Visible to the public Rheem: Enabling Multi-Platform Task Execution

TitleRheem: Enabling Multi-Platform Task Execution
Publication TypeConference Paper
Year of Publication2016
AuthorsAgrawal, Divy, Ba, Lamine, Berti-Equille, Laure, Chawla, Sanjay, Elmagarmid, Ahmed, Hammady, Hossam, Idris, Yasser, Kaoudi, Zoi, Khayyat, Zuhair, Kruse, Sebastian, Ouzzani, Mourad, Papotti, Paolo, Quiane-Ruiz, Jorge-Arnulfo, Tang, Nan, Zaki, Mohammed J.
Conference NameProceedings of the 2016 International Conference on Management of Data
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-3531-7
KeywordsBig Data, cross-platform execution, data analytics, pubcrawl170201
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.

URLhttp://doi.acm.org/10.1145/2882903.2899414
DOI10.1145/2882903.2899414
Citation Keyagrawal_rheem:_2016