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https://issues.apache.org/jira/browse/SPARK-5004?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-5004.
---------------------------------
    Resolution: Incomplete

> PySpark does not handle SOCKS proxy
> -----------------------------------
>
>                 Key: SPARK-5004
>                 URL: https://issues.apache.org/jira/browse/SPARK-5004
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 1.2.0, 1.3.0
>            Reporter: Eric O. LEBIGOT (EOL)
>            Priority: Major
>              Labels: bulk-closed
>
> PySpark cannot run even the quick start examples when a SOCKS proxy is used. 
> Turning off the SOCKS proxy makes PySpark work.
> The Scala-shell version is not affected and works even when a SOCKS proxy is 
> used.
> Is there a quick workaround, while waiting for this to be fixed?
> Here is the error message (printed, e.g., when .count() is called):
> {code}
> >>> 14/12/30 17:13:44 WARN PythonWorkerFactory: Failed to open socket to 
> >>> Python daemon:
> java.net.SocketException: Malformed reply from SOCKS server
>         at java.net.SocksSocketImpl.readSocksReply(SocksSocketImpl.java:129)
>         at java.net.SocksSocketImpl.connect(SocksSocketImpl.java:503)
>         at java.net.Socket.connect(Socket.java:579)
>         at java.net.Socket.connect(Socket.java:528)
>         at java.net.Socket.<init>(Socket.java:425)
>         at java.net.Socket.<init>(Socket.java:241)
>         at 
> org.apache.spark.api.python.PythonWorkerFactory.createSocket$1(PythonWorkerFactory.scala:75)
>         at 
> org.apache.spark.api.python.PythonWorkerFactory.liftedTree1$1(PythonWorkerFactory.scala:90)
>         at 
> org.apache.spark.api.python.PythonWorkerFactory.createThroughDaemon(PythonWorkerFactory.scala:89)
>         at 
> org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:62)
>         at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:102)
>         at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
>         at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
>         at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
>         at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
>         at org.apache.spark.scheduler.Task.run(Task.scala:56)
>         at 
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
>         at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>         at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>         at java.lang.Thread.run(Thread.java:724)
> {code}



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