Processing Real-World Datasets Using Apache Hadoop Tools
N. Deshai1, B.V.D.S. Sekhar2, S. Vemkataramana3
1N. Deshai, Department of Information Technology, Sagi Rama Krishnam Raju Engineering College, Bhimavaram (Andhra Pradesh), India.
2B.V.D.S. Sekhar, Department of Information Technology, Sagi Rama Krishnam Raju Engineering College, Bhimavaram (Andhra Pradesh), India.
3S. Venkata Ramana, Department of Information Technology, Sagi Rama Krishnam Raju Engineering College, Bhimavaram (Andhra Pradesh), India.
Manuscript received on 12 May 2019 | Revised Manuscript received on 06 June 2019 | Manuscript Published on 15 June 2019 | PP: 209-213 | Volume-8 Issue-1S3 June 2019 | Retrieval Number: A10370681S319/2019©BEIESP
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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: Today’s digital world applications are extremely demanding for essential requirements to significantly process and store an enormous size of datasets. Because the digital world applications tremendously generate mostly unstructured, unbounded data sets that beyond the limits and double day by day. During the last decade, many organizations have been facing major problems to handling and manage massive chunks of data, which could not be processed efficiently due to lack of enhancements on existing technologies also utilizing only existing centralized architecture standards and techniques. Only data processing with the existing technology and centralized environment, the organization actually faced difficulties of efficiency, poor performance and high operating costs, in addition to time pressures and optimization. These large organizations have been able to address the significant problems of trying to extract, store, process world massive data only with the assistance of Hadoop frameworks and distributed architectures. To overcome this problem as efficiently by using the latest open source Apache frameworks, which are, turn to centralized architecture to the more latest distributed architecture. In this paper, we use Apache Hadoop Map Reduce framework is one of the best data handling weapon and most exciting source of techniques and comprehensive features, which are widely used in the digital world computations regarding the distributed architecture manner, and more accomplish with high fault tolerance, high reliability, great scalability, great synchronization and data locality.
Keywords: Big Data, Apache Hadoop, Data Processing, Map Reduce.
Scope of the Article: Image analysis and Processing