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Vianello, Valerio and Patiño Martínez, Marta and Azqueta Alzúaz, Ainhoa and Jiménez Peris, Ricardo (2018). Cost of fault-tolerance on data stream processing. In: "Workshop on Autonomic Solutions for Parallel and Distributed Data Stream Processing (Auto-DaSP)", 27-28 Aug 2018, Turín, Italia. ISBN 978-3-030-10548-8. pp. 17-27. https://doi.org/10.1007/978-3-030-10549-5_2.
Title: | Cost of fault-tolerance on data stream processing |
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Author/s: |
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Item Type: | Presentation at Congress or Conference (Article) |
Event Title: | Workshop on Autonomic Solutions for Parallel and Distributed Data Stream Processing (Auto-DaSP) |
Event Dates: | 27-28 Aug 2018 |
Event Location: | Turín, Italia |
Title of Book: | Euro-Par 2018: Parallel Processing Workshops |
Date: | 2018 |
ISBN: | 978-3-030-10548-8 |
Subjects: | |
Freetext Keywords: | Data streaming; Fault tolerance; Evaluation; HiBench |
Faculty: | E.T.S. de Ingenieros Informáticos (UPM) |
Department: | Lenguajes y Sistemas Informáticos e Ingeniería del Software |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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Data streaming engines process data on the fly in contrast to databases that first, store the data and then, they process it. In order to process the increasing amount of data produced every day, data streaming engines run on top of a distributed system. In this setting failures will likely happen. Current distributed data streaming engines like Apache Flink provide fault tolerance. In this paper we evaluate the impact on performance of fault tolerance mechanisms of Flink during regular operation (when there are no failures) on a distributed system and the impact on performance when there are failures. We use the Intel HiBench for conducting the evaluation.
Type | Code | Acronym | Leader | Title |
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Horizon 2020 | 732051 | CloudDBAppliance | BULL SAS | European cloud in-memory database appliance with predictable performance for critical applications |
Horizon 2020 | 727560 | CrowdHEALTH | ATOS SPAIN SA | Collective wisdom driving public health policies |
Horizon 2020 | 779747 | BigDataStack | IBM ISRAEL - SCIENCE AND TECHNOLOGY LTD | High-performance data-centric stack for big data applications and operations |
Madrid Regional Government | S2013TIC2894 | Cloud4BigData | Unspecified | Unspecified |
Government of Spain | TIN2016-80350 | Unspecified | Universidad Politécnica de Madrid | CloudDB: una base de datos ultraescalable, eficiente y altamente disponible |
Item ID: | 56629 |
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DC Identifier: | http://oa.upm.es/56629/ |
OAI Identifier: | oai:oa.upm.es:56629 |
DOI: | 10.1007/978-3-030-10549-5_2 |
Official URL: | https://link.springer.com/chapter/10.1007/978-3-030-10549-5_2 |
Deposited by: | Memoria Investigacion |
Deposited on: | 23 Oct 2019 11:12 |
Last Modified: | 23 Oct 2019 11:12 |