Thank you for your response!

I guess the (Spark)AM, who gives the container leash to the NM (along with
the executor JAR and command to run) must know how many CPU or RAM that
container capped, isolated at. There must be a resource vector along the
encrypted container leash if I'm right that describes this. Or maybe is
there a way for the ExecutorBackend to fetch this information directly from
the environment? Then, the ExecutorBackend would be able to hand over this
information to the actual Executor who creates the TaskRunner.

Zvara Zoltán



mail, hangout, skype: zoltan.zv...@gmail.com

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2015-03-24 16:30 GMT+01:00 Sandy Ryza <sandy.r...@cloudera.com>:

> Hi Zoltan,
>
> If running on YARN, the YARN NodeManager starts executors.  I don't think
> there's a 100% precise way for the Spark executor way to know how many
> resources are allotted to it.  It can come close by looking at the Spark
> configuration options used to request it (spark.executor.memory and
> spark.yarn.executor.memoryOverhead), but it can't necessarily for the
> amount that YARN has rounded up if those configuration properties
> (yarn.scheduler.minimum-allocation-mb and
> yarn.scheduler.increment-allocation-mb) are not present on the node.
>
> -Sandy
>
> -Sandy
>
> On Mon, Mar 23, 2015 at 5:08 PM, Zoltán Zvara <zoltan.zv...@gmail.com>
> wrote:
>
>> Let's say I'm an Executor instance in a Spark system. Who started me and
>> where, when I run on a worker node supervised by (a) Mesos, (b) YARN? I
>> suppose I'm the only one Executor on a worker node for a given framework
>> scheduler (driver). If I'm an Executor instance, who is the closest object
>> to me who can tell me how many resources do I have on (a) Mesos, (b) YARN?
>>
>> Thank you for your kind input!
>>
>> Zvara Zoltán
>>
>>
>>
>> mail, hangout, skype: zoltan.zv...@gmail.com
>>
>> mobile, viber: +36203129543
>>
>> bank: 10918001-00000021-50480008
>>
>> address: Hungary, 2475 Kápolnásnyék, Kossuth 6/a
>>
>> elte: HSKSJZ (ZVZOAAI.ELTE)
>>
>
>

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