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CAMAL: Optimizing LSM-trees via Active Learning

Summary: CAMAL tunes LSM-tree parameters via active learning, coupling ML with cost models to optimize reads/writes. Decoupled active learning, online adaptation to dynamic workloads, and extrapolation yield 28% average gains and up to 8x over prior RocksDB. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h242dde7a889f3f87
Venue
SIGMOD
Year
2024
Pagerank
5.4266123e-05
Overall Rank
7,909 | 46.85%
DOI
10.1145/3677138

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{yu_sigmod24,
        title = {{CAMAL: Optimizing LSM-trees via Active Learning}},
        author = {Yu, Weiping and Luo, Siqiang and Yu, Zihao and Cong, Gao},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3677138},
        url = {https://dl.acm.org/doi/10.1145/3677138},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

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Outgoing Citations (Sorted by Pagerank)

Showing 46 of 46 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
78 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036675568
224 Self-Driving Database Management Systems 2017 CIDR 0.00024011047
236 LinkBench: a Database Benchmark Based on the Facebook Social Graph 2013 SIGMOD 0.00023664907
258 bLSM: A General Purpose Log Structured Merge Tree 2012 SIGMOD 0.00022932099
314 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00021276452
318 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021166957
322 Tuning Database Configuration Parameters with iTuned 2009 VLDB 0.00021034201
400 Monkey: Optimal Navigable Key-Value Store 2017 SIGMOD 0.00019124757
437 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00018310278
462 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.00017836105
560 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.00016408613
691 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00014737455
753 Dostoevsky: Better Space-Time Trade-Offs for LSM-Tree Based Key-Value Stores via Adaptive Removal of Superfluous Merging 2018 SIGMOD 0.00014232329
817 SlimDB: A Space-Efficient Key-Value Storage Engine For Semi-Sorted Data 2017 VLDB 0.00013685662
889 SuRF: Practical Range Query Filtering with Fast Succinct Tries 2018 SIGMOD 0.00013243846
1,065 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012202293
1,289 An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems 2021 VLDB 0.00011159167
1,303 Realtime Data Processing at Facebook 2016 SIGMOD 0.00011101274
1,313 X-Engine: An Optimized Storage Engine for Large-scale E-commerce Transaction Processing 2019 SIGMOD 0.00011055196
1,422 The Log-Structured Merge-Bush & the Wacky Continuum 2019 SIGMOD 0.00010720711
1,569 Compaction management in distributed key-value datastores 2015 VLDB 0.00010207173
1,890 WeTune: Automatic Discovery and Verification of Query Rewrite Rules 2022 SIGMOD 9.4234723e-05
1,891 Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn 2019 CIDR 9.4233024e-05
1,982 Chucky: A Succinct Cuckoo Filter for LSM-Tree 2021 SIGMOD 9.2570284e-05
2,278 Active Learning for ML Enhanced Database Systems 2020 SIGMOD 8.7057608e-05
2,664 Rosetta: A Robust Space-Time Optimized Range Filter for Key-Value Stores 2020 SIGMOD 8.1532061e-05
2,771 Constructing and Analyzing the LSM Compaction Design Space 2021 VLDB 8.0338932e-05
2,788 Lethe: A Tunable Delete-Aware LSM Engine 2020 SIGMOD 8.0114055e-05
2,868 Spooky: Granulating LSM-Tree Compactions Correctly 2022 VLDB 7.9205462e-05
2,996 Accordion: Better Memory Organization for LSM Key-Value Stores 2018 VLDB 7.7670057e-05
3,480 Cosine: A Cloud-Cost Optimized Self-Designing Key-Value Storage Engine 2022 VLDB 7.2661848e-05
3,588 Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation 2021 VLDB 7.1841858e-05
3,672 Leaper: A Learned Prefetcher for Cache Invalidation in LSM-tree based Storage Engines 2020 VLDB 7.1084283e-05
3,964 MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems 2021 SIGMOD 6.889374e-05
4,198 Proteus: A Self-Designing Range Filter 2022 SIGMOD 6.7385809e-05
4,509 Optimization for Active Learning-based Interactive Database Exploration 2019 VLDB 6.5684897e-05
4,775 LogKV: Exploiting Key-Value Stores for Event Log Processing 2013 CIDR 6.4199958e-05
4,851 The RLR-Tree: A Reinforcement Learning Based R-Tree for Spatial Data 2023 SIGMOD 6.377837e-05
5,022 Breaking Down Memory Walls: Adaptive Memory Management in LSM-based Storage Systems 2021 VLDB 6.309271e-05
5,041 Dissecting, Designing, and Optimizing LSM-based Data Stores 2022 SIGMOD 6.2998284e-05
5,047 Lightweight Cardinality Estimation in LSM-based Systems 2018 SIGMOD 6.2972183e-05
5,250 Endure: A Robust Tuning Paradigm for LSM Trees Under Workload Uncertainty 2022 VLDB 6.2092552e-05
6,123 Learning to Optimize LSM-trees: Towards A Reinforcement Learning based Key-Value Store for Dynamic Workloads 2023 SIGMOD 5.8771312e-05
7,915 Tastes Great! Less Filling! High Performance and Accurate Training Data Collection for Self-Driving Database Management Systems 2022 SIGMOD 5.4258674e-05
9,191 Structural Designs Meet Optimality: Exploring Optimized LSM-tree Structures in A Colossal Configuration Space 2024 SIGMOD 5.20942e-05
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