Architecting a Query Compiler for Spatial Workloads
Summary: Shows why standard query compilation misses spatial workloads; uses partial evaluation to push codegen into spatial structures. Extends LB2 with spatial types, predicates, indexing, and operators; matches library performance and beats relational/map-reduce. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ruby Y. Tahboub (Purdue University)
- 2. Tiark Rompf (Purdue University)
BibTeX Citation
@inproceedings{tahboub_sigmod20,
title = {{Architecting a Query Compiler for Spatial Workloads}},
author = {Tahboub, Ruby Y. and Rompf, Tiark},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3389701},
url = {https://dl.acm.org/doi/10.1145/3318464.3389701},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,301 | Babelfish: Efficient Execution of Polyglot Queries | 2022 | VLDB | 6.2750553e-05 |
| 8,638 | Towards A Polyglot Framework for Factorized ML | 2021 | VLDB | 5.395289e-05 |
| 10,072 | Query Compilation Without Regrets | 2024 | SIGMOD | 5.1624689e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 20 of 20 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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