 Rheem: Enabling Multi-Platform Task Execution
 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 | 

 
 