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Leveraging Query Logs and Machine Learning for Parametric Query Optimization
Summary: Decouples PQO into populateCache (small plan set) and getPlan (choose cached plans) using log costs. ML-based getPlan latency ~210 μs with sub-optimality 1.05–1.3; populateCache remains efficient and scales to large logs.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 12910
- Venue
- VLDB
- Year
- 2022
- Pagerank
- 4.9688874e-05
- Overall Rank
- 6,667 | 53.62%
- DOI
-
10.14778/3494124.3494126
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 10 of 10 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 5,368 |
Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing |
2022 |
VLDB |
5.5457532e-05 |
| 5,423 |
Kepler: Robust Learning for Faster Parametric Query Optimization |
2023 |
SIGMOD |
5.5130233e-05 |
| 8,020 |
The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions |
2024 |
VLDB |
4.6040862e-05 |
| 8,448 |
PARQO: Penalty-Aware Robust Plan Selection in Query Optimization |
2024 |
VLDB |
4.5100508e-05 |
| 8,854 |
Optimizing the cloud? Don't train models. Build oracles! |
2024 |
CIDR |
4.4349047e-05 |
| 9,960 |
An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL |
2025 |
SIGMOD |
4.2294678e-05 |
| 10,050 |
APQO: An Adaptive Framework for Parametric Query Optimization |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,219 |
Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking |
2026 |
SIGMOD |
4.1945683e-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 |
Outgoing Citations (Sorted by Pagerank)
Showing 19 of 19 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 333 |
Neo: A Learned Query Optimizer |
2019 |
VLDB |
0.00027206884 |
| 339 |
Optimization of Dynamic Query Evaluation Plans |
1994 |
SIGMOD |
0.00026851113 |
| 508 |
Dynamic Query Evaluation Plans |
1989 |
SIGMOD |
0.00021463742 |
| 640 |
Bao: Making Learned Query Optimization Practical |
2021 |
SIGMOD |
0.00018759152 |
| 1,070 |
Analyzing Plan Diagrams of Database Query Optimizers |
2005 |
VLDB |
0.00014316791 |
| 1,236 |
Least Expected Cost Query Optimization: An Exercise in Utility |
1999 |
PODS |
0.00013117798 |
| 1,254 |
Selectivity Estimation for Range Predicates using Lightweight Models |
2019 |
VLDB |
0.00013027411 |
| 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 |
| 1,986 |
AniPQO: Almost Non-intrusive Parametric Query Optimization for Nonlinear Cost Functions |
2003 |
VLDB |
9.8536784e-05 |
| 2,180 |
Least Expected Cost Query Optimization: What Can We Expect? |
2002 |
PODS |
9.3481968e-05 |
| 3,408 |
Query Optimizers: Time to Rethink the Contract? |
2009 |
SIGMOD |
7.1288167e-05 |
| 3,954 |
Efficiently Approximating Selectivity Functions using Low Overhead Regression Models |
2020 |
VLDB |
6.5926838e-05 |
| 4,482 |
Variance Aware Optimization of Parameterized Queries |
2010 |
SIGMOD |
6.1482936e-05 |
| 5,340 |
Efficiently Approximating Query Optimizer Plan Diagrams |
2008 |
VLDB |
5.5623066e-05 |
| 5,466 |
On the Production of Anorexic Plan Diagrams |
2007 |
VLDB |
5.4909203e-05 |
| 6,139 |
Closing The Query Processing Loop in Oracle 11g |
2008 |
VLDB |
5.1912675e-05 |
| 6,479 |
Leveraging Re-costing for Online Optimization of Parameterized Queries with Guarantees |
2017 |
SIGMOD |
5.0483805e-05 |
| 8,184 |
Dynamic Plan Generation for Parameterized Queries |
2009 |
SIGMOD |
4.5654336e-05 |
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