Rheem: Enabling Multi-Platform Task Execution

Abstract : 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.
Type de document :
Communication dans un congrès
SIGMOD 2016 - International Conference on Management of Data, Jun 2016, San Francisco, United States. ACM Press, SIGMOD '16 Proceedings of the 2016 International Conference on Management of Data, pp.2069-2072, 〈10.1145/2882903.2899414〉
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https://hal.inria.fr/hal-01829075
Contributeur : Laure Berti-Equille <>
Soumis le : mardi 3 juillet 2018 - 17:13:02
Dernière modification le : mardi 8 janvier 2019 - 16:10:13

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Divy Agrawal, Lamine Ba, Laure Berti-Équille, Sanjay Chawla, Ahmed Elmagarmid, et al.. Rheem: Enabling Multi-Platform Task Execution. SIGMOD 2016 - International Conference on Management of Data, Jun 2016, San Francisco, United States. ACM Press, SIGMOD '16 Proceedings of the 2016 International Conference on Management of Data, pp.2069-2072, 〈10.1145/2882903.2899414〉. 〈hal-01829075〉

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