FILM: a Fully Learned Index for Larger-than-Memory Databases
Summary: FILM: a fully learned tree index for larger-than-memory DBs using tiny approximation models to index across memory+disk, reducing in-memory index size by orders of magnitude versus anti-caching. An adaptive LRU piggybacked on queries avoids swap overhead, improving query latency and insertion performance. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Chaohong Ma (Renmin University of China)
- 2. Xiaohui Yu (York University)
- 3. Yifan Li (York University)
- 4. Xiaofeng Meng (Renmin University of China)
- 5. Aishan Maoliniyazi (Renmin University of China)
BibTeX Citation
@article{ma_vldb23,
title = {{FILM: a Fully Learned Index for Larger-than-Memory Databases}},
author = {Ma, Chaohong and Yu, Xiaohui and Li, Yifan and Meng, Xiaofeng and Maoliniyazi, Aishan},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {3},
pages = {561--573},
doi = {10.14778/3570690.3570704},
url = {https://doi.org/10.14778/3570690.3570704},
year = {2023}
}
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