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Filters: Author is Elmagarmid, Ahmed  [Clear All Filters]
2017-03-07
Agrawal, Divy, Ba, Lamine, Berti-Equille, Laure, Chawla, Sanjay, Elmagarmid, Ahmed, Hammady, Hossam, Idris, Yasser, Kaoudi, Zoi, Khayyat, Zuhair, Kruse, Sebastian et al..  2016.  Rheem: Enabling Multi-Platform Task Execution. Proceedings of the 2016 International Conference on Management of Data. :2069–2072.

Many emerging applications, from domains such as healthcare and oil & gas, require several data processing systems for complex analytics. This demo paper showcases system, 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 system by using real-world scenarios from three different applications, namely, machine learning, data cleaning, and data fusion.