Oasis: An Optimal Disjoint Segmented Learned Range Filter
Summary: Oasis optimally prunes large empty key-space intervals and maps remaining disjoint segments into a compressed bitmap, improving learned range-filter space/FPR tradeoffs with guarantees. Oasis+ unifies learned and conventional filters, achieving up to 1.4×/6.2× RocksDB gains. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Guanduo Chen (Fudan University)
- 2. Zhenying He (Fudan University)
- 3. Meng Li (Nanjing University)
- 4. Siqiang Luo (Nanyang Technological University)
BibTeX Citation
@article{chen_vldb24,
title = {{Oasis: An Optimal Disjoint Segmented Learned Range Filter}},
author = {Chen, Guanduo and He, Zhenying and Li, Meng and Luo, Siqiang},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {8},
pages = {1911--1924},
doi = {10.14778/3659437.3659447},
url = {https://doi.org/10.14778/3659437.3659447},
year = {2024}
}
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