Conformal Prediction for Verifiable Learned Query Optimization

Summary: Cast LQO verification as a conformal prediction problem to yield user-controlled pre-execution latency bounds, CP-based runtime verification with violation handling, and adaptive CP to handle distribution shifts. Applied to Balsa/Lero/RTOS, CP-guided plan search uses those bounds to steer optimization, producing tight guarantees and large empirical gains. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 14097
Venue: VLDB
Year: 2025
Pagerank: 5.093636e-05
Overall Rank: 10,884 | 25.33%
DOI: 10.14778/3742728.3742755

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

1. Hanwen Liu (University of Southern California)
2. Shashank Giridhara (Amazon)
3. Ibrahim Sabek (University of Southern California)

BibTeX Citation

@article{liu_vldb25,
        title = {{Conformal Prediction for Verifiable Learned Query Optimization}},
        author = {Liu, Hanwen and Giridhara, Shashank and Sabek, Ibrahim},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {8},
        pages = {2653--2666},
        doi = {10.14778/3742728.3742755},
        url = {https://doi.org/10.14778/3742728.3742755},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 18 of 18 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
1	Access Path Selection in a Relational Database Management System	1979	SIGMOD	0.0024089429
18	How Good Are Query Optimizers, Really?	2016	VLDB	0.00059284255
84	Learned Cardinalities: Estimating Correlated Joins with Deep Learning	2019	CIDR	0.00035838391
154	Neo: A Learned Query Optimizer	2019	VLDB	0.00028726181
378	Bao: Making Learned Query Optimization Practical	2021	SIGMOD	0.00019638121
401	Deep Unsupervised Cardinality Estimation	2020	VLDB	0.00019092557
465	An End-to-End Learning-based Cost Estimator	2020	VLDB	0.0001803934
513	NeuroCard: One Cardinality Estimator for All Tables	2021	VLDB	0.00017190574
563	Plan-Structured Deep Neural Network Models for Query Performance Prediction	2019	VLDB	0.0001650812
566	Towards a Robust Query Optimizer: A Principled and Practical Approach	2005	SIGMOD	0.00016436005
1,241	Balsa: Learning a Query Optimizer Without Expert Demonstrations	2022	SIGMOD	0.00011521639
1,876	Flow-Loss: Learning Cardinality Estimates That Matter	2021	VLDB	9.5717543e-05
2,420	Lero: A Learning-to-Rank Query Optimizer	2023	VLDB	8.605257e-05
2,723	Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation	2022	VLDB	8.2049453e-05
3,338	Robust Query Driven Cardinality Estimation under Changing Workloads	2023	VLDB	7.5068221e-05
4,470	Kepler: Robust Learning for Faster Parametric Query Optimization	2023	SIGMOD	6.6817353e-05
6,323	Modeling Shifting Workloads for Learned Database Systems	2024	SIGMOD	5.9141228e-05
9,123	BASE: Bridging the Gap between Cost and Latency for Query Optimization	2023	VLDB	5.3193264e-05

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