Mnemosyne: Dynamic Workload-Aware BF Tuning via Accurate Statistics in LSM trees
Summary: Mnemosyne dynamically reallocates Bloom Filters for evolving LSM trees, tuning memory without workload knowledge. It adds Merlin, a sliding-window per-file tracker, and Mnemosyne+ with a refined per-file cost model. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zichen Zhu (Boston University)
- 2. Yanpeng Wei (Tsinghua University)
- 3. Ju Hyoung Mun (Brandeis University)
- 4. Manos Athanassoulis (Boston University)
BibTeX Citation
@inproceedings{zhu_sigmod25,
title = {{Mnemosyne: Dynamic Workload-Aware BF Tuning via Accurate Statistics in LSM trees}},
author = {Zhu, Zichen and Wei, Yanpeng and Mun, Ju Hyoung and Athanassoulis, Manos},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3725327},
url = {https://dl.acm.org/doi/10.1145/3725327},
year = {2025}
}
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,811 | ArceKV: Towards Workload-driven LSM-compactions for Key-Value Store Under Dynamic Workloads | 2026 | VLDB | 5.3652966e-05 |
| 10,225 | Dynamic Flat Filter: A Unified Framework for Scalable and Stable Fingerprint-Based Filters | 2026 | SIGMOD | 5.093636e-05 |
| 10,465 | Improving Range Scan Performance in LSM-trees with Group Caching | 2026 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 25 of 25 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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