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Boosting scalable data analytics with modern programmable networks

Authors:

Marcel Blöcher,

Tobias Ziegler,

Carsten Binnig,

Patrick EugsterAuthors Info & Claims

DAMON '18: Proceedings of the 14th International Workshop on Data Management on New Hardware

Article No.: 1, Pages 1 - 3

https://doi.org/10.1145/3211922.3211923

Published: 11 June 2018 Publication History

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Abstract

Data center networks lie at the core of distributed data analytics frameworks running in large scale environments. Recent research seek to improve the system performance by optimizing the end-host network usage, e.g., optimally use RDMA [2] or zero copy I/O frameworks [5] for distributed data analytics frameworks. Such approaches allow these systems to leverage the high network-bandwidth at end-hosts, however, keep the network itself untouched which does not solve contention and scalability issues.

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Cited By

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Jasny MZiegler TBinnig C(2025)Scalable Data Management on Next-Generation Data Center NetworksScalable Data Management for Future Hardware10.1007/978-3-031-74097-8_8(199-221)Online publication date: 24-Jan-2025
https://doi.org/10.1007/978-3-031-74097-8_8
Lerner ABinnig CCudré-Mauroux PHussein RJasny MJepsen TPorts DThostrup LZiegler T(2023)Databases on Modern Networks: A Decade of Research That Now Comes into PracticeProceedings of the VLDB Endowment10.14778/3611540.361157916:12(3894-3897)Online publication date: 12-Sep-2023
https://doi.org/10.14778/3611540.3611579
Jasny MThostrup LZiegler TBinnig CIves ZBonifati AEl Abbadi A(2022)P4DB - The Case for In-Network OLTPProceedings of the 2022 International Conference on Management of Data10.1145/3514221.3517825(1375-1389)Online publication date: 10-Jun-2022
https://dl.acm.org/doi/10.1145/3514221.3517825
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Index Terms

Boosting scalable data analytics with modern programmable networks
1. Networks
  1. Network components
    1. Middle boxes / network appliances
  2. Network services
    1. In-network processing
    2. Programmable networks

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DAMON '18: Proceedings of the 14th International Workshop on Data Management on New Hardware

June 2018

75 pages

ISBN:9781450358538

DOI:10.1145/3211922

Conference Chairs:
Wolfgang Lehner
Technische Universität Dresden
,
Ken Salem
University of Waterloo

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 the author(s) 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: 11 June 2018

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NSF CSR grant 1421910
German Research Foundation (DFG) as part of project B2 within the Collaborative Research Center (CRC) 1053 MAKI Multi-Mechanisms Adaptation for the Future Internet
ERC grant 617805 LiveSoft
German Research Foundation (DFG) as part of grant BI2011/1 of SPP 2037
NSF CSR grant 1618923

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SIGMOD/PODS '18

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SIGMOD

SIGMOD/PODS '18: International Conference on Management of Data

June 11, 2018

Texas, Houston

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Overall Acceptance Rate 94 of 127 submissions, 74%

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Jasny MZiegler TBinnig C(2025)Scalable Data Management on Next-Generation Data Center NetworksScalable Data Management for Future Hardware10.1007/978-3-031-74097-8_8(199-221)Online publication date: 24-Jan-2025
https://doi.org/10.1007/978-3-031-74097-8_8
Lerner ABinnig CCudré-Mauroux PHussein RJasny MJepsen TPorts DThostrup LZiegler T(2023)Databases on Modern Networks: A Decade of Research That Now Comes into PracticeProceedings of the VLDB Endowment10.14778/3611540.361157916:12(3894-3897)Online publication date: 12-Sep-2023
https://doi.org/10.14778/3611540.3611579
Jasny MThostrup LZiegler TBinnig CIves ZBonifati AEl Abbadi A(2022)P4DB - The Case for In-Network OLTPProceedings of the 2022 International Conference on Management of Data10.1145/3514221.3517825(1375-1389)Online publication date: 10-Jun-2022
https://dl.acm.org/doi/10.1145/3514221.3517825
Jepsen TLerner APedone FSoulé RCudré-Mauroux P(2021)In-network support for transaction triagingProceedings of the VLDB Endowment10.14778/3461535.346155114:9(1626-1639)Online publication date: 22-Oct-2021
https://dl.acm.org/doi/10.14778/3461535.3461551
Wirth JHofmann JThostrup LBinnig CKoch A(2021)Scalable and Flexible High-Performance In-Network Processing of Hash Joins in Distributed Databases2021 International Conference on Field-Programmable Technology (ICFPT)10.1109/ICFPT52863.2021.9609804(1-9)Online publication date: 6-Dec-2021
https://doi.org/10.1109/ICFPT52863.2021.9609804
Wirth JHofmann JThostrup LKoch ABinnig C(2021)Exploiting 3D Memory for Accelerated In-Network Processing of Hash Joins in Distributed DatabasesApplied Reconfigurable Computing. Architectures, Tools, and Applications10.1007/978-3-030-79025-7_2(18-32)Online publication date: 23-Jun-2021
https://doi.org/10.1007/978-3-030-79025-7_2

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WSDM'15 Workshop Summary / Scalable Data Analytics: Theory and Applications

Scalable machine-learning algorithms for big data analytics: a comprehensive review

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