Accelerating spatial join operations using bit-indices

Authors:
Elizabeth Antoine;Kotagiri Ramamohanarao;Jie Shao;Rui Zhang
Affiliations:
The University of Melbourne, Victoria, Australia;The University of Melbourne, Victoria, Australia;The University of Melbourne, Victoria, Australia;The University of Melbourne, Victoria, Australia
Venue:
ADC '11 Proceedings of the Twenty-Second Australasian Database Conference - Volume 115
Year:
2011

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Abstract

Spatial join is a very expensive operation in spatial databases. In this paper, we propose an innovative method for accelerating spatial join operations using Spatial Join Bitmap (SJB) indices. The SJB indices are used to keep track of intersecting entities in the joining data sets. We provide algorithms for constructing SJB indices and for maintaining the SJB indices when the data sets are updated. We have performed an extensive study using both real and synthetic data sets of various data distributions. The results show that the use of SJB indices produces substantial speedup ranging from 25% to 150% when compared to Filter trees.