DBScholar

Back to papers

LIMAO: A Framework for Lifelong Modular Learned Query Optimization

Summary: LIMAO: a lifelong, modular framework that equips learned query optimizers with attention-based neural composition and continual learning to retain cost-prediction knowledge across evolving workloads. Engine-agnostic plug-in improves plan stability and performance (large runtime reductions vs. baselines and Postgres) and mitigates catastrophic forgetting. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
14254
Venue
VLDB
Year
2025
Pagerank
5.2709145e-05
Overall Rank
9,428 | 35.32%
DOI
10.14778/3749646.3749712

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{zhang_vldb25,
        title = {{LIMAO: A Framework for Lifelong Modular Learned Query Optimization}},
        author = {Zhang, Qihan and Xie, Shaolin and Sabek, Ibrahim},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {11},
        pages = {4546--4559},
        doi = {10.14778/3749646.3749712},
        url = {https://doi.org/10.14778/3749646.3749712},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,445 Divo: Learning a Stable and Effective Query Optimizer with a Diverse Workload 2026 SIGMOD 5.093636e-05
10,559 OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning 2026 VLDB 5.093636e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 35 of 35 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
43 The Case for Learned Index Structures 2018 SIGMOD 0.00046060254
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
447 ALEX: An Updatable Adaptive Learned Index 2020 SIGMOD 0.00018322593
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
1,071 Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions 2011 VLDB 0.00012322342
1,241 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 0.00011521639
1,337 DB-BERT: A Database Tuning Tool that "Reads the Manual" 2022 SIGMOD 0.00011117488
1,876 Flow-Loss: Learning Cardinality Estimates That Matter 2021 VLDB 9.5717543e-05
1,988 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 9.3501502e-05
2,298 GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization 2024 VLDB 8.7886538e-05
2,420 Lero: A Learning-to-Rank Query Optimizer 2023 VLDB 8.605257e-05
2,543 Learned Cardinality Estimation: An In-depth Study 2022 SIGMOD 8.4445934e-05
2,723 Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation 2022 VLDB 8.2049453e-05
2,762 Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection 2022 VLDB 8.1539867e-05
2,844 Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction 2022 VLDB 8.0608767e-05
3,086 A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation 2021 SIGMOD 7.7708642e-05
3,162 Efficiently Approximating Selectivity Functions using Low Overhead Regression Models 2020 VLDB 7.6785856e-05
3,338 Robust Query Driven Cardinality Estimation under Changing Workloads 2023 VLDB 7.5068221e-05
3,516 LOGER: A Learned Optimizer towards Generating Efficient and Robust Query Execution Plans 2023 VLDB 7.3524442e-05
4,349 ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads 2024 VLDB 6.7504619e-05
4,434 LEON: A New Framework for ML-Aided Query Optimization 2023 VLDB 6.7079088e-05
4,468 One Model to Rule them All: Towards Zero-Shot Learning for Databases 2022 CIDR 6.6819041e-05
4,470 Kepler: Robust Learning for Faster Parametric Query Optimization 2023 SIGMOD 6.6817353e-05
4,612 Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts 2022 SIGMOD 6.6072026e-05
5,148 LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems 2022 SIGMOD 6.3465986e-05
5,573 Eraser: Eliminating Performance Regression on Learned Query Optimizer 2024 VLDB 6.1682747e-05
5,701 Lemo: A Cache-Enhanced Learned Optimizer for Concurrent Queries 2023 SIGMOD 6.1167049e-05
6,323 Modeling Shifting Workloads for Learned Database Systems 2024 SIGMOD 5.9141228e-05
Previous Page 1 / 1 Next

Semantically Similar Papers

# Overall Rank Paper Year Venue
1 6,088 How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks 2025 SIGMOD
2 10,513 LIO: A lightweight and interpretable query optimizer based on an evolutionary forest 2026 VLDB
3 2,769 A Layered Aggregate Engine for Analytics Workloads 2019 SIGMOD
4 154 Neo: A Learned Query Optimizer 2019 VLDB
5 11,548 DeepO: A Learned Query Optimizer 2022 SIGMOD
6 6,271 Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective 2024 VLDB
7 2,420 Lero: A Learning-to-Rank Query Optimizer 2023 VLDB
8 7,809 Can Large Language Models Be Query Optimizer for Relational Databases? 2026 SIGMOD
9 5,701 Lemo: A Cache-Enhanced Learned Optimizer for Concurrent Queries 2023 SIGMOD
10 9,601 Low Rank Learning for Offline Query Optimization 2025 SIGMOD