Hybrid Query System

International Journal of Computer Science and Engineering

© 2020 by SSRG - IJCSE Journal

Volume 7 Issue 5

Year of Publication : 2020

Authors : Ramya M, Thirumahal R

10.14445/23488387/IJCSE-V7I5P103

How to Cite?

Ramya M, Thirumahal R, "Hybrid Query System," SSRG International Journal of Computer Science and Engineering , vol. 7,  no. 5, pp. 8-11, 2020. Crossref, https://doi.org/10.14445/23488387/IJCSE-V7I5P103

Abstract:

NoSQL databases are becoming increasingly popular in Web analytics for Big Data applications and supporting large websites because of their high availability and usability. Every NoSQL framework has its own API and usually does not follow standards such as SQL systems hence there is a challenge to handle SQL and NoSQL data in a single application. The proposed approach will provide its own abstract methods to query the data spread in MYSQL and MONGODB databases. These methods operate on an intermediate form of representing objects which is then converted to corresponding object representations. Data can be stored based on its nature on MYSQL and MONGODB databases and can be retrieved. So the proposed approach is to develop a query processing system to retrieve the data from MYSQL and MongoDB databases. The ontology for the patient record has been created using the global XML schema. The XML files are read using the JDOM parser and according to the user requirement, find and display whether the attributes are present in MYSQL or MONGODB. Formulate the query for the respective database and get the output from the database. Finally combine the output and display the final data.

Keywords:

Data integration, semi structured data

References:

[1] Ramon Lawrence “Integration and virtualization of relational SQL and NoSQL systems including MySQL and MongoDB” IEEE 2014.
[2] Wu Xiaoli,Yao Yuan “XML-based Heterogeneous Database Integration System Design and Implementation” Department of Computer Science and Engineering, Henan University of Urban Construction 978-1-4244-5540-9/10/$26.00 ©2010 IEEE.
[3] KIRAN V K, Dr R VIJAYAKUMAR “Ontology Based Data Integration of NoSQL Data stores” IEEE 2011.
[4] P.Priya, Dr.R.Rajalaxmi “Ontology based Semantic Query Suggestion for Movie search IEEE 2018
[5] Mahmudul Hassan, Srividya K. Bansal “Semantic Data Querying Over NoSQL Databases with Apache Spark” International Conference on Information Reuse and Integration for Data Science IEEE 2018.
[6] Shuxia Ren, Xu Lu” Application of Ontology in Medical Heterogeneous Data Integration” 3rd International Conference on Big Data Analysis IEEE 2018.
[7] Chong-Shan Ran, Ma-Chuan Wang “An XML Schema-Based Data Integration” 978-1-4244-5540-9/10/$26.00 © IEEE 2010.
[8] Rohini R. Rao, Krishnamoorthi Makkithaya, Neha Gupta” Ontology based semantic representation for Public Health data integration” 978-1-4799-6629-5/14/$31.00_c IEEE 2014.
[9] Adekunle o. Afolabi, pekka toivanen “Integration of Recommendation Systems Into Connected Health for Effective Management of Chronic Diseases” IEEE 2019.