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INDEXING SCHEME USING PARTITIONED B+-TREE (ISPB) FOR IMPROVING THE EFFICIENCY OF THE HADOOP MAPREDUCE QUERY PROCESSING

The rapid generation and accumulation of data in recent time have led to the concept of big data which requires emergent and development of tools, techniques and systems with significant performance improvement when handling such datasets. Hadoop is one of such systems, that processes 1TB of data...

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Main Author: ABDULLAHI, ALI USMAN
Format: Thesis
Language:English
Published: 2018
Subjects:
T Technology (General)
Online Access:http://utpedia.utp.edu.my/19005/1/ThesisV01.pdf
http://utpedia.utp.edu.my/19005/
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spelling my-utp-utpedia.190052019-05-14T10:26:38Z http://utpedia.utp.edu.my/19005/ INDEXING SCHEME USING PARTITIONED B+-TREE (ISPB) FOR IMPROVING THE EFFICIENCY OF THE HADOOP MAPREDUCE QUERY PROCESSING ABDULLAHI, ALI USMAN T Technology (General) The rapid generation and accumulation of data in recent time have led to the concept of big data which requires emergent and development of tools, techniques and systems with significant performance improvement when handling such datasets. Hadoop is one of such systems, that processes 1TB of data in 2 min on a 100 nodes cluster. In an attempt to improve the Hadoop performance indexing was introduced into it. 2018-05 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/19005/1/ThesisV01.pdf ABDULLAHI, ALI USMAN (2018) INDEXING SCHEME USING PARTITIONED B+-TREE (ISPB) FOR IMPROVING THE EFFICIENCY OF THE HADOOP MAPREDUCE QUERY PROCESSING. PhD thesis, Universiti Teknologi PETRONAS.
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
ABDULLAHI, ALI USMAN
INDEXING SCHEME USING PARTITIONED B+-TREE (ISPB) FOR IMPROVING THE EFFICIENCY OF THE HADOOP MAPREDUCE QUERY PROCESSING
description The rapid generation and accumulation of data in recent time have led to the concept of big data which requires emergent and development of tools, techniques and systems with significant performance improvement when handling such datasets. Hadoop is one of such systems, that processes 1TB of data in 2 min on a 100 nodes cluster. In an attempt to improve the Hadoop performance indexing was introduced into it.
format Thesis
author ABDULLAHI, ALI USMAN
author_facet ABDULLAHI, ALI USMAN
author_sort ABDULLAHI, ALI USMAN
title INDEXING SCHEME USING PARTITIONED B+-TREE (ISPB) FOR IMPROVING THE EFFICIENCY OF THE HADOOP MAPREDUCE QUERY PROCESSING
title_short INDEXING SCHEME USING PARTITIONED B+-TREE (ISPB) FOR IMPROVING THE EFFICIENCY OF THE HADOOP MAPREDUCE QUERY PROCESSING
title_full INDEXING SCHEME USING PARTITIONED B+-TREE (ISPB) FOR IMPROVING THE EFFICIENCY OF THE HADOOP MAPREDUCE QUERY PROCESSING
title_fullStr INDEXING SCHEME USING PARTITIONED B+-TREE (ISPB) FOR IMPROVING THE EFFICIENCY OF THE HADOOP MAPREDUCE QUERY PROCESSING
title_full_unstemmed INDEXING SCHEME USING PARTITIONED B+-TREE (ISPB) FOR IMPROVING THE EFFICIENCY OF THE HADOOP MAPREDUCE QUERY PROCESSING
title_sort indexing scheme using partitioned b+-tree (ispb) for improving the efficiency of the hadoop mapreduce query processing
publishDate 2018
url http://utpedia.utp.edu.my/19005/1/ThesisV01.pdf
http://utpedia.utp.edu.my/19005/
_version_ 1739832575905497088
score 13.214268

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