Spatial Hash-Joins
Summary: Defines a spatial hash-join framework with a two-component partition: bucket extents plus an assignment function; inner partitions adapt while outer partitions are immutable and may replicate items into multiple buckets. No precomputed indices required; it outperforms tree-based spatial joins (even with indices) and offers predictable costs and easy integration with existing hash-join engines. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ming-Ling Lo (University of Michigan)
- 2. Chinya V. Ravishankar (University of Michigan)
BibTeX Citation
@inproceedings{lo_sigmod96,
title = {{Spatial Hash-Joins}},
author = {Lo, Ming-Ling and Ravishankar, Chinya V.},
series = {{SIGMOD} '96},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/233269.233337},
url = {https://dl.acm.org/doi/10.1145/233269.233337},
year = {1996}
}
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