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https://issues.apache.org/jira/browse/SPARK-12261?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15115433#comment-15115433
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Christopher Bourez commented on SPARK-12261:
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I think the issue is not resolved

I installed spark 1.6 on many different computers. 

On Windows, PySpark textfile method, followed by take(1), does not work on a 
file of 13M.
If I set numpartitions to 2000 or take a smaller file, the method works well. 
The Pyspark is set with all RAM memory of the computer thanks to the command 
--conf spark.driver.memory=5g in local mode. 

On Mac OS, I'm able to launch the exact same program with Pyspark with 16G RAM 
for a file of much bigger in comparison, of 5G. Memory is correctly allocated, 
removed etc 

On Ubuntu, no trouble, I can also launch a cluster 
http://christopher5106.github.io/big/data/2016/01/19/computation-power-as-you-need-with-EMR-auto-termination-cluster-example-random-forest-python.html
 

The error message on Windows is : java.net.SocketException: Connection reset by 
peer: socket write error 
What could be the reason to have the windows spark textfile method fail ?

> pyspark crash for large dataset
> -------------------------------
>
>                 Key: SPARK-12261
>                 URL: https://issues.apache.org/jira/browse/SPARK-12261
>             Project: Spark
>          Issue Type: Bug
>    Affects Versions: 1.5.2
>         Environment: windows
>            Reporter: zihao
>
> I tried to import a local text(over 100mb) file via textFile in pyspark, when 
> i ran data.take(), it failed and gave error messages including:
> 15/12/10 17:17:43 ERROR TaskSetManager: Task 0 in stage 0.0 failed 1 times; 
> aborting job
> Traceback (most recent call last):
>   File "E:/spark_python/test3.py", line 9, in <module>
>     lines.take(5)
>   File "D:\spark\spark-1.5.2-bin-hadoop2.6\python\pyspark\rdd.py", line 1299, 
> in take
>     res = self.context.runJob(self, takeUpToNumLeft, p)
>   File "D:\spark\spark-1.5.2-bin-hadoop2.6\python\pyspark\context.py", line 
> 916, in runJob
>     port = self._jvm.PythonRDD.runJob(self._jsc.sc(), mappedRDD._jrdd, 
> partitions)
>   File "C:\Anaconda2\lib\site-packages\py4j\java_gateway.py", line 813, in 
> __call__
>     answer, self.gateway_client, self.target_id, self.name)
>   File "D:\spark\spark-1.5.2-bin-hadoop2.6\python\pyspark\sql\utils.py", line 
> 36, in deco
>     return f(*a, **kw)
>   File "C:\Anaconda2\lib\site-packages\py4j\protocol.py", line 308, in 
> get_return_value
>     format(target_id, ".", name), value)
> py4j.protocol.Py4JJavaError: An error occurred while calling 
> z:org.apache.spark.api.python.PythonRDD.runJob.
> : 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): java.net.SocketException: Connection reset by peer: 
> socket write error
> Then i ran the same code for a small text file, this time .take() worked fine.
> How can i solve this problem?



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