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| <h1>Rheem: Enabling Multi-Platform Task Execution</h1> |
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| <p class="italic">By <span class="bold">Divy Agrawal, Lamine Ba, Laure Berti-Equille, Sanjay Chawla, Ahmed Elmagarmid, Hossam Hammady, Yasser Idris, Zoi Kaoudi, Zuhair Khayyat, Sebastian Kruse, Mourad Ouzzani, Paolo Papotti, Jorge-Arnulfo Quiané-Ruiz, Nan Tang and Mohammed J. Zaki</span> on <span class="bold">2016</span></p> |
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| <p><p>Many emerging applications, from domains such as healthcare and oil & gas, require several data processing systems for complex analytics. This demo paper showcases Rheem, a framework that provides multi-platform task execution for such applications. It features a three-layer data processing abstraction and a new query optimization approach for multi-platform settings. We will demonstrate the strengths of Rheem by using real-world scenarios from three different applications, namely, machine learning, data cleaning, and data fusion.</p> |
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