k release are you running ?
>
> Cheers
>
> On Mon, Jan 19, 2015 at 12:04 PM, suresh wrote:
>
>> I am trying to run SparkR shell on aws
>>
>> I am unable to access worker nodes webUI access.
>>
>> 15/01/19 19:57:17 ERROR TaskSchedulerImpl: Lost an executor
am trying to run SparkR shell on aws
>>
>> I am unable to access worker nodes webUI access.
>>
>> 15/01/19 19:57:17 ERROR TaskSchedulerImpl: Lost an executor 0 (already
>> removed): remote Akka client disassociated
>> 15/01/19 19:57:17 ERROR TaskSched
19:57:17 ERROR TaskSchedulerImpl: Lost an executor 0 (already
> removed): remote Akka client disassociated
> 15/01/19 19:57:17 ERROR TaskSchedulerImpl: Lost an executor 1 (already
> removed): remote Akka client disassociated
> 15/01/19 19:57:17 ERROR TaskSchedulerImpl: Lost an executor 2 (already
>
I am trying to run SparkR shell on aws
I am unable to access worker nodes webUI access.
15/01/19 19:57:17 ERROR TaskSchedulerImpl: Lost an executor 0 (already
removed): remote Akka client disassociated
15/01/19 19:57:17 ERROR TaskSchedulerImpl: Lost an executor 1 (already
removed): remote Akka
.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
> at
> scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
> at
>
> scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
>
>
>
> --
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>
doesn't even get to the algorithm portion because it breaks at
graph.edges.count when it reads the data...
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.java:1979)
at
scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
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Sent from the Ap
orkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
> at
> scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
> at
>
> scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
>
>
>
> --
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>
1979)
> at
>
> scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
>
>
>
> --
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t;
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Worker(ForkJoinPool.java:1979)
> at
>
> scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
>
>
>
> --
> View this message in context:
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ext:
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On Wed, Apr 23, 2014 at 12:06 AM, jaeholee wrote:
> How do you determine the number of partitions? For example, I have 16
> workers, and the number of cores and the worker memory set in spark-env.sh
> are:
>
> CORE = 8
> MEMORY = 16g
>
So you have the capacity to work on 16 * 8 = 128 tasks at a
spark-env.sh different from spark.executor.memory
that you mentioned? If they're different, how do I set
spark.executor.memory?
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gt;
> scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
>
>
>
> --
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>
:107)
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-user-list.1001560.n3.nabble.com/ERROR-TaskSchedulerImpl-Lost-an-executor-tp4566p4615.html
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hat
> error message.
>
> Sorry if it got more confusing..
>
>
>
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I get this
> message:
>
> 14/04/21 16:31:51 ERROR TaskSchedulerImpl: Lost an executor 1 (already
> removed): remote Akka client disassociated
> 14/04/21 16:31:51 ERROR TaskSchedulerImpl: Lost an executor 2 (already
> removed): remote Akka client disassociated
> 14/04/21 16:31
Hi, I am trying to set up my own standalone Spark, and I started the master
node and worker nodes. Then I ran ./bin/spark-shell, and I get this message:
14/04/21 16:31:51 ERROR TaskSchedulerImpl: Lost an executor 1 (already
removed): remote Akka client disassociated
14/04/21 16:31:51 ERROR
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