We   are using spark in  two  ways 
1. Yarn with spark support. Kafka running along with  data nodes 
2.  Spark master and workers  running  with  some  of  Kafka brokers. 
Data locality is  important.

Regards
Diwakar 


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<div>-------- Original message --------</div><div>From: أنس الليثي 
<[email protected]> </div><div>Date:08/02/2016  02:07  (GMT+05:30) 
</div><div>To: Diwakar Dhanuskodi <[email protected]> </div><div>Cc: 
"Yuval.Itzchakov" <[email protected]>, user <[email protected]> 
</div><div>Subject: Re: Apache Spark data locality when integrating with Kafka 
</div><div>
</div>Diwakar 

We have our own servers. We will not use any cloud service like Amazon's 

On 7 February 2016 at 18:24, Diwakar Dhanuskodi <[email protected]> 
wrote:
Fanoos, 
Where  you  want the solution to  be deployed ?. On premise or cloud?

Regards 
Diwakar .



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-------- Original message --------
From: "Yuval.Itzchakov" <[email protected]>
Date:07/02/2016 19:38 (GMT+05:30)
To: [email protected]
Cc:
Subject: Re: Apache Spark data locality when integrating with Kafka

I would definitely try to avoid hosting Kafka and Spark on the same servers. 

Kafka and Spark will be doing alot of IO between them, so you'll want to
maximize on those resources and not share them on the same server. You'll
want each Kafka broker to be on a dedicated server, as well as your spark
master and workers. If you're hosting them on Amazon EC2 instances, then
you'll want these to be on the same availability zone, so you can benefit
from low latency in that same zone. If you're on a dedicated servers,
perhaps you'll want to create a VPC between the two clusters so you can,
again, benefit from low IO latency and high throughput.



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