16/05/19 15:51:39 WARN CoarseGrainedExecutorBackend: An unknown
(ip-10-171-80-97.ec2.internal:44765) driver disconnected.
16/05/19 15:51:42 ERROR TransportClient: Failed to send RPC
5466711974642652953 to ip-10-171-80-97.ec2.internal/10.171.80.97:44765:
java.nio.channels.ClosedChannelException
java.nio.channels.ClosedChannelException

Can you check the log for ip-10-171-80-97.ec2.internal to see if there was
some clue ?

Cheers

On Thu, May 19, 2016 at 9:24 AM, Geet Kumar <[email protected]> wrote:

> Ah, it seems the code did not show up in the email. Here is a link to the
> original post:
> http://apache-spark-user-list.1001560.n3.nabble.com/Latency-experiment-without-losing-executors-td26981.html
>
> Also, attached is the executor logs.​
>  spark-logging.log
> <https://drive.google.com/a/hawk.iit.edu/file/d/0B6naIKwXOhAUVjNLSTlkTGhnM3c/view?usp=drive_web>
> ​
>
> Geet Kumar
> DataSys Laboratory, CS/IIT
> Linguistic Cognition Laboratory, CS/IIT
> Department of Computer Science, Illinois Institute of Technology (IIT)
> Email: [email protected]
>
>
> On Thu, May 19, 2016 at 3:23 AM, Ted Yu <[email protected]> wrote:
>
>> I didn't see the code snippet. Were you using picture(s) ?
>>
>> Please pastebin the code.
>>
>> It would be better if you pastebin executor log for the killed executor.
>>
>> Thanks
>>
>> On Wed, May 18, 2016 at 9:41 PM, gkumar7 <[email protected]> wrote:
>>
>>> I would like to test the latency (tasks/s) perceived in a simple
>>> application
>>> on Apache Spark.
>>>
>>> The idea: The workers will generate random data to be placed in a list.
>>> The
>>> final action (count) will count the total number of data points
>>> generated.
>>>
>>> Below, the numberOfPartitions is equal to the number of datapoints which
>>> need to be generated (datapoints are integers).
>>>
>>> Although the code works as expected, a total of 119 spark executors were
>>> killed while running with 64 slaves. I feel this is because since spark
>>> assigns executors to each node, the amount of total partitions each node
>>> is
>>> assigned to compute may be larger than the available memory on that node.
>>> This causes these executors to be killed and therefore, the latency
>>> measurement I would like to analyze is inaccurate.
>>>
>>> Any assistance with code cleanup below or how to fix the above issue to
>>> decrease the number of killed executors, would be much appreciated.
>>>
>>>
>>>
>>>
>>>
>>> --
>>> View this message in context:
>>> http://apache-spark-user-list.1001560.n3.nabble.com/Latency-experiment-without-losing-executors-tp26981.html
>>> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>>>
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>>> To unsubscribe, e-mail: [email protected]
>>> For additional commands, e-mail: [email protected]
>>>
>>>
>>
>

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