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Lero: A Learning-to-Rank Query Optimizer

Summary: Lero: a non‑intrusive learning‑to‑rank layer that uses pairwise classifiers to compare plans instead of regressing costs. Pluggable into existing DBMS (Postgres prototype), it continuously adapts to workloads and cuts execution time vs native optimizer by up to 70% (vs other learned optimizers up to 37%). (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
hbb604c140db832df
Venue
VLDB
Year
2023
Pagerank
8.8848923e-05
Overall Rank
2,190 | 85.33%
DOI
10.14778/3583140.3583160
PDF
Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{zhu_vldb23,
        title = {{Lero: A Learning-to-Rank Query Optimizer}},
        author = {Zhu, Rong and Chen, Wei and Ding, Bolin and Chen, Xingguang and Pfadler, Andreas and Wu, Ziniu and Zhou, Jingren},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {6},
        pages = {1466--1479},
        doi = {10.14778/3583140.3583160},
        url = {https://doi.org/10.14778/3583140.3583160},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 42 of 42 citing papers.

Rank Citing Paper Year Venue Pagerank
4,641 How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks 2025 SIGMOD 6.4739208e-05
5,453 Eraser: Eliminating Performance Regression on Learned Query Optimizer 2024 VLDB 6.1077838e-05
5,457 Sample-Efficient Cardinality Estimation Using Geometric Deep Learning 2024 VLDB 6.1058928e-05
5,713 PilotScope: Steering Databases with Machine Learning Drivers 2024 VLDB 6.0090633e-05
5,794 Lemo: A Cache-Enhanced Learned Optimizer for Concurrent Queries 2023 SIGMOD 5.9759435e-05
6,109 Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective 2024 VLDB 5.8676956e-05
6,158 Rethinking Learned Cost Models: Why Start from Scratch? 2023 SIGMOD 5.8518237e-05
6,584 Can Large Language Models Be Query Optimizer for Relational Databases? 2026 SIGMOD 5.72395e-05
6,646 Join Order Selection with Deep Reinforcement Learning: Fundamentals, Techniques, and Challenges 2023 VLDB 5.7053761e-05
7,092 E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model 2025 VLDB 5.5868637e-05
7,257 RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems 2025 VLDB 5.5579707e-05
7,483 T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees 2025 SIGMOD 5.5007125e-05
7,561 Learned Offline Query Planning via Bayesian Optimization 2025 SIGMOD 5.4784915e-05
7,997 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 5.3938336e-05
8,050 NeurDB: On the Design and Implementation of an AI-powered Autonomous Database 2025 CIDR 5.3839177e-05
8,389 GenJoin: Conditional Generative Plan-to-Plan Query Optimizer that Learns from Subplan Hints 2026 SIGMOD 5.3250456e-05
8,657 LIMAO: A Framework for Lifelong Modular Learned Query Optimization 2025 VLDB 5.2790784e-05
8,989 Conformal Prediction for Verifiable Learned Query Optimization 2025 VLDB 5.2304457e-05
9,583 Athena: An Effective Learning-based Framework for Query Optimizer Performance Improvement 2025 SIGMOD 5.140977e-05
9,662 Low Rank Learning for Offline Query Optimization 2025 SIGMOD 5.1283524e-05
9,819 Optimizing Dataflow Systems for Scalable Interactive Visualization 2024 SIGMOD 5.1106557e-05
9,995 Graph Transformers for Query Plan Representation: Potentials and Challenges 2025 VLDB 5.0845476e-05
10,109 veDB-HTAP: a Highly Integrated, Efficient and Adaptive HTAP System 2025 VLDB 5.0672857e-05
10,370 An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL 2025 SIGMOD 5.0010514e-05
10,392 E-LQO: A Comprehensive Energy Evaluation Framework for Learned Query Optimization 2027 SIGMOD 4.9605343e-05
10,490 Are Learned DBMS Components Robust to Workload Drift?: [Experiments & Analysis] 2026 SIGMOD 4.9605343e-05
10,561 NeurBench: A Benchmark Suite for Learned Database Components with Drift Modeling: [Experiments & Analysis] 2026 SIGMOD 4.9605343e-05
10,668 SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer 2026 SIGMOD 4.9605343e-05
