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Authors: Yaokai Feng ; Zhibin Wang and Akifumi Makinouchi

Affiliation: The Graduate School of Information Science and Electrical Engineering, Kyushu University, Japan

ISBN: 972-8865-19-8

Keyword(s): Multidimensional indices, R*-tree, clustering criterion, Multidimensional range query, TPC-H.

Related Ontology Subjects/Areas/Topics: Data Warehouses and OLAP ; Databases and Information Systems Integration ; Enterprise Information Systems

Abstract: It is well-known that multidimensional indices are efficient to improve the query performance on relational data. As one successful multi-dimensional index structure, R*-tree, a famous member of the R-tree family, is very popular. The clustering pattern of the objects (i.e., tuples in relational tables) among R*-tree leaf nodes is one of the deceive factors on performance of range queries, a popular kind of queries on business data. Then, how is the clustering pattern formed? In this paper, we point out that the insert algorithm of R*-tree, especially, its clustering criterion of choosing subtrees for new coming objects, determines the clustering pattern of the tuples among the leaf nodes. According to our discussion and observations, it becomes clear that the present clustering criterion of R*-tree can not lead to a good clustering pattern of tuples when R*-tree is applied to business data, which greatly degrades query performance. After that, a hybrid clustering criterion for the in sert algorithm of R*-tree is introduced. Our discussion and experiments indicate that query performance of R*-tree on business data is improved clearly by the hybrid criterion. (More)

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Paper citation in several formats:
Feng Y.; Wang Z.; Makinouchi A. and (2005). A HYBRID CLUSTERING CRITERION FOR R*-TREE ON BUSINESS DATA.In Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 972-8865-19-8, pages 346-352. DOI: 10.5220/0002552703460352

@conference{iceis05,
author={Yaokai Feng and Zhibin Wang and Akifumi Makinouchi},
title={A HYBRID CLUSTERING CRITERION FOR R*-TREE ON BUSINESS DATA},
booktitle={Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2005},
pages={346-352},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002552703460352},
isbn={972-8865-19-8},
}

TY - CONF

JO - Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - A HYBRID CLUSTERING CRITERION FOR R*-TREE ON BUSINESS DATA
SN - 972-8865-19-8
AU - Feng, Y.
AU - Wang, Z.
AU - Makinouchi, A.
PY - 2005
SP - 346
EP - 352
DO - 10.5220/0002552703460352

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