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November Edition 2021

International Journal of Applied Information Systems solicits high quality original research papers for the November 2021 Edition of the journal. The last date of research paper submission is October 15, 2021.

Online Analytical Processing on Hadoop using Apache Kylin

Supriya Vitthal Ranawade, Shivani Navale, Akshay Dhamal, Kuldeep Deshpande, Chandrashekhar Ghuge. Published in Information Sciences

International Journal of Applied Information Systems
Year of Publication: 2017
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Supriya Vitthal Ranawade, Shivani Navale, Akshay Dhamal, Kuldeep Deshpande, Chandrashekhar Ghuge
10.5120/ijais2017451682
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  1. Supriya Vitthal Ranawade, Shivani Navale, Akshay Dhamal, Kuldeep Deshpande and Chandrashekhar Ghuge. Online Analytical Processing on Hadoop using Apache Kylin. International Journal of Applied Information Systems 12(2):1-5, May 2017. URL, DOI BibTeX

    @article{10.5120/ijais2017451682,
    	author = "Supriya Vitthal Ranawade and Shivani Navale and Akshay Dhamal and Kuldeep Deshpande and Chandrashekhar Ghuge",
    	title = "Online Analytical Processing on Hadoop using Apache Kylin",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "May 2017",
    	volume = 12,
    	number = 2,
    	month = "May",
    	year = 2017,
    	issn = "2249-0868",
    	pages = "1-5",
    	url = "http://www.ijais.org/archives/volume12/number2/983-2017451682",
    	doi = "10.5120/ijais2017451682",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"
    }
    

Abstract

In the Big Data age, it is necessary to remodel the traditional data warehousing and Online Analytical Processing (OLAP) system. Many challenges are posed to the traditional platforms due to the ever increasing data. In this paper, we have proposed a system which overcomes the challenges and is also beneficial to the business organizations. The proposed system mainly focuses on OLAP on Hadoop platform using Apache Kylin. Kylin is an OLAP engine which builds OLAP cubes from the data present in hive and stores the cubes in HBase for further analysis. The cubes stored in HBase are analyzed by firing SQL-like analytics queries. Also, reports and dashboards are further generated on the underlying cubes that provides powerful insights of the company data. This helps the business users to take decisions that are profitable to the organization. The proposed system is a boon to small as well as large scale business organizations. The aim of the paper is to present a system which builds OLAP cubes on Hadoop and generate insightful reports for business users.

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Keywords

Analytics, OLAP, Hadoop, Kylin, Hive, Datawarehouse