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From Pavel Plotnikov <pavel.plotni...@team.wrike.com>
Subject Re: Spark on Mesos - Weird behavior
Date Wed, 11 Jul 2018 14:22:14 GMT
Oh, sorry, i missed that you use spark without dynamic allocation. Anyway,
i don't know does this parameters works without dynamic allocation.

On Wed, Jul 11, 2018 at 5:11 PM Thodoris Zois <zois@ics.forth.gr> wrote:

> Hello,
>
> Yeah you are right, but I think that works only if you use Spark dynamic
> allocation. Am I wrong?
>
> -Thodoris
>
> On 11 Jul 2018, at 17:09, Pavel Plotnikov <pavel.plotnikov@team.wrike.com>
> wrote:
>
> Hi, Thodoris
> You can configure resources per executor and manipulate with number of
> executers instead using spark.max.cores. I think spark.dynamicAllocation.minExecutors
> and spark.dynamicAllocation.maxExecutors configuration values can help
> you.
>
> On Tue, Jul 10, 2018 at 5:07 PM Thodoris Zois <zois@ics.forth.gr> wrote:
>
>> Actually after some experiments we figured out that spark.max.cores /
>> spark.executor.cores is the upper bound for the executors. Spark apps will
>> run even only if one executor can be launched.
>>
>> Is there any way to specify also the lower bound? It is a bit annoying
>> that seems that we can’t control the resource usage of an application. By
>> the way, we are not using dynamic allocation.
>>
>> - Thodoris
>>
>>
>> On 10 Jul 2018, at 14:35, Pavel Plotnikov <pavel.plotnikov@team.wrike.com>
>> wrote:
>>
>> Hello Thodoris!
>> Have you checked this:
>>  - does mesos cluster have available resources?
>>   - if spark have waiting tasks in queue more than
>> spark.dynamicAllocation.schedulerBacklogTimeout configuration value?
>>  - And then, have you checked that mesos send offers to spark app mesos
>> framework at least with 10 cores and 2GB RAM?
>>
>> If mesos have not available offers with 10 cores, for example, but have
>> with 8 or 9, so you can use smaller executers for better fit for available
>> resources on nodes for example with 4 cores and 1 GB RAM, for example
>>
>> Cheers,
>> Pavel
>>
>> On Mon, Jul 9, 2018 at 9:05 PM Thodoris Zois <zois@ics.forth.gr> wrote:
>>
>>> Hello list,
>>>
>>> We are running Apache Spark on a Mesos cluster and we face a weird
>>> behavior of executors. When we submit an app with e.g 10 cores and 2GB of
>>> memory and max cores 30, we expect to see 3 executors running on the
>>> cluster. However, sometimes there are only 2... Spark applications are not
>>> the only one that run on the cluster. I guess that Spark starts executors
>>> on the available offers even if it does not satisfy our needs. Is there any
>>> configuration that we can use in order to prevent Spark from starting when
>>> there are no resource offers for the total number of executors?
>>>
>>> Thank you
>>> - Thodoris
>>>
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>>>
>>>
>

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