OLAP*: Effectively and efficiently supporting parallel OLAP over big data

Alfredo CUZZOCREA, Rim MOUSSA, Guandong XU

Research output: Chapter in Book/Report/Conference proceedingChapters

46 Citations (Scopus)

Abstract

In this paper, we investigate solutions relying on data partitioning schemes for parallel building of OLAP data cubes, suitable to novel Big Data environments, and we propose the framework OLAP*, along with the associated benchmark TPC-H*d, a suitable transformation of the well-known data warehouse benchmark TPC-H. We demonstrate through performance measurements the efficiency of the proposed framework, developed on top of the ROLAP server Mondrian. Copyright © 2013 Springer-Verlag Berlin Heidelberg.

Original languageEnglish
Title of host publicationModel and data engineering: Third International Conference, MEDI 2013, Amantea, Italy, September 25-27, 2013 proceedings
EditorsAlfredo CUZZOCREA, Sofian MAABOUT
Place of PublicationBerlin
PublisherSpringer
Pages38-49
ISBN (Electronic)9783642413667
ISBN (Print)9783642413650
DOIs
Publication statusPublished - 2013

Citation

Cuzzocrea, A., Moussa, R., & Xu, G. (2013). OLAP*: Effectively and efficiently supporting parallel OLAP over big data. In A. Cuzzocrea & S. Maabout (Eds.), Model and data engineering: Third International Conference, MEDI 2013, Amantea, Italy, September 25-27, 2013 proceedings (pp. 38-49). Springer. https://doi.org/10.1007/978-3-642-41366-7_4

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