Version 1
: Received: 25 June 2017 / Approved: 26 June 2017 / Online: 26 June 2017 (06:07:51 CEST)
How to cite:
Dubey, H. Fair: A Hadoop-based Hybrid Model for Faculty Information Retrieval System. Preprints2017, 2017060115. https://doi.org/10.20944/preprints201706.0115.v1
Dubey, H. Fair: A Hadoop-based Hybrid Model for Faculty Information Retrieval System. Preprints 2017, 2017060115. https://doi.org/10.20944/preprints201706.0115.v1
Dubey, H. Fair: A Hadoop-based Hybrid Model for Faculty Information Retrieval System. Preprints2017, 2017060115. https://doi.org/10.20944/preprints201706.0115.v1
APA Style
Dubey, H. (2017). Fair: A Hadoop-based Hybrid Model for Faculty Information Retrieval System. Preprints. https://doi.org/10.20944/preprints201706.0115.v1
Chicago/Turabian Style
Dubey, H. 2017 "Fair: A Hadoop-based Hybrid Model for Faculty Information Retrieval System" Preprints. https://doi.org/10.20944/preprints201706.0115.v1
Abstract
In era of ever-expanding data and knowledge, we lack a centralized system that maps all the faculties to their research works. This problem has not been addressed in the past and it becomes challenging for students to connect with the right faculty of their domain. Since we have so many colleges and faculties this lies in the category of big data problem. In this paper, we present a model which works on the distributed computing environment to tackle big data. The proposed model uses apache spark as an execution engine and hive as database. The results are visualized with the help of Tableau that is connected to Apache Hive to achieve distributed computing.
Keywords
big data,；Hadoop； visualization； model
Subject
Computer Science and Mathematics, Information Systems
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
