Rheem: Enabling Multi-Platform Task Execution
Title | Rheem: Enabling Multi-Platform Task Execution |
Publication Type | Conference Paper |
Year of Publication | 2016 |
Authors | Agrawal, 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 Name | Proceedings of the 2016 International Conference on Management of Data |
Publisher | ACM |
Conference Location | New York, NY, USA |
ISBN Number | 978-1-4503-3531-7 |
Keywords | Big 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. |
URL | http://doi.acm.org/10.1145/2882903.2899414 |
DOI | 10.1145/2882903.2899414 |
Citation Key | agrawal_rheem:_2016 |