Enhancing Big Data Analysis by using Map-reduce Technique
Abstract
Database is defined as a set of data that is organized and distributed in a manner that permits the user to access the data being stored in an easy and more convenient manner. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work enhances the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on Electroencephalogram (EEG) Big-data as a case study. The proposed approach showed clear enhancement on managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG researchers and specialist with an easy and fast method of handling the EEG big data.
Keywords
Big data; EEg data; Hadoop; Cloud-wave; NoSQL
Full Text:
PDFDOI: https://doi.org/10.11591/eei.v7i1.895
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Bulletin of Electrical Engineering and Informatics (BEEI)
ISSN: 2089-3191
,
e-ISSN: 2302-9285
This journal is published by the
Institute of Advanced Engineering and Science (IAES)
.