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https://issues.apache.org/jira/browse/SPARK-12980?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Christopher Bourez updated SPARK-12980:
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Description:
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
What could be the reason to have the windows spark textfile method fail ?
was:
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?
> pyspark crash for large dataset - clone
> ---------------------------------------
>
> Key: SPARK-12980
> URL: https://issues.apache.org/jira/browse/SPARK-12980
> Project: Spark
> Issue Type: Bug
> Affects Versions: 1.5.2
> Environment: windows
> Reporter: Christopher Bourez
>
> 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
> What could be the reason to have the windows spark textfile method fail ?
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