Data Cube Computational Model with Hadoop MapReduce

Bo Wang; Hao Gui; Mark Roantree; Martin F. O

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Paper

Data Cube Computational Model with Hadoop MapReduce

Topics: Distributed and Parallel Applications; XML and Data Management

In Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST, 193-199, 2014 , Barcelona, Spain

Authors: Bo Wang ¹ ; Hao Gui ¹ ; Mark Roantree ² and Martin F. O'Connor ²

Affiliations: ¹ Wuhan University, China ; ² Dublin City University, Ireland

Keyword(s): XML, Hadoop, Data Warehouse, MapReduce.

Related Ontology Subjects/Areas/Topics: Distributed and Parallel Applications ; Internet Technology ; Web Information Systems and Technologies ; XML and Data Management

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.

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Paper citation in several formats:

Wang, B.; Gui, H.; Roantree, M. and O'Connor, M. (2014). Data Cube Computational Model with Hadoop MapReduce. In Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST; ISBN 978-989-758-023-9; ISSN 2184-3252, SciTePress, pages 193-199. DOI: 10.5220/0004935001930199

@conference{webist14,
author={Bo Wang. and Hao Gui. and Mark Roantree. and Martin F. O'Connor.},
title={Data Cube Computational Model with Hadoop MapReduce},
booktitle={Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST},
year={2014},
pages={193-199},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004935001930199},
isbn={978-989-758-023-9},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST
TI - Data Cube Computational Model with Hadoop MapReduce
SN - 978-989-758-023-9
IS - 2184-3252
AU - Wang, B.
AU - Gui, H.
AU - Roantree, M.
AU - O'Connor, M.
PY - 2014
SP - 193
EP - 199
DO - 10.5220/0004935001930199
PB - SciTePress