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Cost of fault-tolerance on data stream processing
Citation
Vianello, Valerio, Patiño Martínez, Marta 
ORCID: https://orcid.org/0000-0001-6947-4974, Azqueta Alzúaz, Ainhoa ORCID: https://orcid.org/0000-0002-5451-8900 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.
Description
| Title: | Cost of fault-tolerance on data stream processing |
|---|---|
| Author/s: |
|
| 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 |
Abstract
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.
Funding Projects
Type
Code
Acronym
Leader
Title
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
More information
| Item ID: | 56629 |
|---|---|
| DC Identifier: | https://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/10.1007/978-3-03... |
| Deposited by: | Memoria Investigacion |
| Deposited on: | 23 Oct 2019 11:12 |
| Last Modified: | 23 Oct 2019 11:12 |
