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Big data analysis solutions using mapReduce framework

Recently, data that generated from variety of sources with massive volumes, high rates, and different data structure, data with these characteristics is called Big Data. Big Data processing and analyzing is a challenge for the current systems because they were designed without Big Data requirements...

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Main Authors: Elagib, Sara B., Najeeb, Athaur Rahman, Hassan Abdalla Hashim, Aisha, Olanrewaju, Rashidah Funke
Format: Conference or Workshop Item
Language:English
English
Published: 2014
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://irep.iium.edu.my/41638/1/41638.pdf
http://irep.iium.edu.my/41638/4/41638_Big%20data%20analysis%20solutions%20using%20map_Scopus.pdf
http://irep.iium.edu.my/41638/
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7031477
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spelling my.iium.irep.416382017-09-20T10:26:56Z http://irep.iium.edu.my/41638/ Big data analysis solutions using mapReduce framework Elagib, Sara B. Najeeb, Athaur Rahman Hassan Abdalla Hashim, Aisha Olanrewaju, Rashidah Funke QA75 Electronic computers. Computer science Recently, data that generated from variety of sources with massive volumes, high rates, and different data structure, data with these characteristics is called Big Data. Big Data processing and analyzing is a challenge for the current systems because they were designed without Big Data requirements in mind and most of them were built on centralized architecture, which is not suitable for Big Data processing because it results on high processing cost and low processing performance and quality. MapReduce framework was built as a parallel distributed programming model to process such large-scale datasets effectively and efficiently. This paper presents six successful Big Data software analysis solutions implemented on MapReduce framework, describing their datasets structures and how they were implemented, so that it can guide and help other researchers in their own Big Data solutions. 2014 Conference or Workshop Item REM application/pdf en http://irep.iium.edu.my/41638/1/41638.pdf application/pdf en http://irep.iium.edu.my/41638/4/41638_Big%20data%20analysis%20solutions%20using%20map_Scopus.pdf Elagib, Sara B. and Najeeb, Athaur Rahman and Hassan Abdalla Hashim, Aisha and Olanrewaju, Rashidah Funke (2014) Big data analysis solutions using mapReduce framework. In: 5th International Conference on Computer and Communication Engineering (ICCCE 2014), 23th - 25th September 2014, Sunway Putra Hotel, Kuala Lumpur. http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7031477
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Elagib, Sara B.
Najeeb, Athaur Rahman
Hassan Abdalla Hashim, Aisha
Olanrewaju, Rashidah Funke
Big data analysis solutions using mapReduce framework
description Recently, data that generated from variety of sources with massive volumes, high rates, and different data structure, data with these characteristics is called Big Data. Big Data processing and analyzing is a challenge for the current systems because they were designed without Big Data requirements in mind and most of them were built on centralized architecture, which is not suitable for Big Data processing because it results on high processing cost and low processing performance and quality. MapReduce framework was built as a parallel distributed programming model to process such large-scale datasets effectively and efficiently. This paper presents six successful Big Data software analysis solutions implemented on MapReduce framework, describing their datasets structures and how they were implemented, so that it can guide and help other researchers in their own Big Data solutions.
format Conference or Workshop Item
author Elagib, Sara B.
Najeeb, Athaur Rahman
Hassan Abdalla Hashim, Aisha
Olanrewaju, Rashidah Funke
author_facet Elagib, Sara B.
Najeeb, Athaur Rahman
Hassan Abdalla Hashim, Aisha
Olanrewaju, Rashidah Funke
author_sort Elagib, Sara B.
title Big data analysis solutions using mapReduce framework
title_short Big data analysis solutions using mapReduce framework
title_full Big data analysis solutions using mapReduce framework
title_fullStr Big data analysis solutions using mapReduce framework
title_full_unstemmed Big data analysis solutions using mapReduce framework
title_sort big data analysis solutions using mapreduce framework
publishDate 2014
url http://irep.iium.edu.my/41638/1/41638.pdf
http://irep.iium.edu.my/41638/4/41638_Big%20data%20analysis%20solutions%20using%20map_Scopus.pdf
http://irep.iium.edu.my/41638/
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7031477
_version_ 1643612056320999424
score 13.211869

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