An Efficient Approach for Processing Big Data with Incremental MapReduce |
Author(s): |
| Solanke Poonam G. , MBES's College of Engineering, Ambajogai.; Solanke Poonam G, MBES's College of Engineering, Ambajogai. |
Keywords: |
| Big data, Hadoop, incremental MapReduce, iterative. |
Abstract |
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Now a day, data is constantly evolving and becomes a big data. The data is being generated from different sources – transactions, social media, sensors, digital images, video, audio and clickstreams for domains together with healthcare, retail, energy and utilities. Big data with 3 V’s: volume, variety and velocity. For processing such big volume of data, variety of data and the data with high velocity and having high storage capacity, we introduced Hadoop which is evolved day by day. We used MapReduce at this point as a programming model. In this paper we worn Incremental MapReduce most extensively used framework for processing big data. To improve the time of processing big data and optimizing data content of big data we applied PageRank and k-means iteratively along with MapReduce. Therefore to process big data incremental MapReduce approach is used. |
Other Details |
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Paper ID: IJSRDV4I20104 Published in: Volume : 4, Issue : 2 Publication Date: 01/05/2016 Page(s): 53-57 |
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