Big data analysis solutions using mapReduce framework

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.

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Abstract

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.

Item Type:	Conference or Workshop Item (Invited Papers)
Additional Information:	3800/41638 (ISBN: 978-147997635-5, DOI: 10.1109/ICCCE.2014.46)
Uncontrolled Keywords:	Big Data, data analysis, MapReduce, data mining
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User:	Dr. Rashidah Funke Olanrewaju
Date Deposited:	18 Feb 2015 09:24
Last Modified:	20 Sep 2017 18:26
URI:	http://irep.iium.edu.my/id/eprint/41638

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