模块Python 的文档 作为“Unix 特定服务”的一部分。

你确定你可以在 Windows 上运行 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特定于 Windows 的安装步骤吗？

你能打开一个 python 控制台（pyspark 使用的那个）并看看你是否可以 

>>> import resource
而不会得到相同的 
ModuleNotFoundError
吗？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？

1
投票

当您运行 python 安装程序时，在自定义 Python 部分，确保选择将 python.exe 添加到路径选项。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！快乐分享:)

0
投票

出现这个错误的原因好像有很多。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
.

0
投票

我必须设置：

  • HADOOP_HOME = [..]\winutils\hadoop-3.0.0
  • PATH = [..]\winutils\hadoop-3.0.0\bin
  • PYSPARK_PYTHON = python

你可以找到 winutils here。我用

Hadoop 3.0.0
和
PySpark 3.2.1
.

0
投票

这个错误的原因是pyspark和python之间的连接没有正确建立

解决方案： 将 

PYSPARK_PYTHON
环境变量设置为 
python
.

注意：添加环境变量后一定要重启cmd或shell

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