Improving Mapreduce Process By Introducing Aggregator Repartition Data for Big Data Analytics
K. Sathesh Kumar1, S. Ramkumar2, K.Shankar3, M.Ilayaraja4
1K.Sathesh Kumar, Department of Computing, Kalasalingam Academy of Research and Education College, Krishnankoil, Virudhunagar (Tamil Nadu), India.
2S.Ramkumar, Department of Computing, Kalasalingam Academy of Research and Education College, Krishnankoil, Virudhunagar (Tamil Nadu), India.
3K.Shankar, Department of Computing, Kalasalingam Academy of Research and Education College, Krishnankoil, Virudhunagar (Tamil Nadu), India.
4M.Ilayaraja, Department of Computing, Kalasalingam Academy of Research and Education, Krishnankoil, Virudhunagar (Tamil Nadu), India.
Manuscript received on 24 November 2019 | Revised Manuscript received on 18 December 2019 | Manuscript Published on 30 December 2019 | PP: 483-487 | Volume-9 Issue-1S4 December 2019 | Retrieval Number: A1109291S419/19©BEIESP | DOI: 10.35940/ijeat.A1109.1291S419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This work suggested data aggregator is used in between the mapper and reducer to enhance the performance of MapReduce. Initially the massive amount of data is partitioned into number of subset of data through the n number of independent mappers and it produces key value pairs for each partitioned data. Then the key value pairs are fed into aggregator where the data from different mappers are combining with smaller amount than the input. Followed by data aggregation data de duplication is carried over then repartition the data based on content, computation and network aware of data. Finally reducer merges the data to produce the final output, the proposed Content, computation and Network Aware (CCNA) MapReducer is compared with the existing Content Aware (CA) MapReducer and Content, computation Aware (CCA) MapReducer.
Keywords: Data Aggregator, Big data, Aggregator Node, Mapreducer.
Scope of the Article: Big Data Analytics for Social Networking using IoT