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
- 2. Sungho Moon
- 3. Sangeun Chae
- 4. Wook-Hee Kim
- 5. Jongmoo Choi
- 6. Beomseok Nam
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 102 | The Case for Learned Index Structures | 2018 | SIGMOD | 0.00049545203 |
| 826 | ALEX: An Updatable Adaptive Learned Index | 2020 | SIGMOD | 0.00016224841 |
| 857 | The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds | 2020 | VLDB | 0.00015882892 |
| 1,375 | FITing-Tree: A Data-aware Index Structure | 2019 | SIGMOD | 0.00012303141 |
| 1,460 | Benchmarking Learned Indexes | 2021 | VLDB | 0.00011887068 |
| 1,960 | Compaction management in distributed key-value datastores | 2015 | VLDB | 9.9521444e-05 |
| 2,552 | Updatable Learned Index with Precise Positions | 2021 | VLDB | 8.5530411e-05 |
| 9,346 | Can Learned Indexes be Built Efficiently? A Deep Dive into Sampling Trade-offs | 2024 | SIGMOD | 4.3532026e-05 |
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| 1,460 | Benchmarking Learned Indexes | 2021 | VLDB | 0.00011887068 |
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