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[50.46.126.28]) by smtp.gmail.com with ESMTPSA id f9sm9376204pfj.56.2017.02.15.14.48.38 for (version=TLS1_2 cipher=ECDHE-RSA-AES128-GCM-SHA256 bits=128/128); Wed, 15 Feb 2017 14:48:38 -0800 (PST) Subject: Re: Write-up about REEF as a library To: dev@reef.apache.org References: <047d7e95-7a34-5656-89e1-d2ab797d7044@weimo.de> From: Markus Weimer Message-ID: <9c8fe2c7-b536-3eda-a750-8292fc6d7b49@weimo.de> Date: Wed, 15 Feb 2017 14:48:38 -0800 User-Agent: Mozilla/5.0 (Windows NT 10.0; WOW64; rv:45.0) Gecko/20100101 Thunderbird/45.7.1 MIME-Version: 1.0 In-Reply-To: Content-Type: text/plain; charset=utf-8; format=flowed Content-Transfer-Encoding: 7bit archived-at: Wed, 15 Feb 2017 22:48:45 -0000 As I have some knowledge of both these efforts, maybe I can provide a useful summary: Gon's students were working on Spark-on-REEF. The idea being to replace the bottom parts of the Spark system with REEF: Resource allocation, communications protocols and the likes. One instant benefit of that is that such a version of Spark can run anywhere REEF is available. Sergiy is now working on the inverse architecture: REEF on Spark. The idea here is that REEF Jobs can be part of a longer Spark pipeline. The REEF job then gets Spark's Executors as Evaluators and access to the data stored on them. The benefit of this approach is that we add the flexibility of REEF to the Spark surface without giving up on the attractive API veneer Spark can offer over both. Markus