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A Spatial Hash Strip Join Algorithm for Effective Handling of Skewed Data  

Shim Young-Bok (충북대학교 컴퓨터교육과)
Lee Jong-Yun (충북대학교 컴퓨터교육과)
Publication Information
Journal of KIISE:Databases / v.32, no.5, 2005 , pp. 536-546 More about this Journal
Abstract
In this paper, we focus on the filtering step of candidate objects for spatial join operations on the input tables that none of the inputs is indexed. Over the last decade, several spatial Join algorithms for the input tables with index have been extensively studied. Those algorithms show excellent performance over most spatial data, while little research on solving the performance degradation in the presence of skewed data has been attempted. Therefore, we propose a spatial hash strip join(SHSJ) algorithm that can refine the problem of skewed data in the conventional spatial hash Join(SHJ) algorithm. The basic idea is similar to the conventional SHJ algorithm, but the differences are that bucket capacities are not limited while allocating data into buckets and SSSJ algorithm is applied to bucket join operations. Finally, as a result of experiment using Tiger/line data set, the performance of the spatial hash strip join operation was improved over existing SHJ algorithm and SSSJ algorithm.
Keywords
Spatial Databases; Spatial Join; Query Processing; Query Optimization;
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