research-article

Exploring Performance Models of Hadoop Applications on Cloud Architecture

Authors:

Ian GortonAuthors Info & Claims

QoSA '15: Proceedings of the 11th International ACM SIGSOFT Conference on Quality of Software Architectures

Pages 93 - 101

https://doi.org/10.1145/2737182.2737197

Published: 04 May 2015 Publication History

Abstract

Hadoop is an open source implementation of the MapReduce programming model, and provides the runtime infrastructure for map and reduce functions programmed in individual applications. Commercial clouds such as Amazon Elastic MapReduce provides the Hadoop architecture with IaaS support. In this architecture, the map and reduce functions are major determinants of end-to-end application latency, along with the framework components responsible for data access and exchange. In this paper, we aim to explore modeling methods that capture the performance characteristic and the semantics of a Hadoop architecture. We present our early results for modeling the performance of a Hadoop application given the design of map and reduce functions using Layered Queueing Network (LQN). We build two different LQN models to represent the data parallel computing of these functions and calibrate both models using monitored performance data. The output of both models produces converging results that are within ~10% of observed performance. From our modeling experience, we further discuss the issues of modeling Hadoop architecture using LQN in general and describe our future work.

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Cited By

Zhao YXiao LBondi AChen BLiu Y(2023)A Large-Scale Empirical Study of Real-Life Performance Issues in Open Source ProjectsIEEE Transactions on Software Engineering10.1109/TSE.2022.316762849:2(924-946)Online publication date: 1-Feb-2023
https://doi.org/10.1109/TSE.2022.3167628
Gorton IRajagopal SLiu YMedvidovic NMirakhorli MMalek SGarcia JCai YKazman RXiao L(2019)Towards a cloud performance research repositoryProceedings of the 2nd International Workshop on Establishing a Community-Wide Infrastructure for Architecture-Based Software Engineering10.1109/ECASE.2019.00012(22-25)Online publication date: 27-May-2019
https://dl.acm.org/doi/10.1109/ECASE.2019.00012
Parn EEdwards DRiaz ZMehmood FLai J(2019)Engineering-out hazards: digitising the management working safety in confined spacesFacilities10.1108/F-03-2018-003937:3/4(196-215)Online publication date: 28-Feb-2019
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Index Terms

Exploring Performance Models of Hadoop Applications on Cloud Architecture
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis
      1. Modeling methodologies
2. Software and its engineering
  1. Software creation and management
    1. Software development process management
      1. Software development methods

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Published In

cover image ACM Conferences

QoSA '15: Proceedings of the 11th International ACM SIGSOFT Conference on Quality of Software Architectures

May 2015

152 pages

ISBN:9781450334709

DOI:10.1145/2737182

General Chair:
Philippe Kruchten
University of British Columbia, Canada
,
Program Chairs:
Ipek Ozkaya
Carnegie Mellon University, Software Engineering Institute, Pittsburgh, USA
,
Heiko Koziolek
ABB Corporate Research, Ladenburg, Germany

Copyright © 2015 ACM.

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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SIGSOFT: ACM Special Interest Group on Software Engineering
IEEE-CS\DATC: IEEE Computer Society

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Association for Computing Machinery

New York, NY, United States

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Published: 04 May 2015

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CompArch '15: Federated Events on Component-Based Software Engineering and Software Architecture

May 4 - 8, 2015

QC, Montréal, Canada

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QoSA '15 Paper Acceptance Rate 14 of 42 submissions, 33%;

Overall Acceptance Rate 46 of 131 submissions, 35%

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Cited By

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https://doi.org/10.1109/TSE.2022.3167628
Gorton IRajagopal SLiu YMedvidovic NMirakhorli MMalek SGarcia JCai YKazman RXiao L(2019)Towards a cloud performance research repositoryProceedings of the 2nd International Workshop on Establishing a Community-Wide Infrastructure for Architecture-Based Software Engineering10.1109/ECASE.2019.00012(22-25)Online publication date: 27-May-2019
https://dl.acm.org/doi/10.1109/ECASE.2019.00012
Parn EEdwards DRiaz ZMehmood FLai J(2019)Engineering-out hazards: digitising the management working safety in confined spacesFacilities10.1108/F-03-2018-003937:3/4(196-215)Online publication date: 28-Feb-2019
https://doi.org/10.1108/F-03-2018-0039
Drăgan IIuhasz GPetcu D(2019)A Scalable Platform for Monitoring Data Intensive ApplicationsJournal of Grid Computing10.1007/s10723-019-09483-1Online publication date: 29-May-2019
https://doi.org/10.1007/s10723-019-09483-1
Morán Jde la Riva CTuya J(2019)Testing MapReduce programsJournal of Software: Evolution and Process10.1002/smr.212031:3Online publication date: 25-Mar-2019
https://dl.acm.org/doi/10.1002/smr.2120
Chattaraj DSarma MSamanta D(2018)Stochastic Petri Net Based Modeling for Analyzing Dependability of Big Data Storage SystemEmerging Technologies in Data Mining and Information Security10.1007/978-981-13-1498-8_42(473-484)Online publication date: 2-Sep-2018
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Kim BKim T(2017)Cooperation between data modeling and simulation modeling for performance analysis of Hadoop2017 International Symposium on Performance Evaluation of Computer and Telecommunication Systems (SPECTS)10.23919/SPECTS.2017.8046769(1-7)Online publication date: Jul-2017
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Arslan MRiaz ZMunawar S(2017)Building Information Modeling (BIM) Enabled Facilities Management Using Hadoop Architecture2017 Portland International Conference on Management of Engineering and Technology (PICMET)10.23919/PICMET.2017.8125462(1-7)Online publication date: Jul-2017
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Das AHong JGoswami SPlatania RLee KChang WPark SLiu L(2017)Augmenting Amdahl's Second Law: A Theoretical Model to Build Cost-Effective Balanced HPC Infrastructure for Data-Driven Science2017 IEEE 10th International Conference on Cloud Computing (CLOUD)10.1109/CLOUD.2017.27(147-154)Online publication date: Jun-2017
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Lu QLi ZZhang WYang L(2017)Autonomic deployment decision making for big data analytics applications in the cloudSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-015-1945-521:16(4501-4512)Online publication date: 1-Aug-2017
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