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APQO: An Adaptive Framework for Parametric Query Optimization

Summary: APQO: adaptive PQO that models query parameters and plan embeddings to handle variable/dynamic plan caches vs. fixed-plan PQO. Combines an offline pre-trained foundation model, hybrid data augmentation, and lightweight online calibration to adapt to distribution shifts, improving cache-hit rates and reducing query latency. (summarized by gpt-5-mini on Feb 11 2026)

Paper ID
hb83067003ecd68e5
Venue
SIGMOD
Year
2026
Pagerank
5.1349531e-05
Overall Rank
9,720 | 34.65%
DOI
10.1145/3769761

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{li_sigmod26,
        title = {{APQO: An Adaptive Framework for Parametric Query Optimization}},
        author = {Li, Sijia and Cai, Peng and Zhang, Zhifan and Hu, Huiqi and Zhang, Rong and Zhou, Xuan and Xu, Quanqing and Yang, Chuanhui},
        series = {{SIGMOD} '26},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3769761},
        url = {https://dl.acm.org/doi/10.1145/3769761},
        year = {2026}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
10,721 Pisco: An Isolation Bug Case Reduction and Deduplication Framework 2026 VLDB 4.9793485e-05
10,928 Real-time SQL Plan Management in Oracle 2026 VLDB 4.9793485e-05
10,938 Towards Industrial-Scale Parametric Query Optimization 2026 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 26 of 26 cited papers.

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

Rank Cited Paper Year Venue Pagerank
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061066921
362 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00019989474
461 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.00017829982
560 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.00016403151
982 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00012714044
996 Analyzing Plan Diagrams of Database Query Optimizers 2005 VLDB 0.00012634603
1,199 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 0.00011563985
1,279 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011226878
1,298 Parametric Query Optimization for Linear and Piecewise Linear Cost Functions 2002 VLDB 0.00011120288
1,449 Design and Analysis of Parametric Query Optimization Algorithms 1998 VLDB 0.00010620564
1,612 AniPQO: Almost Non-intrusive Parametric Query Optimization for Nonlinear Cost Functions 2003 VLDB 0.00010072731
2,250 QueryFormer: A Tree Transformer Model for Query Plan Representation 2022 VLDB 8.7533306e-05
2,812 OceanBase: A 707 Million tpmC Distributed Relational Database System 2022 VLDB 7.9811649e-05
2,842 Query Performance Prediction for Concurrent Queries using Graph Embedding 2020 VLDB 7.949193e-05
2,908 AI Meets Database: AI4DB and DB4AI 2021 SIGMOD 7.8742664e-05
3,396 Variance Aware Optimization of Parameterized Queries 2010 SIGMOD 7.3418098e-05
3,527 Identifying Robust Plans through Plan Diagram Reduction 2008 VLDB 7.2310714e-05
3,978 Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload 2021 SIGMOD 6.8807882e-05
4,202 Kepler: Robust Learning for Faster Parametric Query Optimization 2023 SIGMOD 6.7374091e-05
4,657 On the Production of Anorexic Plan Diagrams 2007 VLDB 6.4824233e-05
5,039 Leveraging Query Logs and Machine Learning for Parametric Query Optimization 2022 VLDB 6.3023214e-05
5,078 Leveraging Re-costing for Online Optimization of Parameterized Queries with Guarantees 2017 SIGMOD 6.2857912e-05
6,632 Join Order Selection with Deep Reinforcement Learning: Fundamentals, Techniques, and Challenges 2023 VLDB 5.7270153e-05
8,389 PARQO: Penalty-Aware Robust Plan Selection in Query Optimization 2024 VLDB 5.3413016e-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
11,453 RankPQO: Learning-to-Rank for Parametric Query Optimization 2025 VLDB 4.9793485e-05
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Semantically Similar Papers

# Overall Rank Paper Year Venue
1 1,298 Parametric Query Optimization for Linear and Piecewise Linear Cost Functions 2002 VLDB
2 1,612 AniPQO: Almost Non-intrusive Parametric Query Optimization for Nonlinear Cost Functions 2003 VLDB
3 4,202 Kepler: Robust Learning for Faster Parametric Query Optimization 2023 SIGMOD
4 8,389 PARQO: Penalty-Aware Robust Plan Selection in Query Optimization 2024 VLDB
5 5,078 Leveraging Re-costing for Online Optimization of Parameterized Queries with Guarantees 2017 SIGMOD
6 9,730 PAR2QO: Parametric Penalty-Aware Robust Query Optimization 2025 VLDB
7 11,453 RankPQO: Learning-to-Rank for Parametric Query Optimization 2025 VLDB
8 10,693 Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking 2026 SIGMOD
9 10,938 Towards Industrial-Scale Parametric Query Optimization 2026 VLDB
10 5,039 Leveraging Query Logs and Machine Learning for Parametric Query Optimization 2022 VLDB