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SCompression: Enhancing Database Knob Tuning Efficiency Through Slice-Based OLTP Workload Compression

Summary: Defines the OLTP-specific compression objective for knob tuning and introduces SCompression: slice-by-time compression that preserves concurrency and transaction context so compressed workloads reflect config-sensitive performance variation. Segments workloads, slices to retain concurrency, and cluster-samples slices under time constraints; replays compressed workloads to speed up tuning up to 40× with ≈5% performance loss. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
h27a80dc22b9dcdd1
Venue
VLDB
Year
2025
Pagerank
5.0281656e-05
Overall Rank
10,333 | 30.53%
DOI
10.14778/3725688.3725712

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{cai_vldb25,
        title = {{SCompression: Enhancing Database Knob Tuning Efficiency Through Slice-Based OLTP Workload Compression}},
        author = {Cai, Baoqing and Liu, Yu and Ma, Lin and Huang, Pingqi and Lian, Bingcheng and Zhou, Ke and Yuan, Jia and Yang, Jie and Cai, Xiaofan and Wu, Peijun},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {6},
        pages = {1865--1878},
        doi = {10.14778/3725688.3725712},
        url = {https://doi.org/10.14778/3725688.3725712},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 28 of 28 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
78 Automatic Database Management System Tuning Through Large-scale Machine Learning 2017 SIGMOD 0.00036684414
314 An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning 2019 SIGMOD 0.00021282642
322 Tuning Database Configuration Parameters with iTuned 2009 VLDB 0.00021041865
437 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00018315867
460 Query-based Workload Forecasting for Self-Driving Database Management Systems 2018 SIGMOD 0.00017842695
491 Database Tuning Advisor for Microsoft SQL Server 2005 2004 VLDB 0.00017413042
508 Adaptive Self-Tuning Memory in DB2 2006 VLDB 0.00017089907
971 Reducing the Storage Overhead of Main-Memory OLTP Databases with Hybrid Indexes 2016 SIGMOD 0.00012766019
1,242 Compressing SQL Workloads 2002 SIGMOD 0.00011373611
1,397 Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms 2020 VLDB 0.00010789242
2,209 The Case for Predictive Database Systems: Opportunities and Challenges 2011 CIDR 8.8326479e-05
2,231 GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization 2024 VLDB 8.7982985e-05
2,720 ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases 2021 SIGMOD 8.0966919e-05
2,772 Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation 2022 VLDB 8.035288e-05
3,032 iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases 2019 VLDB 7.7351139e-05
3,051 LlamaTune: Sample-Efficient DBMS Configuration Tuning 2022 VLDB 7.7055931e-05
3,486 HUNTER: An Online Cloud Database Hybrid Tuning System for Personalized Requirements 2022 SIGMOD 7.2636102e-05
3,815 Comprehensive and Efficient Workload Compression 2021 VLDB 7.0075744e-05
3,844 Database Tuning Advisor for Microsoft SQL Server 2005: Demo 2005 SIGMOD 6.9871379e-05
3,965 MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems 2021 SIGMOD 6.8918628e-05
4,079 Towards Dynamic and Safe Configuration Tuning for Cloud Databases 2022 SIGMOD 6.818264e-05
4,252 Primitives for Workload Summarization and Implications for SQL 2003 VLDB 6.7015609e-05
4,681 LOCAT: Low-Overhead Online Configuration Auto-Tuning of Spark SQL Applications 2022 SIGMOD 6.4721364e-05
5,286 An Efficient Transfer Learning Based Configuration Adviser for Database Tuning 2024 VLDB 6.1971399e-05
5,630 ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning 2022 SIGMOD 6.0582762e-05
7,915 Tastes Great! Less Filling! High Performance and Accurate Training Data Collection for Self-Driving Database Management Systems 2022 SIGMOD 5.4276987e-05
9,133 Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems 2024 VLDB 5.2229655e-05
9,706 Database Gyms 2023 CIDR 5.1376763e-05
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