Cloud-based OLAP over big data: Application scenarios and performance analysis

Cuzzocrea, A; Moussa, R; Xu, G; Grasso, GM

Cloud-based OLAP over big data: Application scenarios and performance analysis

Cuzzocrea, A Moussa, R Xu, G

Grasso, GM

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 2015 IEEE/ACM 15th International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2015, 2015, pp. 921 - 927
Issue Date:: 2015-07-07

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Field	Value	Language
dc.contributor.author	Cuzzocrea, A	en_US
dc.contributor.author	Moussa, R	en_US
dc.contributor.author	Xu, G https://orcid.org/0000-0003-4493-6663	en_US
dc.contributor.author	Grasso, GM	en_US
dc.date.issued	2015-07-07	en_US
dc.identifier.citation	Proceedings - 2015 IEEE/ACM 15th International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2015, 2015, pp. 921 - 927	en_US
dc.identifier.isbn	9781479980062	en_US
dc.identifier.uri	http://hdl.handle.net/10453/41842
dc.description.abstract	© 2015 IEEE. Following our previous research results, in this paper we provide two authoritative application scenarios that build on top of OLAP, a middleware for parallel processing of OLAP queries that truly realizes effective and efficiently OLAP over Big Data. We have provided two authoritative case studies, namely parallel OLAP data cube processing and virtual OLAP data cube design, for which we also propose a comprehensive performance evaluation and analysis. Derived analysis clearly confirms the benefits of our proposed framework.	en_US
dc.relation.ispartof	Proceedings - 2015 IEEE/ACM 15th International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2015	en_US
dc.relation.isbasedon	10.1109/CCGrid.2015.174	en_US
dc.title	Cloud-based OLAP over big data: Application scenarios and performance analysis	en_US
dc.type	Conference Proceeding
utslib.for	080101 Adaptive Agents and Intelligent Robotics	en_US
utslib.for	0806 Information Systems	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2015 IEEE. Following our previous research results, in this paper we provide two authoritative application scenarios that build on top of OLAP, a middleware for parallel processing of OLAP queries that truly realizes effective and efficiently OLAP over Big Data. We have provided two authoritative case studies, namely parallel OLAP data cube processing and virtual OLAP data cube design, for which we also propose a comprehensive performance evaluation and analysis. Derived analysis clearly confirms the benefits of our proposed framework.

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http://hdl.handle.net/10453/41842