arrow
Return

Multi-way R-tree joins using indirect predicates

delete2004-09-01
delete1
PRE
AI
H
Ho‐Hyun Park
J
Jun‐Ki Min
C
Chin‐Wan Chung
T
Tae‐Gyu Chang
DOI:10.1016/j.infsof.2003.12.007delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Since spatial join processing consumes much time, several algorithms have been proposed to improve spatial join performance. Spatial join has been processed in two steps, called filter step and refinement step. The M-way R-tree join (MRJ) is a filter step join algorithm, which synchronously traverses M R-trees. In this paper, we introduce indirect predicates which do not directly come from the multi-way join conditions but are indirectly derived from them. By applying indirect predicates as well as direct predicates to MRJ, we can quickly remove the minimum bounding rectangle (MBR) combinations which do not satisfy the direct predicates or the indirect predicates at the parent level. Hence we can reduce the intermediate MBR combinations for the input to the child level processing and improve the performance of MRJ. We call such a multi-way R-tree join algorithm using indirect predicates indirect predicate filtering (IPF). Through experiments using synthetic data and real data, we show that IPF significantly improves the performance of MRJ. (C) 2004 Elsevier B.V. All rights reserved.
Keywords:
spatial databases
spatial join
M-way R-tree join
indirect predicates
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Information and Software Technology cover
Information and Software Technology
IF:
4.3
Papers:
3.7K
Citations:
7.7K

Organization

No organization information available