AT-GIS: Highly Parallel Spatial Query Processing with Associative Transducers
Summary: AT-GIS introduces associative transducers (ATs) to fuse parsing and spatial query operators into a single data-parallel pipeline. It processes raw formats with no pre-processing, scales linearly on multi-core CPUs, and on 64 cores outperforms an 8-node Hadoop cluster (3x containment, 10x aggregation). (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Peter Ogden (Imperial College London)
- 2. David Thomas (Imperial College London)
- 3. Peter Pietzuch (Imperial College London)
BibTeX Citation
@inproceedings{ogden_sigmod16,
title = {{AT-GIS: Highly Parallel Spatial Query Processing with Associative Transducers}},
author = {Ogden, Peter and Thomas, David and Pietzuch, Peter},
series = {{SIGMOD} '16},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2882903.2882962},
url = {https://dl.acm.org/doi/10.1145/2882903.2882962},
year = {2016}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,057 | Architecting a Query Compiler for Spatial Workloads | 2020 | SIGMOD | 5.4982831e-05 |
| 9,544 | SwiftSpatial: Spatial Joins on Modern Hardware | 2025 | SIGMOD | 5.2528121e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 11 of 11 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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