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Posted to user@spark.apache.org by Tian Zhang <tz...@yahoo.com> on 2015/10/09 00:22:35 UTC

Re: "Too many open files" exception on reduceByKey

I hit this issue with spark 1.3.0 stateful application (with
updateStateByKey) function on mesos.  It will 
fail after running fine for about 24 hours.
The error stack trace as below, I checked ulimit -n and we have very large
numbers set on the machines.
What else can be wrong?
15/09/27 18:45:11 WARN scheduler.TaskSetManager: Lost task 2.0 in stage
113727.0 (TID 833758, ip-10-112-10-221.ec2.internal):
java.io.FileNotFoundException:
/media/ephemeral0/oncue/mesos-slave/slaves/20150512-215537-2165010442-5050-1730-S5/frameworks/20150825-175705-2165010442-5050-13705-0338/executors/0/runs/19342849-d076-483c-88da-747896e19b93/./spark-6efa2dcd-aea7-478e-9fa9-6e0973578eb4/blockmgr-33b1e093-6dd6-4462-938c-2597516272a9/27/shuffle_535_2_0.index
(Too many open files)
        at java.io.FileOutputStream.open(Native Method)
        at java.io.FileOutputStream.<init>(FileOutputStream.java:221)
        at java.io.FileOutputStream.<init>(FileOutputStream.java:171)
        at
org.apache.spark.shuffle.IndexShuffleBlockManager.writeIndexFile(IndexShuffleBlockManager.scala:85)
        at
org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:69)
        at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
        at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
        at org.apache.spark.scheduler.Task.run(Task.scala:64)
        at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
        at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:745)





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Re: "Too many open files" exception on reduceByKey

Posted by tian zhang <tz...@yahoo.com.INVALID>.
You are right, I did find that mesos overwrite this to a smaller number.So we will modify that and try to run again. Thanks!
Tian 


     On Thursday, October 8, 2015 4:18 PM, DB Tsai <db...@dbtsai.com> wrote:
   

 Try to run to see actual ulimit. We found that mesos overrides the ulimit which causes the issue.
import sys.process._
val p = 1 to 100
val rdd = sc.parallelize(p, 100)
val a = rdd.map(x=> Seq("sh", "-c", "ulimit -n").!!.toDouble.toLong).collect



Sincerely,

DB Tsai
----------------------------------------------------------Blog: https://www.dbtsai.com
PGP Key ID: 0xAF08DF8D

On Thu, Oct 8, 2015 at 3:22 PM, Tian Zhang <tz...@yahoo.com> wrote:

I hit this issue with spark 1.3.0 stateful application (with
updateStateByKey) function on mesos.  It will
fail after running fine for about 24 hours.
The error stack trace as below, I checked ulimit -n and we have very large
numbers set on the machines.
What else can be wrong?
15/09/27 18:45:11 WARN scheduler.TaskSetManager: Lost task 2.0 in stage
113727.0 (TID 833758, ip-10-112-10-221.ec2.internal):
java.io.FileNotFoundException:
/media/ephemeral0/oncue/mesos-slave/slaves/20150512-215537-2165010442-5050-1730-S5/frameworks/20150825-175705-2165010442-5050-13705-0338/executors/0/runs/19342849-d076-483c-88da-747896e19b93/./spark-6efa2dcd-aea7-478e-9fa9-6e0973578eb4/blockmgr-33b1e093-6dd6-4462-938c-2597516272a9/27/shuffle_535_2_0.index
(Too many open files)
        at java.io.FileOutputStream.open(Native Method)
        at java.io.FileOutputStream.<init>(FileOutputStream.java:221)
        at java.io.FileOutputStream.<init>(FileOutputStream.java:171)
        at
org.apache.spark.shuffle.IndexShuffleBlockManager.writeIndexFile(IndexShuffleBlockManager.scala:85)
        at
org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:69)
        at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
        at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
        at org.apache.spark.scheduler.Task.run(Task.scala:64)
        at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
        at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:745)





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Re: "Too many open files" exception on reduceByKey

Posted by DB Tsai <db...@dbtsai.com>.
Try to run to see actual ulimit. We found that mesos overrides the ulimit
which causes the issue.

import sys.process._
val p = 1 to 100
val rdd = sc.parallelize(p, 100)
val a = rdd.map(x=> Seq("sh", "-c", "ulimit -n").!!.toDouble.toLong).collect




Sincerely,

DB Tsai
----------------------------------------------------------
Blog: https://www.dbtsai.com
PGP Key ID: 0xAF08DF8D
<https://pgp.mit.edu/pks/lookup?search=0x59DF55B8AF08DF8D>

On Thu, Oct 8, 2015 at 3:22 PM, Tian Zhang <tz...@yahoo.com> wrote:

> I hit this issue with spark 1.3.0 stateful application (with
> updateStateByKey) function on mesos.  It will
> fail after running fine for about 24 hours.
> The error stack trace as below, I checked ulimit -n and we have very large
> numbers set on the machines.
> What else can be wrong?
> 15/09/27 18:45:11 WARN scheduler.TaskSetManager: Lost task 2.0 in stage
> 113727.0 (TID 833758, ip-10-112-10-221.ec2.internal):
> java.io.FileNotFoundException:
>
> /media/ephemeral0/oncue/mesos-slave/slaves/20150512-215537-2165010442-5050-1730-S5/frameworks/20150825-175705-2165010442-5050-13705-0338/executors/0/runs/19342849-d076-483c-88da-747896e19b93/./spark-6efa2dcd-aea7-478e-9fa9-6e0973578eb4/blockmgr-33b1e093-6dd6-4462-938c-2597516272a9/27/shuffle_535_2_0.index
> (Too many open files)
>         at java.io.FileOutputStream.open(Native Method)
>         at java.io.FileOutputStream.<init>(FileOutputStream.java:221)
>         at java.io.FileOutputStream.<init>(FileOutputStream.java:171)
>         at
>
> org.apache.spark.shuffle.IndexShuffleBlockManager.writeIndexFile(IndexShuffleBlockManager.scala:85)
>         at
>
> org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:69)
>         at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
>         at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
>         at org.apache.spark.scheduler.Task.run(Task.scala:64)
>         at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
>         at
>
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>         at
>
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>         at java.lang.Thread.run(Thread.java:745)
>
>
>
>
>
> --
> View this message in context:
> http://apache-spark-user-list.1001560.n3.nabble.com/Too-many-open-files-exception-on-reduceByKey-tp2462p24985.html
> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>
> ---------------------------------------------------------------------
> To unsubscribe, e-mail: user-unsubscribe@spark.apache.org
> For additional commands, e-mail: user-help@spark.apache.org
>
>

Re: "Too many open files" exception on reduceByKey

Posted by Tian Zhang <tz...@yahoo.com>.
It turns out the mesos can overwrite the OS ulimit -n setting. So we have
increased the mesos slave ulimit -n setting.



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