Actually I met similar issue when doing groupByKey and then count if the 
shuffle size is big e.g. 1tb.

Thanks.

Zhan Zhang

Sent from my iPhone

> On Sep 21, 2014, at 10:56 PM, Nishkam Ravi <nr...@cloudera.com> wrote:
> 
> Thanks for the quick follow up Reynold and Patrick. Tried a run with
> significantly higher ulimit, doesn't seem to help. The executors have 35GB
> each. Btw, with a recent version of the branch, the error message is "fetch
> failures" as opposed to "too many open files". Not sure if they are
> related.  Please note that the workload runs fine with head set to 066765d.
> In case you want to reproduce the problem: I'm running slightly modified
> ScalaPageRank (with KryoSerializer and persistence level
> memory_and_disk_ser) on a 30GB input dataset and a 6-node cluster.
> 
> Thanks,
> Nishkam
> 
> On Sun, Sep 21, 2014 at 10:32 PM, Patrick Wendell <pwend...@gmail.com>
> wrote:
> 
>> Ah I see it was SPARK-2711 (and PR1707). In that case, it's possible
>> that you are just having more spilling as a result of the patch and so
>> the filesystem is opening more files. I would try increasing the
>> ulimit.
>> 
>> How much memory do your executors have?
>> 
>> - Patrick
>> 
>> On Sun, Sep 21, 2014 at 10:29 PM, Patrick Wendell <pwend...@gmail.com>
>> wrote:
>>> Hey the numbers you mentioned don't quite line up - did you mean PR 2711?
>>> 
>>> On Sun, Sep 21, 2014 at 8:45 PM, Reynold Xin <r...@databricks.com>
>> wrote:
>>>> It seems like you just need to raise the ulimit?
>>>> 
>>>> 
>>>> On Sun, Sep 21, 2014 at 8:41 PM, Nishkam Ravi <nr...@cloudera.com>
>> wrote:
>>>> 
>>>>> Recently upgraded to 1.1.0. Saw a bunch of fetch failures for one of
>> the
>>>>> workloads. Tried tracing the problem through change set analysis. Looks
>>>>> like the offending commit is 4fde28c from Aug 4th for PR1707. Please
>> see
>>>>> SPARK-3633 for more details.
>>>>> 
>>>>> Thanks,
>>>>> Nishkam
>> 

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