Compressed Spatial Hierarchical Bitmap (cSHB) Indexes for Efficiently Processing Spatial Range Query Workloads
Summary: Compressed Spatial Hierarchical Bitmap (cSHB) index for efficient spatial range queries, using hierarchical bitmaps with compression to prune candidates. Cost models and workload-driven query planning select index nodes and bitwise operations to retrieve matching objects. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Parth Nagarkar (Arizona State University)
- 2. K. Selçuk Candan (Arizona State University)
- 3. Aneesha Bhat (Arizona State University)
BibTeX Citation
@article{nagarkar_vldb15,
title = {{Compressed Spatial Hierarchical Bitmap (cSHB) Indexes for Efficiently Processing Spatial Range Query Workloads}},
author = {Nagarkar, Parth and Candan, K. Selçuk and Bhat, Aneesha},
journal = {PVLDB},
series = {{VLDB} '15},
volume = {8},
number = {12},
pages = {1382--1393},
doi = {10.14778/2824032.2824038},
url = {https://doi.org/10.14778/2824032.2824038},
year = {2015}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,349 | Tree-Encoded Bitmaps | 2020 | SIGMOD | 5.4460774e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,067 | Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce | 2013 | VLDB | 0.00012327784 |
| 2,960 | XXL - A Library Approach to Supporting Efficient Implementations of Advanced Database Queries | 2001 | VLDB | 7.9182423e-05 |
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