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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
hf670c5f1dfeb1e04
Venue
VLDB
Year
2025
Pagerank
5.2965922e-05
Overall Rank
8,638 | 41.95%
DOI
10.14778/3749646.3749712
PDF
Download (CC BY-NC-ND 4.0)

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 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
10,353 Rethinking Query Optimization for Multi-Agent Systems 2027 VLDB 4.9769913e-05
10,644 Divo: Learning a Stable and Effective Query Optimizer with a Diverse Workload 2026 SIGMOD 4.9769913e-05
10,751 OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning 2026 VLDB 4.9769913e-05
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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 0.0023943337
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061067652
40 The Case for Learned Index Structures 2018 SIGMOD 0.00046363107
85 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035876108
144 Neo: A Learned Query Optimizer 2019 VLDB 0.00029090793
361 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00020000855
406 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00019050182
422 ALEX: An Updatable Adaptive Learned Index 2020 SIGMOD 0.00018488849
462 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.00017836105
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
1,058 Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions 2011 VLDB 0.00012224038
1,195 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 0.00011574218
1,245 DB-BERT: A Database Tuning Tool that "Reads the Manual" 2022 SIGMOD 0.0001136308
1,735 Flow-Loss: Learning Cardinality Estimates That Matter 2021 VLDB 9.7566604e-05
2,002 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 9.2076835e-05
2,209 Lero: A Learning-to-Rank Query Optimizer 2023 VLDB 8.8360101e-05
2,227 GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization 2024 VLDB 8.8007923e-05
2,342 Learned Cardinality Estimation: An In-depth Study 2022 SIGMOD 8.6074783e-05
2,518 Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation 2022 VLDB 8.3532841e-05
2,686 Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection 2022 VLDB 8.1300913e-05
2,879 Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction 2022 VLDB 7.9126862e-05
3,053 A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation 2021 SIGMOD 7.7041081e-05
3,208 Efficiently Approximating Selectivity Functions using Low Overhead Regression Models 2020 VLDB 7.5355264e-05
3,327 Robust Query Driven Cardinality Estimation under Changing Workloads 2023 VLDB 7.4233639e-05
3,479 LOGER: A Learned Optimizer towards Generating Efficient and Robust Query Execution Plans 2023 VLDB 7.2665349e-05
4,191 Kepler: Robust Learning for Faster Parametric Query Optimization 2023 SIGMOD 6.7425275e-05
4,240 LEON: A New Framework for ML-Aided Query Optimization 2023 VLDB 6.7064546e-05
4,299 ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads 2024 VLDB 6.6766173e-05
4,536 One Model to Rule them All: Towards Zero-Shot Learning for Databases 2022 CIDR 6.552998e-05
4,559 Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts 2022 SIGMOD 6.5324275e-05
5,043 LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems 2022 SIGMOD 6.2979214e-05
5,438 Eraser: Eliminating Performance Regression on Learned Query Optimizer 2024 VLDB 6.1278045e-05
5,776 Lemo: A Cache-Enhanced Learned Optimizer for Concurrent Queries 2023 SIGMOD 5.9957692e-05
5,850 Modeling Shifting Workloads for Learned Database Systems 2024 SIGMOD 5.9697921e-05
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