research-article

Rheem: Enabling Multi-Platform Task Execution

Authors:

Jorge-Arnulfo Quiane-Ruiz,

Nan Tang,

Mohammed J. ZakiAuthors Info & Claims

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

Pages 2069 - 2072

https://doi.org/10.1145/2882903.2899414

Published: 26 June 2016 Publication History

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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.

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Cited By

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Chen QChen ZZhang KWang X(2024)CLIC: An Extensible and Efficient Cross-Platform Data Analytics SystemIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2023.329803835:1(34-45)Online publication date: Jan-2024
https://doi.org/10.1109/TPDS.2023.3298038
Reznichenko V(2023)60 Years of Databases (final part)PROBLEMS IN PROGRAMMING10.15407/pp2023.01.066(66-103)Online publication date: Jan-2023
https://doi.org/10.15407/pp2023.01.066
Kaoudi ZQuiané-Ruiz J(2022)Unified data analyticsProceedings of the VLDB Endowment10.14778/3554821.355489815:12(3778-3781)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.14778/3554821.3554898
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Index Terms

Rheem: Enabling Multi-Platform Task Execution
1. Information systems
  1. Data management systems
    1. Middleware for databases
      1. Data federation tools

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Information & Contributors

Information

Published In

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

June 2016

2300 pages

ISBN:9781450335317

DOI:10.1145/2882903

General Chairs:
Fatma Özcan
IBM Research, USA
,
Georgia Koutrika
HP Labs, USA
,
Program Chair:
Sam Madden
Massachusetts Institute of Technology, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 June 2016

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SIGMOD/PODS'16

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SIGMOD

SIGMOD/PODS'16: International Conference on Management of Data

June 26 - July 1, 2016

California, San Francisco, USA

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Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

View all

Chen QChen ZZhang KWang X(2024)CLIC: An Extensible and Efficient Cross-Platform Data Analytics SystemIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2023.329803835:1(34-45)Online publication date: Jan-2024
https://doi.org/10.1109/TPDS.2023.3298038
Reznichenko V(2023)60 Years of Databases (final part)PROBLEMS IN PROGRAMMING10.15407/pp2023.01.066(66-103)Online publication date: Jan-2023
https://doi.org/10.15407/pp2023.01.066
Kaoudi ZQuiané-Ruiz J(2022)Unified data analyticsProceedings of the VLDB Endowment10.14778/3554821.355489815:12(3778-3781)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.14778/3554821.3554898
Zhou XChai CLi GSun J(2022)Database Meets Artificial Intelligence: A SurveyIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2020.299464134:3(1096-1116)Online publication date: 1-Mar-2022
https://doi.org/10.1109/TKDE.2020.2994641
Glake DSchmidt MKiehn FPanse FLenfers UClemen TRitter N(2022)Operator Placement for Spatio-temporal Tasks2022 IEEE International Conference on Big Data (Big Data)10.1109/BigData55660.2022.10020279(281-290)Online publication date: 17-Dec-2022
https://doi.org/10.1109/BigData55660.2022.10020279
Gévay GSoto JMarkl V(2021)Handling Iterations in Distributed Dataflow SystemsACM Computing Surveys10.1145/347760254:9(1-38)Online publication date: 8-Oct-2021
https://dl.acm.org/doi/10.1145/3477602
Gevay GRabl TBres SMadai-Tahy LQuiane-Ruiz JMarkl V(2021)Efficient Control Flow in Dataflow Systems: When Ease-of-Use Meets High Performance2021 IEEE 37th International Conference on Data Engineering (ICDE)10.1109/ICDE51399.2021.00127(1428-1439)Online publication date: Apr-2021
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Glake DKiehn FSchmidt MRitter N(2021)Towards Taming the Adaptivity ProblemService-Oriented Computing10.1007/978-3-030-87568-8_5(83-99)Online publication date: 26-Sep-2021
https://doi.org/10.1007/978-3-030-87568-8_5
Kaoudi ZQuiane-Ruiz JContreras-Rojas BPardo-Meza RTroudi AChawla S(2020)ML-based Cross-Platform Query Optimization2020 IEEE 36th International Conference on Data Engineering (ICDE)10.1109/ICDE48307.2020.00132(1489-1500)Online publication date: Apr-2020
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Contreras-Rojas BQuiané-Ruiz JKaoudi ZThirumuruganathan S(2019)TagSniffProceedings of the ACM Symposium on Cloud Computing10.1145/3357223.3362738(453-464)Online publication date: 20-Nov-2019
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