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  1. Proceedings of the 8th International Workshop on Modeling in Software Engineering (MiSE '16)
  2. Model driven performance simulation of cloud provisioned Hadoop mapreduce applications
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Model driven performance simulation of cloud provisioned Hadoop mapreduce applications

Content Provider ACM Digital Library
Author Gorton, Ian Liu, Yan Hamou-Lhadj, Abdelwahab Alipour, Hanieh
Abstract Hadoop is a widely adopted open source implementation of MapReduce. A Hadoop cluster can be fully provisioned by a Cloud service provider to provide elasticity in computational resource allocation. Understanding the performance characteristics of a Hadoop job can help achieve an optimal balance between resource usage (cost) and job latency on a cloud-based cluster. This paper presents a method that estimates the performance of a MapReduce application in a Cloud provisioned Hadoop cluster. We develop a model-driven approach that models a cloud provided independent Hadoop MapReduce model and customizes it for a specific Cloud deployment. These models are further transformed into a simulation model that produces estimations of end-to-end job latency. We explore this method in the design space of MapReduce applications to estimate the performance for different sizes of input data. Our approach provides a model-to-simulation-to-prediction method for observing the performance behaviour of MapReduce applications given a configuration of a MapReduce platform.
Starting Page 48
Ending Page 54
Page Count 7
File Format PDF
ISBN 9781450341646
DOI 10.1145/2896982.2896989
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2016-05-14
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Model driven Cloud computing Hadoop Mapreduce Performance
Content Type Text
Resource Type Article
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