Efficient Cost Modeling of Space-filling Curves
Summary: Proposes constant-time cost estimators for space-filling curves enabling fast, workload-aware evaluation across many SFC candidates, bridging deterministic and costly dynamic approaches. Builds an RL-based SFC learner using these estimators to efficiently discover high-performance curves. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Guanli Liu (University of Melbourne)
- 2. Lars Kulik (University of Melbourne)
- 3. Christian S. Jensen (Aalborg University)
- 4. Tianyi Li (Aalborg University)
- 5. Renata Borovica-Gajic (University of Melbourne)
- 6. Jianzhong Qi (University of Melbourne)
BibTeX Citation
@article{liu_vldb24,
title = {{Efficient Cost Modeling of Space-filling Curves}},
author = {Liu, Guanli and Kulik, Lars and Jensen, Christian S. and Li, Tianyi and Borovica-Gajic, Renata and Qi, Jianzhong},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {13},
pages = {4773--4785},
doi = {10.14778/3704965.3704982},
url = {https://doi.org/10.14778/3704965.3704982},
year = {2024}
}
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,569 | Toward Drift-Aware Database Benchmarking | 2026 | VLDB | 5.093636e-05 |
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