M, Mennour Rostom <mennou...@gmail.com>
> wrote:
>
>> Hi,
>>
>> I am running my app in a single machine first before moving it in the
>> cluster; actually simultaneous actions are not working for me now; is this
>> comming from the fact that I am using a single mac
Hi,
I am running my app in a single machine first before moving it in the
cluster; actually simultaneous actions are not working for me now; is this
comming from the fact that I am using a single machine ? yet I am using
FAIR scheduler.
2016-01-17 21:23 GMT+01:00 Mark Hamstra &l
stacktrace? details?
On Mon, Jan 18, 2016 at 5:58 AM, Mennour Rostom <mennou...@gmail.com> wrote:
> Hi,
>
> I am running my app in a single machine first before moving it in the
> cluster; actually simultaneous actions are not working for me now; is this
> comming from the
ll be
> used to calculate simultaneous actions against the same RDD. It is likely
> that many of the same Workers and Executors will be used as the Scheduler
> tries to preserve data locality, but that is not guaranteed. In fact, what
> is most likely to happen is that the share
erform operations sequentially.
>>
>> As an alternative, I would suggest to restructure your RDD transformations
>> to compute the required results in one single operation.
>>
>> On 15 January 2016 at 06:18, Jonathan Coveney <jcove...@gmail.com
>> <m
Same SparkContext means same pool of Workers. It's up to the Scheduler,
not the SparkContext, whether the exact same Workers or Executors will be
used to calculate simultaneous actions against the same RDD. It is likely
that many of the same Workers and Executors will be used as the Scheduler
Executors will be
>> used to calculate simultaneous actions against the same RDD. It is likely
>> that many of the same Workers and Executors will be used as the Scheduler
>> tries to preserve data locality, but that is not guaranteed. In fact, what
>> is most likely to
the required results in one single operation.
>>>
>>> On 15 January 2016 at 06:18, Jonathan Coveney <jcove...@gmail.com>
>>> wrote:
>>>
>>>> Threads
>>>>
>>>>
>>>> El viernes, 15 de enero de 2016, Kira <mennou...@
ns on distributed data. Even if you were to call
>>>> actions from several threads at once, the individual executors of your
>>>> spark environment would still have to perform operations sequentially.
>>>>
>>>> As an alternative, I would suggest to restructur
Hi,
Can we run *simultaneous* actions on the *same RDD* ?; if yes how can this
be done ?
Thank you,
Regards
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Threads
El viernes, 15 de enero de 2016, Kira <mennou...@gmail.com> escribió:
> Hi,
>
> Can we run *simultaneous* actions on the *same RDD* ?; if yes how can this
> be done ?
>
> Thank you,
> Regards
>
>
>
> --
> View this message in context:
> http:/
operation.
>
> On 15 January 2016 at 06:18, Jonathan Coveney <jcove...@gmail.com> wrote:
>>
>> Threads
>>
>>
>> El viernes, 15 de enero de 2016, Kira <mennou...@gmail.com> escribió:
>>>
>>> Hi,
>>>
>>> Can we
com> wrote:
> Threads
>
>
> El viernes, 15 de enero de 2016, Kira <mennou...@gmail.com> escribió:
>
>> Hi,
>>
>> Can we run *simultaneous* actions on the *same RDD* ?; if yes how can this
>> be done ?
>>
>> Thank you,
>> Regards
>&g
es, 15 de enero de 2016, Kira <mennou...@gmail.com
>> <javascript:_e(%7B%7D,'cvml','mennou...@gmail.com');>> escribió:
>>
>>> Hi,
>>>
>>> Can we run *simultaneous* actions on the *same RDD* ?; if yes how can
>>> this
>>> be done ?
&g
gt; wrote:
> Threads
>
>
> El viernes, 15 de enero de 2016, Kira <mennou...@gmail.com
> <mailto:mennou...@gmail.com>> escribió:
> Hi,
>
> Can we run *simultaneous* actions on the *same RDD* ?; if yes how can this
> be done ?
>
> Thank you,
>
ucture your RDD transformations
> to compute the required results in one single operation.
>
> On 15 January 2016 at 06:18, Jonathan Coveney <jcove...@gmail.com> wrote:
>
>> Threads
>>
>>
>> El viernes, 15 de enero de 2016, Kira <mennou...@gmail.c
>> As an alternative, I would suggest to restructure your RDD
>> transformations to compute the required results in one single operation.
>>
>> On 15 January 2016 at 06:18, Jonathan Coveney <jcove...@gmail.com> wrote:
>>
>>> Threads
>>&
It makes sense if you're parallelizing jobs that have relatively few
tasks, and have a lot of execution slots available. It makes sense to
turn them loose all at once and try to use the parallelism available.
There are downsides, eventually: for example, N jobs accessing one
cached RDD may
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