Workload-Adaptive Filtering in Storage Engines
Summary: Adaptive filter for LSM-tree storage engines that remembers frequent false positives, converting them to true negatives for skewed workloads. Outperforms workload-agnostic filters, delivering up to 2x end-to-end throughput. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Joshua Pan (Harvard University)
BibTeX Citation
@inproceedings{pan_sigmod22,
title = {{Workload-Adaptive Filtering in Storage Engines}},
author = {Pan, Joshua},
series = {{SIGMOD} '22},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3514221.3520256},
url = {https://dl.acm.org/doi/10.1145/3514221.3520256},
year = {2022}
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Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 446 | Monkey: Optimal Navigable Key-Value Store | 2017 | SIGMOD | 0.00018332392 |
| 789 | Don't Thrash: How to Cache Your Hash on Flash | 2012 | VLDB | 0.0001401724 |
| 3,577 | Cosine: A Cloud-Cost Optimized Self-Designing Key-Value Storage Engine | 2022 | VLDB | 7.2930211e-05 |
| 4,532 | Stacked Filters: Learning to Filter by Structure | 2021 | VLDB | 6.6436681e-05 |
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