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Big-data Management using Map Reduce on Cloud: Case study, EEG Images' Data | ||
| Al-Khwarizmi Engineering Journal | ||
| Article 1, Volume 13, Issue 1, 2017, Pages 129-137 | ||
| Author | ||
| Sahar Mahdie Klim | ||
| Abstract | ||
| Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. 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 studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for 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; Cloud Computing; Electroencephalogram; MapReduce; Hadoop | ||
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