MRSim: A discrete event based MapReduce simulator

Recently MapReduce programming model is becoming popular for large scale data intensive distributed applications due to its efficiency, simplicity and ease of use. The Hadoop implementation of MapReduce is one of the most popular tools for many programmers due its ability to hide details of parallel...

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Published in2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery Vol. 6; pp. 2993 - 2997
Main Authors Hammoud, S, Maozhen Li, Yang Liu, Alham, Nasullah Khalid, Zelong Liu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2010
Subjects
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ISBN1424459311
9781424459315
DOI10.1109/FSKD.2010.5569086

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Abstract Recently MapReduce programming model is becoming popular for large scale data intensive distributed applications due to its efficiency, simplicity and ease of use. The Hadoop implementation of MapReduce is one of the most popular tools for many programmers due its ability to hide details of parallel programming from the users. However work on simulating the Hadoop environment is still in its infancy. Although there are a large number of simulating tools available to simulate distributed environments. However there are only a few simulators available which specifically targets the MapReduce environment. Based on testing we performed; the usability of these simulators is not satisfactory due to the simplified design which limits simulating jobs with variance configurations. We have designed and implemented a MapReduce simulator based on discrete event simulation called MRSim which accurately simulate the Hadoop environment. The simulator on one hand allows us to measure scalability of MapReduce based applications easily and quickly, on the other hand captures the effects of different configurations of Hadoop setup on MapReduce based applications behavior in terms of Hadoop job completion times and hardware utilization.
AbstractList Recently MapReduce programming model is becoming popular for large scale data intensive distributed applications due to its efficiency, simplicity and ease of use. The Hadoop implementation of MapReduce is one of the most popular tools for many programmers due its ability to hide details of parallel programming from the users. However work on simulating the Hadoop environment is still in its infancy. Although there are a large number of simulating tools available to simulate distributed environments. However there are only a few simulators available which specifically targets the MapReduce environment. Based on testing we performed; the usability of these simulators is not satisfactory due to the simplified design which limits simulating jobs with variance configurations. We have designed and implemented a MapReduce simulator based on discrete event simulation called MRSim which accurately simulate the Hadoop environment. The simulator on one hand allows us to measure scalability of MapReduce based applications easily and quickly, on the other hand captures the effects of different configurations of Hadoop setup on MapReduce based applications behavior in terms of Hadoop job completion times and hardware utilization.
Author Maozhen Li
Zelong Liu
Yang Liu
Alham, Nasullah Khalid
Hammoud, S
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  surname: Maozhen Li
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  surname: Yang Liu
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  givenname: Nasullah Khalid
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  organization: Sch. of Eng. & Design, Brunel Univ., Uxbridge, UK
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  surname: Zelong Liu
  fullname: Zelong Liu
  organization: Sch. of Eng. & Design, Brunel Univ., Uxbridge, UK
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Snippet Recently MapReduce programming model is becoming popular for large scale data intensive distributed applications due to its efficiency, simplicity and ease of...
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StartPage 2993
SubjectTerms Clustering algorithms
Computational modeling
Corporate acquisitions
Data models
Distributed databases
File systems
hadoop
MapReuce
Object oriented modeling
simulation
Title MRSim: A discrete event based MapReduce simulator
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Volume 6
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