Reqo: A Comprehensive Learning-Based Cost Model for Robust and Explainable Query Optimization

Summary: Reqo: a learning-based query optimization cost model that jointly attacks plan generation, plan representation, and plan selection. Key novelty: explainable subgraph attribution for plan hints, Bi-GNN+GRU tree encoding, and uncertainty-aware learning-to-rank for robust cost estimation. (summarized by gpt-5-mini on Apr 11 2026)

Paper ID: 7515
Venue: SIGMOD
Year: 2026
Pagerank: 4.1945683e-05
Overall Rank: 10,203 | 29.02%
DOI: 10.1145/3786689

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Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 22 of 22 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
333	Neo: A Learned Query Optimizer	2019	VLDB	0.00027206884
629	Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors	2009	VLDB	0.00018942366
640	Bao: Making Learned Query Optimization Practical	2021	SIGMOD	0.00018759152
806	An End-to-End Learning-based Cost Estimator	2020	VLDB	0.00016434274
1,638	Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation	2022	VLDB	0.00011049779
2,631	Plan Bouquets: Query Processing without Selectivity Estimation	2014	SIGMOD	8.4101843e-05
2,783	Flow-Loss: Learning Cardinality Estimates That Matter	2021	VLDB	8.1293383e-05
2,985	DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems	2021	VLDB	7.7795847e-05
3,169	QueryFormer: A Tree Transformer Model for Query Plan Representation	2022	VLDB	7.4498425e-05
3,348	Lero: A Learning-to-Rank Query Optimizer	2023	VLDB	7.1904529e-05
3,499	Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation	2021	VLDB	7.0376445e-05
3,727	Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection	2022	VLDB	6.8141709e-05
3,828	Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction	2022	VLDB	6.7208524e-05
3,951	Why You Should Run TPC-DS: A Workload Analysis	2007	VLDB	6.5953162e-05
4,434	Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process	2022	SIGMOD	6.1929999e-05
5,334	LEON: A New Framework for ML-Aided Query Optimization	2023	VLDB	5.5649836e-05
5,423	Kepler: Robust Learning for Faster Parametric Query Optimization	2023	SIGMOD	5.5130233e-05
5,640	AutoSteer: Learned Query Optimization for Any SQL Database	2023	VLDB	5.3933314e-05
5,930	FASTgres: Making Learned Query Optimizer Hinting Effective	2023	VLDB	5.2682075e-05
6,685	How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks	2025	SIGMOD	4.9627485e-05
10,627	Robust Plan Evaluation based on Approximate Probabilistic Machine Learning	2025	VLDB	4.1945683e-05

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8,448	PARQO: Penalty-Aware Robust Plan Selection in Query Optimization	2024	VLDB	4.5100508e-05
3,348	Lero: A Learning-to-Rank Query Optimizer	2023	VLDB	7.1904529e-05
8,783	GEqO: ML-Accelerated Semantic Equivalence Detection	2023	SIGMOD	4.452825e-05
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806	An End-to-End Learning-based Cost Estimator	2020	VLDB	0.00016434274
6,685	How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks	2025	SIGMOD	4.9627485e-05
3,169	QueryFormer: A Tree Transformer Model for Query Plan Representation	2022	VLDB	7.4498425e-05
9,587	Low Rank Learning for Offline Query Optimization	2025	SIGMOD	4.3215645e-05
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