Improving query performance on OLAP-data using enhanced multidimensional indices

Yaokai Feng, Akifumi Makinouchi, Hiroshi Ryu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Multidimensional indices are efficient to improve the query performance on OLAP data. As one multi-dimensional index structure, R*-tree is popular and successful, which is a member of the famous R-tree family. We enhance the R*-tree to improve the performance of range queries on OLAP data. First, the following observations are presented. (1) The clustering pattern of the tuples (of the OLAP data) among the R*-tree leaf nodes is a decisive factor on range search performance and it is controllable. (2) There often exist many slender nodes when the R*-tree is used to index OLAP data, which causes some problems both with the R*-tree construction and with queries. And then, we propose an approach to control the clustering pattern of tuples and propose an approach to solve the problems of slender nodes, where slender nodes refer to those having a very narrow side (even the side length is zero) in some dimension. Our proposals are examined by experiments using synthetic data and TPC-H benchmark data.

Original languageEnglish
Title of host publicationICEIS 2004 - Proceedings of the Sixth International Conference on Enterprise Information Systems
EditorsI. Seruca, J. Filipe, S. Hammoudi, J. Cordeiro
Pages282-289
Number of pages8
Publication statusPublished - Nov 24 2004
EventICEIS 2004 - Proceedings of the Sixth International Conference on Enterprise Information Systems - Porto, Portugal
Duration: Apr 14 2004Apr 17 2004

Publication series

NameICEIS 2004 - Proceedings of the Sixth International Conference on Enterprise Information Systems

Other

OtherICEIS 2004 - Proceedings of the Sixth International Conference on Enterprise Information Systems
Country/TerritoryPortugal
CityPorto
Period4/14/044/17/04

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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