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
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-utpedia.19005 /
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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id utp-utpedia.19005
recordtype eprints
spelling 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
collection UTPedia
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_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_ 1741195435418058752
score 11.62408

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