Performance Comparison of Hive, Pig & Map Reduce over Variety of Big Data
Yojna Arora1, Dinesh Goyal2
1Dr. Dinesh Goyal, Professor, Department of Computer Science and Engineering, Poornima Institute of Engineering and Technology, Jaipur (Rajasthan), India.
2Dr. Yojna Arora, Department of Computer Science, College of Computer Science and Engineering, Amity University, (Haryana), India.
Manuscript received on 24 January 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 January 2019 | PP: 77-82 | Volume-7 Issue-6, March 2019 | Retrieval Number: E1965017519©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© 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: Big Data refers to that huge amount of data which cannot be analyzed by using traditional analytics methods. With the increase of web content at a rapid rate, only analyzing data is not enough rather managing it with that great pace and efficiency is needed. A new framework Hadoop was implemented in order to perform parallel distributed computing. Hadoop is supported by various frameworks. In this paper, a performance comparison of Pig, Hive and Map Reduce over Big Data is analyzed
Keywords: Pig, Hive, Map Reduce, Hadoop, Big Data
Scope of the Article: High Performance Computing