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Investigating MapReduce framework extensions for efficient processing of geographically scattered datasets
Descriptive
TitleInfo
Title
Investigating MapReduce framework extensions for efficient processing of geographically scattered datasets
Name
(type = personal)
NamePart
(type = family)
Gadre
NamePart
(type = given)
Hrishikesh
DisplayForm
Hrishikesh Gadre
Role
RoleTerm
(authority = RULIB)
author
Name
(type = personal)
NamePart
(type = family)
Parashar
NamePart
(type = given)
Manish
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Manish Parashar
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
chair
Name
(type = personal)
NamePart
(type = family)
Marsic
NamePart
(type = given)
Ivan
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Ivan Marsic
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Rodero
NamePart
(type = given)
Ivan
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Ivan Rodero
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
outside member
Name
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NamePart
Rutgers University
Role
RoleTerm
(authority = RULIB)
degree grantor
Name
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NamePart
Graduate School - New Brunswick
Role
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(authority = RULIB)
school
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Text
Genre
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theses
OriginInfo
DateCreated
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2011
DateOther
(qualifier = exact);
(type = degree)
2011-10
CopyrightDate
(qualifier = exact)
2011
Place
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(type = code)
xx
Language
LanguageTerm
(authority = ISO639-2b);
(type = code)
eng
Abstract
(type = abstract)
We observe two important trends brought about by the evolution of Internet in recent years. Firstly to improve end-to-end application performance in presence of bottlenecks in the wide-area Internet communication, modern day Internet services are designed in a decentralized fashion involving geographically distributed data-centers connected through the Internet. Secondly the pervasive nature of Internet services has resulted into an exponential growth in the size of digital information created, captured or replicated. Organizations are keenly interested in mining this information to uncover trends, statistics and other actionable information which can give them competitive advantage. These two trends necessitate the design of a large-scale data processing system which can operate efficiently in a distributed environment involving multiple datacenters connected through the Internet. In recent years, MapReduce programming model and specifically its open source implementation Hadoop is gaining a lot of traction for performing large-scale data processing in a centralized environment. Our evaluation of different real-world usage scenarios of Hadoop deployments revealed that the organizations with the distributed datasets are required to copy the entire dataset to a centralized location so that it can be efficiently processed by the Hadoop MapReduce framework. As the Internet evolves growth in the size of distributed datasets would outpace the improvements in the network bandwidth available in the Internet. At that point the approach of copying the entire dataset to a single location using Internet would become infeasible. In this thesis, we have investigated the possibility of extending the MapReduce and specifically Hadoop framework to operate in a distributed environment involving multiple datacenters connected through the Internet. We also have proposed policies to improve the performance of Hadoop MapReduce framework in a distributed environment. We have observed that our policies improve the performance of Hadoop framework substantially.
Subject
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Topic
Electrical and Computer Engineering
RelatedItem
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TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
(type = RULIB)
ETD
Identifier
ETD_3507
PhysicalDescription
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electronic resource
InternetMediaType
application/pdf
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text/xml
Extent
ix, 80 p. : ill.
Note
(type = degree)
M.S.
Note
(type = bibliography)
Includes bibliographical references
Note
(type = statement of responsibility)
by Hrishikesh Gadre
Subject
(authority = ETD-LCSH)
Topic
Information storage and retrieval systems
Subject
(authority = ETD-LCSH)
Topic
Data processing service centers
Identifier
(type = hdl)
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000063404
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TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
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rucore19991600001
Location
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(displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier
(type = doi)
doi:10.7282/T3CR5SFB
Genre
(authority = ExL-Esploro)
ETD graduate
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Rights
RightsDeclaration
(ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder
(type = personal)
Name
FamilyName
Gadre
GivenName
Hrishikesh
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
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(qualifier = exact);
(point = start)
2011-08-19 16:47:06
AssociatedEntity
Name
Hrishikesh Gadre
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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700928
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