From Learning to Recycling: A Log-Structured Learned-Less Index
Summary: Learned-Less Index: a log-structured learned index for LSM KV stores that recycles/merges existing linear regression models instead of retraining from sorted keys, making model construction up to 615x faster than Greedy-PLR. Prebuilt models are available at SSTable creation, improving query speed and compaction under high concurrency despite larger prediction error. (summarized by gpt-5-mini on Apr 11 2026)
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Authors
- 1. Hera Koo (Sungkyunkwan University)
- 2. Sungho Moon (Sungkyunkwan University)
- 3. Sangeun Chae (Sungkyunkwan University)
- 4. Wook-Hee Kim (Konkuk University)
- 5. Jongmoo Choi (Dankook University)
- 6. Beomseok Nam (Sungkyunkwan University)
BibTeX Citation
@inproceedings{koo_sigmod26,
title = {{From Learning to Recycling: A Log-Structured Learned-Less Index}},
author = {Koo, Hera and Moon, Sungho and Chae, Sangeun and Kim, Wook-Hee and Choi, Jongmoo and Nam, Beomseok},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3786654},
url = {https://dl.acm.org/doi/10.1145/3786654},
year = {2026}
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Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 40 | The Case for Learned Index Structures | 2018 | SIGMOD | 0.00046363107 |
| 422 | ALEX: An Updatable Adaptive Learned Index | 2020 | SIGMOD | 0.00018488849 |
| 458 | The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds | 2020 | VLDB | 0.00017880664 |
| 768 | FITing-Tree: A Data-aware Index Structure | 2019 | SIGMOD | 0.00014107655 |
| 835 | Benchmarking Learned Indexes | 2021 | VLDB | 0.00013575971 |
| 1,525 | Updatable Learned Index with Precise Positions | 2021 | VLDB | 0.00010355133 |
| 1,569 | Compaction management in distributed key-value datastores | 2015 | VLDB | 0.00010207173 |
| 9,601 | Can Learned Indexes be Built Efficiently? A Deep Dive into Sampling Trade-offs | 2024 | SIGMOD | 5.153951e-05 |
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