10,705 Divo: Learning a Stable and Effective Query Optimizer with a Diverse Workload 2026 SIGMOD 4.9605343e-05
10,751 Reqo: A Comprehensive Learning-Based Cost Model for Robust and Explainable Query Optimization 2026 SIGMOD 4.9605343e-05
10,764 Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking 2026 SIGMOD 4.9605343e-05
10,769 LIO: A lightweight and interpretable query optimizer based on an evolutionary forest 2026 VLDB 4.9605343e-05
10,812 OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning 2026 VLDB 4.9605343e-05
10,957 MFTune: An Efficient Multi-fidelity Framework for Spark SQL Configuration Tuning 2026 VLDB 4.9605343e-05
10,989 ScaleSense: Cost-Intelligent Scaling Framework via Learned Resource Estimation in Alibaba AnalyticDB 2026 VLDB 4.9605343e-05
10,994 TATA: An Efficient Framework for Task Transfer in Query Plan Representation 2026 VLDB 4.9605343e-05
11,008 Towards Industrial-Scale Parametric Query Optimization 2026 VLDB 4.9605343e-05
11,302 PlanRGCN: Predicting SPARQL Query Performance 2025 VLDB 4.9605343e-05
11,347 Robust Plan Evaluation based on Approximate Probabilistic Machine Learning 2025 VLDB 4.9605343e-05
11,484 Learned Cost Models for Query Optimization: From Batch to Streaming Systems 2025 VLDB 4.9605343e-05
11,501 LEAP: A Low-cost Spark SQL Query Optimizer using Pairwise Comparison 2025 VLDB 4.9605343e-05
11,511 RankPQO: Learning-to-Rank for Parametric Query Optimization 2025 VLDB 4.9605343e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 29 of 29 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 0.00061463175
30 SCOPE: Easy and Efficient Parallel Processing of Massive Data Sets 2008 VLDB 0.00050364918
84 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035920657
142 Neo: A Learned Query Optimizer 2019 VLDB 0.00029114937
151 An Efficient, Cost-Driven Index Selection Tool for Microsoft SQL Server 1997 VLDB 0.00028611216
320 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021128745
355 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00020146245
381 Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors 2009 VLDB 0.00019497061
405 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00019020138
453 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.0001801482
493 Database Tuning Advisor for Microsoft SQL Server 2005 2004 VLDB 0.0001735831
508 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00017108973
545 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.0001657599
676 Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques 2012 VLDB 0.00014838681
690 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00014703258
983 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00012677179
996 Analyzing Plan Diagrams of Database Query Optimizers 2005 VLDB 0.00012595827
1,061 Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions 2011 VLDB 0.00012207625
1,064 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012181459
1,175 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 0.00011630532
1,282 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011197535
1,609 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2019 SIGMOD 0.0001007196
2,009 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 9.1813272e-05
2,584 Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation 2021 VLDB 8.2435322e-05
2,768 Query Performance Prediction for Concurrent Queries using Graph Embedding 2020 VLDB 8.0199086e-05
3,531 Identifying Robust Plans through Plan Diagram Reduction 2008 VLDB 7.2065332e-05
3,967 Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload 2021 SIGMOD 6.8772718e-05
4,876 Efficiently Approximating Query Optimizer Plan Diagrams 2008 VLDB 6.357646e-05
5,126 Steering Query Optimizers: A Practical Take on Big Data Workloads 2021 SIGMOD 6.2493606e-05
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Semantically Similar Papers

# Overall Rank Paper Year Venue
1 10,764 Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking 2026 SIGMOD
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