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From Krishna Kishore Bonagiri <write2kish...@gmail.com>
Subject Re: What else can be built on top of YARN.
Date Thu, 30 May 2013 06:42:17 GMT
Hi Rahul,

  It is at least because of the reasons that Vinod listed that makes my
life easy for porting my application on to YARN instead of making it work
in the Map Reduce framework. The main purpose of me using YARN is to
exploit the resource management capabilities of YARN.

Thanks,
Kishore


On Wed, May 29, 2013 at 11:00 PM, Rahul Bhattacharjee <
rahul.rec.dgp@gmail.com> wrote:

> Thanks for the response Krishna.
>
> I was wondering if it were possible for using MR to  solve you problem
> instead of building the whole stack on top of yarn.
> Most likely its not possible , thats why you are building it . I wanted to
> know why is that ?
>
> I am in just trying to find out the need or why we might need to write the
> application on yarn.
>
> Rahul
>
>
> On Wed, May 29, 2013 at 8:23 PM, Krishna Kishore Bonagiri <
> write2kishore@gmail.com> wrote:
>
>> Hi Rahul,
>>
>>   I am porting a distributed application that runs on a fixed set of
>> given resources to YARN, with the aim of  being able to run it on a
>> dynamically selected resources whichever are available at the time of
>> running the application.
>>
>> Thanks,
>> Kishore
>>
>>
>> On Wed, May 29, 2013 at 8:04 PM, Rahul Bhattacharjee <
>> rahul.rec.dgp@gmail.com> wrote:
>>
>>> Hi all,
>>>
>>> I was going through the motivation behind Yarn. Splitting the
>>> responsibility of JT is the major concern.Ultimately the base (Yarn) was
>>> built in a generic way for building other generic distributed applications
>>> too.
>>>
>>> I am not able to think of any other parallel processing use case that
>>> would be useful to built on top of YARN. I though of a lot of use cases
>>> that would be beneficial when run in parallel , but again ,we can do those
>>> using map only jobs in MR.
>>>
>>> Can someone tell me a scenario , where a application can utilize Yarn
>>> features or can be built on top of YARN and at the same time , it cannot be
>>> done efficiently using MRv2 jobs.
>>>
>>> thanks,
>>> Rahul
>>>
>>>
>>>
>>
>

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