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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
8.8360101e-05
Overall Rank
2,209 | 85.16%
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 41 of 41 citing papers.

Rank Citing Paper Year Venue Pagerank
5,316 How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks 2025 SIGMOD 6.1827415e-05
5,438 Eraser: Eliminating Performance Regression on Learned Query Optimizer 2024 VLDB 6.1278045e-05
5,630 Sample-Efficient Cardinality Estimation Using Geometric Deep Learning 2024 VLDB 6.056758e-05
5,700 PilotScope: Steering Databases with Machine Learning Drivers 2024 VLDB 6.028998e-05
5,776 Lemo: A Cache-Enhanced Learned Optimizer for Concurrent Queries 2023 SIGMOD 5.9957692e-05
6,298 Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective 2024 VLDB 5.8177684e-05
6,575 Can Large Language Models Be Query Optimizer for Relational Databases? 2026 SIGMOD 5.7428777e-05
6,636 Join Order Selection with Deep Reinforcement Learning: Fundamentals, Techniques, and Challenges 2023 VLDB 5.7243042e-05
7,021 Rethinking Learned Cost Models: Why Start from Scratch? 2023 SIGMOD 5.6168049e-05
7,072 E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model 2025 VLDB 5.6053987e-05
7,238 RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems 2025 VLDB 5.5764098e-05
7,464 T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees 2025 SIGMOD 5.5189616e-05
7,546 Learned Offline Query Planning via Bayesian Optimization 2025 SIGMOD 5.4966669e-05
7,981 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 5.4117272e-05
8,032 NeurDB: On the Design and Implementation of an AI-powered Autonomous Database 2025 CIDR 5.4017794e-05
8,373 GenJoin: Conditional Generative Plan-to-Plan Query Optimizer that Learns from Subplan Hints 2026 SIGMOD 5.3427119e-05
8,638 LIMAO: A Framework for Lifelong Modular Learned Query Optimization 2025 VLDB 5.2965922e-05
8,969 Conformal Prediction for Verifiable Learned Query Optimization 2025 VLDB 5.2477982e-05
9,556 Athena: An Effective Learning-based Framework for Query Optimizer Performance Improvement 2025 SIGMOD 5.1580326e-05
9,635 Low Rank Learning for Offline Query Optimization 2025 SIGMOD 5.1453041e-05
9,787 Optimizing Dataflow Systems for Scalable Interactive Visualization 2024 SIGMOD 5.1276108e-05
9,962 Graph Transformers for Query Plan Representation: Potentials and Challenges 2025 VLDB 5.1014161e-05
10,320 veDB-HTAP: a Highly Integrated, Efficient and Adaptive HTAP System 2025 VLDB 5.0362412e-05
10,343 An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL 2025 SIGMOD 5.0176429e-05
10,424 Are Learned DBMS Components Robust to Workload Drift?: [Experiments & Analysis] 2026 SIGMOD 4.9769913e-05
10,495 NeurBench: A Benchmark Suite for Learned Database Components with Drift Modeling: [Experiments & Analysis] 2026 SIGMOD 4.9769913e-05
10,607 SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer 2026 SIGMOD 4.9769913e-05
10,644 Divo: Learning a Stable and Effective Query Optimizer with a Diverse Workload 2026 SIGMOD 4.9769913e-05
10,690 Reqo: A Comprehensive Learning-Based Cost Model for Robust and Explainable Query Optimization 2026 SIGMOD 4.9769913e-05
10,703 Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking 2026 SIGMOD 4.9769913e-05
10,708 LIO: A lightweight and interpretable query optimizer based on an evolutionary forest 2026 VLDB 4.9769913e-05
10,751 OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning 2026 VLDB 4.9769913e-05
10,896 MFTune: An Efficient Multi-fidelity Framework for Spark SQL Configuration Tuning 2026 VLDB 4.9769913e-05
10,928 ScaleSense: Cost-Intelligent Scaling Framework via Learned Resource Estimation in Alibaba AnalyticDB 2026 VLDB 4.9769913e-05
10,933 TATA: An Efficient Framework for Task Transfer in Query Plan Representation 2026 VLDB 4.9769913e-05
10,947 Towards Industrial-Scale Parametric Query Optimization 2026 VLDB 4.9769913e-05
11,246 PlanRGCN: Predicting SPARQL Query Performance 2025 VLDB 4.9769913e-05
11,291 Robust Plan Evaluation based on Approximate Probabilistic Machine Learning 2025 VLDB 4.9769913e-05
11,431 Learned Cost Models for Query Optimization: From Batch to Streaming Systems 2025 VLDB 4.9769913e-05
11,449 LEAP: A Low-cost Spark SQL Query Optimizer using Pairwise Comparison 2025 VLDB 4.9769913e-05
11,459 RankPQO: Learning-to-Rank for Parametric Query Optimization 2025 VLDB 4.9769913e-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 0.00061067652
30 SCOPE: Easy and Efficient Parallel Processing of Massive Data Sets 2008 VLDB 0.00050475202
85 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035876108
144 Neo: A Learned Query Optimizer 2019 VLDB 0.00029090793
151 An Efficient, Cost-Driven Index Selection Tool for Microsoft SQL Server 1997 VLDB 0.00028664776
318 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021166957
361 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00020000855
386 Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors 2009 VLDB 0.00019446558
406 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00019050182
462 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.00017836105
492 Database Tuning Advisor for Microsoft SQL Server 2005 2004 VLDB 0.00017406029
510 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00017059914
560 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.00016408613
682 Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques 2012 VLDB 0.00014814858
691 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00014737455
981 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00012713454
995 Analyzing Plan Diagrams of Database Query Optimizers 2005 VLDB 0.00012629969
1,058 Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions 2011 VLDB 0.00012224038
1,065 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012202293
1,195 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 0.00011574218
1,280 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011224914
1,605 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2019 SIGMOD 0.00010095581
2,002 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 9.2076835e-05
2,583 Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation 2021 VLDB 8.2589842e-05
2,837 Query Performance Prediction for Concurrent Queries using Graph Embedding 2020 VLDB 7.9495917e-05
3,527 Identifying Robust Plans through Plan Diagram Reduction 2008 VLDB 7.2283486e-05
3,979 Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload 2021 SIGMOD 6.8791817e-05
4,857 Efficiently Approximating Query Optimizer Plan Diagrams 2008 VLDB 6.3772435e-05
5,110 Steering Query Optimizers: A Practical Take on Big Data Workloads 2021 SIGMOD 6.2678118e-05
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# Overall Rank Paper Year Venue
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