A HYBRID CLUSTERING CRITERION  FOR  R*-TREE ON BUSINESS DATA

Yaokai Feng; Zhibin Wang; Akifumi Makinouchi

doi:10.5220/0002552703460352

A HYBRID CLUSTERING CRITERION FOR R*-TREE ON BUSINESS DATA

Yaokai Feng, Zhibin Wang, Akifumi Makinouchi

2005

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 insert 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.

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Paper Citation

in Harvard Style

Feng Y., Wang Z. and Makinouchi A. (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

in Bibtex Style

@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},
}

in EndNote Style

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