Rheem: Enabling Multi-Platform Task Execution

Divy Agrawal; Sebastian Kruse; Mourad Ouzzani; Paolo Papotti; Jorge-Arnulfo Quiane-Ruiz; Nan Tang; Mohammed J. Zaki; Lamine Ba; Laure Berti-Equille; Sanjay Chawla; Ahmed Elmagarmid; Hossam Hammady; Yasser Idris; Zoi Kaoudi; Zuhair Khayyat

doi:10.1145/2882903.2899414

Rheem: Enabling Multi-Platform Task Execution

Divy Agrawal, Sebastian Kruse, Mourad Ouzzani, Paolo Papotti, Jorge-Arnulfo Quiane-Ruiz, Nan Tang, Mohammed J. Zaki, Lamine Ba, Laure Berti-Equille, Sanjay Chawla, Ahmed Elmagarmid, Hossam Hammady, Yasser Idris, Zoi Kaoudi, Zuhair Khayyat

King Abdullah University of Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

30 Scopus citations

Abstract

Many emerging applications, from domains such as healthcare and oil & gas, require several data processing systems for complex analytics. This demo paper showcases Rheem, 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 Rheem by using real-world scenarios from three different applications, namely, machine learning, data cleaning, and data fusion. © 2016 ACM.

Original language	English (US)
Title of host publication	Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16
Publisher	Association for Computing Machinery (ACM)
Pages	2069-2072
Number of pages	4
ISBN (Print)	9781450335317
DOIs	https://doi.org/10.1145/2882903.2899414
State	Published - Jun 16 2016

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KAUST Repository Item: Exported on 2020-10-01

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Agrawal, D., Kruse, S., Ouzzani, M., Papotti, P., Quiane-Ruiz, J.-A., Tang, N., Zaki, M. J., Ba, L., Berti-Equille, L., Chawla, S., Elmagarmid, A., Hammady, H., Idris, Y., Kaoudi, Z., & Khayyat, Z. (2016). Rheem: Enabling Multi-Platform Task Execution. In Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16 (pp. 2069-2072). Association for Computing Machinery (ACM). https://doi.org/10.1145/2882903.2899414

@inproceedings{1a76197c8d7d479c911cd429f6684630,

title = "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 Rheem, 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 Rheem by using real-world scenarios from three different applications, namely, machine learning, data cleaning, and data fusion. {\textcopyright} 2016 ACM.",

author = "Divy Agrawal and Sebastian Kruse and Mourad Ouzzani and Paolo Papotti and Jorge-Arnulfo Quiane-Ruiz and Nan Tang and Zaki, {Mohammed J.} and Lamine Ba and Laure Berti-Equille and Sanjay Chawla and Ahmed Elmagarmid and Hossam Hammady and Yasser Idris and Zoi Kaoudi and Zuhair Khayyat",

note = "KAUST Repository Item: Exported on 2020-10-01",

year = "2016",

month = jun,

day = "16",

doi = "10.1145/2882903.2899414",

language = "English (US)",

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Agrawal, D, Kruse, S, Ouzzani, M, Papotti, P, Quiane-Ruiz, J-A, Tang, N, Zaki, MJ, Ba, L, Berti-Equille, L, Chawla, S, Elmagarmid, A, Hammady, H, Idris, Y, Kaoudi, Z & Khayyat, Z 2016, Rheem: Enabling Multi-Platform Task Execution. in Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16. Association for Computing Machinery (ACM), pp. 2069-2072. https://doi.org/10.1145/2882903.2899414

TY - GEN

T1 - Rheem: Enabling Multi-Platform Task Execution

AU - Agrawal, Divy

AU - Kruse, Sebastian

AU - Ouzzani, Mourad

AU - Papotti, Paolo

AU - Quiane-Ruiz, Jorge-Arnulfo

AU - Tang, Nan

AU - Zaki, Mohammed J.

AU - Ba, Lamine

AU - Berti-Equille, Laure

AU - Chawla, Sanjay

AU - Elmagarmid, Ahmed

AU - Hammady, Hossam

AU - Idris, Yasser

AU - Kaoudi, Zoi

AU - Khayyat, Zuhair

N1 - KAUST Repository Item: Exported on 2020-10-01

PY - 2016/6/16

Y1 - 2016/6/16

N2 - Many emerging applications, from domains such as healthcare and oil & gas, require several data processing systems for complex analytics. This demo paper showcases Rheem, 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 Rheem by using real-world scenarios from three different applications, namely, machine learning, data cleaning, and data fusion. © 2016 ACM.

AB - Many emerging applications, from domains such as healthcare and oil & gas, require several data processing systems for complex analytics. This demo paper showcases Rheem, 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 Rheem by using real-world scenarios from three different applications, namely, machine learning, data cleaning, and data fusion. © 2016 ACM.

UR - http://hdl.handle.net/10754/621289

UR - http://dl.acm.org/citation.cfm?doid=2882903.2899414

UR - http://www.scopus.com/inward/record.url?scp=84979656031&partnerID=8YFLogxK

U2 - 10.1145/2882903.2899414

DO - 10.1145/2882903.2899414

M3 - Conference contribution

SN - 9781450335317

SP - 2069

EP - 2072

BT - Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16

PB - Association for Computing Machinery (ACM)

ER -

Rheem: Enabling Multi-Platform Task Execution

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