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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
- 7357
- Venue
- SIGMOD
- Year
- 2026
- Pagerank
- 4.1945683e-05
- Overall Rank
- 10,050 | 30.09%
- DOI
-
10.1145/3769761
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
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 |
| 71 |
How Good Are Query Optimizers, Really? |
2016 |
VLDB |
0.00059038975 |
| 640 |
Bao: Making Learned Query Optimization Practical |
2021 |
SIGMOD |
0.00018759152 |
| 806 |
An End-to-End Learning-based Cost Estimator |
2020 |
VLDB |
0.00016434274 |
| 884 |
Plan-Structured Deep Neural Network Models for Query Performance Prediction |
2019 |
VLDB |
0.00015654004 |
| 1,070 |
Analyzing Plan Diagrams of Database Query Optimizers |
2005 |
VLDB |
0.00014316791 |
| 1,638 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.00011049779 |
| 1,647 |
Parametric Query Optimization for Linear and Piecewise Linear Cost Functions |
2002 |
VLDB |
0.00011033757 |
| 1,726 |
Design and Analysis of Parametric Query Optimization Algorithms |
1998 |
VLDB |
0.00010741411 |
| 1,855 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00010315245 |
| 1,986 |
AniPQO: Almost Non-intrusive Parametric Query Optimization for Nonlinear Cost Functions |
2003 |
VLDB |
9.8536784e-05 |
| 2,121 |
Balsa: Learning a Query Optimizer Without Expert Demonstrations |
2022 |
SIGMOD |
9.5017232e-05 |
| 3,169 |
QueryFormer: A Tree Transformer Model for Query Plan Representation |
2022 |
VLDB |
7.4498425e-05 |
| 3,473 |
AI Meets Database: AI4DB and DB4AI |
2021 |
SIGMOD |
7.062864e-05 |
| 3,580 |
Query Performance Prediction for Concurrent Queries using Graph Embedding |
2020 |
VLDB |
6.9500996e-05 |
| 3,628 |
OceanBase: A 707 Million tpmC Distributed Relational Database System |
2022 |
VLDB |
6.9031596e-05 |
| 4,348 |
Identifying Robust Plans through Plan Diagram Reduction |
2008 |
VLDB |
6.2660237e-05 |
| 4,482 |
Variance Aware Optimization of Parameterized Queries |
2010 |
SIGMOD |
6.1482936e-05 |
| 4,804 |
Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload |
2021 |
SIGMOD |
5.910467e-05 |
| 5,423 |
Kepler: Robust Learning for Faster Parametric Query Optimization |
2023 |
SIGMOD |
5.5130233e-05 |
| 5,466 |
On the Production of Anorexic Plan Diagrams |
2007 |
VLDB |
5.4909203e-05 |
| 6,479 |
Leveraging Re-costing for Online Optimization of Parameterized Queries with Guarantees |
2017 |
SIGMOD |
5.0483805e-05 |
| 6,667 |
Leveraging Query Logs and Machine Learning for Parametric Query Optimization |
2022 |
VLDB |
4.9688874e-05 |
| 6,862 |
Join Order Selection with Deep Reinforcement Learning: Fundamentals, Techniques, and Challenges |
2023 |
VLDB |
4.9051979e-05 |
| 8,448 |
PARQO: Penalty-Aware Robust Plan Selection in Query Optimization |
2024 |
VLDB |
4.5100508e-05 |
| 9,006 |
Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems |
2024 |
VLDB |
4.4101482e-05 |
| 10,880 |
RankPQO: Learning-to-Rank for Parametric Query Optimization |
2025 |
VLDB |
4.1945683e-05 |
Semantically Similar Papers
| Overall Rank |
Paper |
Year |
Venue |
Pagerank |
| 5,530 |
Permutable Compiled Queries: Dynamically Adapting Compiled Queries without Recompiling |
2021 |
VLDB |
5.4554282e-05 |
| 1,647 |
Parametric Query Optimization for Linear and Piecewise Linear Cost Functions |
2002 |
VLDB |
0.00011033757 |
| 1,986 |
AniPQO: Almost Non-intrusive Parametric Query Optimization for Nonlinear Cost Functions |
2003 |
VLDB |
9.8536784e-05 |
| 5,423 |
Kepler: Robust Learning for Faster Parametric Query Optimization |
2023 |
SIGMOD |
5.5130233e-05 |
| 8,448 |
PARQO: Penalty-Aware Robust Plan Selection in Query Optimization |
2024 |
VLDB |
4.5100508e-05 |
| 6,479 |
Leveraging Re-costing for Online Optimization of Parameterized Queries with Guarantees |
2017 |
SIGMOD |
5.0483805e-05 |
| 10,751 |
PAR2QO: Parametric Penalty-Aware Robust Query Optimization |
2025 |
VLDB |
4.1945683e-05 |
| 10,880 |
RankPQO: Learning-to-Rank for Parametric Query Optimization |
2025 |
VLDB |
4.1945683e-05 |
| 10,219 |
Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking |
2026 |
SIGMOD |
4.1945683e-05 |
| 6,667 |
Leveraging Query Logs and Machine Learning for Parametric Query Optimization |
2022 |
VLDB |
4.9688874e-05 |