Semi-structured data analysis and visualisation using NoSQL. (2018)
- Record Type:
- Journal Article
- Title:
- Semi-structured data analysis and visualisation using NoSQL. (2018)
- Main Title:
- Semi-structured data analysis and visualisation using NoSQL
- Authors:
- Hiriyannaiah, Srinidhi
Siddesh, G.M.
Anoop, P.
Srinivasa, K.G. - Abstract:
- In the field of computing, every day huge amounts of data are created by scientific experiments, companies and users' activities. These large datasets are labelled as 'big data', presenting new challenges for computer science researchers and professionals in terms of storage, processing and analysis. Traditional relational database systems (RDBMS) supported with conventional searches cannot be effectively used to handle such multi-structured data. NoSQL databases complement to the challenges of managing RDBMS with big data and facilitate in further analysis of data. In this paper, we introduce a framework that aims at analysing semi-structured data applications using NoSQL database MongoDB. The proposed framework focuses on the key aspects needed for semi-structured data analytics in terms of data collection, data parsing and data prediction. The layers involved in the framework are request layer facilitating the queries from user, input layer that interfaces the data sources and the analytics layer; and the output layer facilitating the visualisation of the analytics performed. A performance analysis for select+fetch operations needed for analytics, of MySQL and MongoDB is carried out where NoSQL database MongoDB outperforms MySQL database. The proposed framework is applied on predicting the performance and monitoring of cluster of servers.
- Is Part Of:
- International journal of big data intelligence. Volume 5:Number 3(2018)
- Journal:
- International journal of big data intelligence
- Issue:
- Volume 5:Number 3(2018)
- Issue Display:
- Volume 5, Issue 3 (2018)
- Year:
- 2018
- Volume:
- 5
- Issue:
- 3
- Issue Sort Value:
- 2018-0005-0003-0000
- Page Start:
- 133
- Page End:
- 142
- Publication Date:
- 2018
- Subjects:
- analytics -- semi-structured data -- big data analytics -- server performance monitoring -- cluster analytics -- MongoDB -- NoSQL analytics
Big data -- Periodicals
005.705 - Journal URLs:
- http://www.inderscience.com/jhome.php?jcode=ijbdi ↗
http://www.inderscience.com/ ↗ - Languages:
- English
- ISSNs:
- 2053-1389
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 9210.xml