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Data cube computational model with Hadoop MapReduce

Wang, Bo, Gui, Hao, Roantree, Mark and O'Connor, Martin F. (2014) Data cube computational model with Hadoop MapReduce. In: 10th International Conference on Web Information Systems and Technologies (WEBIST 2014), 3-5 Apr 2014, Barcelona, Spain. ISBN 978-989-758-023-9

Abstract
XML has become a widely used and well structured data format for digital document handling and message transmission. To find useful knowledge in XML data, data warehouse and OLAP applications aimed at providing supports for decision making should be developed. Apache Hadoop is an open source cloud computing framework that provides a distributed file system for large scale data processing. In this paper, we discuss an XML data cube model which offers us the complete views to observe XML data, and present a basic algorithm to implement its building process on Hadoop. To improve the efficiency, an optimized algorithm more suitable for this kind of XML data is also proposed. The experimental results given in the paper prove the effectiveness of our optimization strategies.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:XML; Hadoop; Data Warehouse; MapReduce
Subjects:Computer Science > Information technology
Computer Science > Information storage and retrieval systems
Computer Science > Algorithms
DCU Faculties and Centres:Research Initiatives and Centres > INSIGHT Centre for Data Analytics
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in: Proceedings of the 10th International Conference on Web Information Systems and Technologies. 1. SCITEPRESS. ISBN 978-989-758-023-9
Publisher:SCITEPRESS
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland
ID Code:19914
Deposited On:16 Apr 2014 14:09 by Martin F. O'Connor . Last Modified 19 Jul 2018 15:03
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