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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
14067
Venue
VLDB
Year
2025
Pagerank
4.3494621e-05
Overall Rank
9,350 | 35.02%
DOI
10.14778/3749646.3749712

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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 0.0040465394
71 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059446482
101 The Case for Learned Index Structures 2018 SIGMOD 0.00049778866
203 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00034868567
329 Neo: A Learned Query Optimizer 2019 VLDB 0.00027301488
634 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00018844568
752 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00017138049
804 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.0001643674
819 ALEX: An Updatable Adaptive Learned Index 2020 SIGMOD 0.00016237497
876 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.00015660534
905 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00015423174
1,404 DB-BERT: A Database Tuning Tool that "Reads the Manual" 2022 SIGMOD 0.00012179714
1,536 Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions 2011 VLDB 0.00011458359
2,090 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 9.5668285e-05
2,769 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 8.1512848e-05
2,781 Flow-Loss: Learning Cardinality Estimates That Matter 2021 VLDB 8.1282042e-05
3,105 GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization 2024 VLDB 7.5567226e-05
3,269 Learned Cardinality Estimation: An In-depth Study 2022 SIGMOD 7.3026051e-05
3,345 Lero: A Learning-to-Rank Query Optimizer 2023 VLDB 7.1908499e-05
3,455 Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation 2022 VLDB 7.0760196e-05
3,729 Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection 2022 VLDB 6.8078013e-05
3,819 Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction 2022 VLDB 6.7267885e-05
3,924 A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation 2021 SIGMOD 6.6227223e-05
3,955 Efficiently Approximating Selectivity Functions using Low Overhead Regression Models 2020 VLDB 6.5895015e-05
4,413 Robust Query Driven Cardinality Estimation under Changing Workloads 2023 VLDB 6.1989918e-05
4,464 LOGER: A Learned Optimizer towards Generating Efficient and Robust Query Execution Plans 2023 VLDB 6.1552798e-05
5,250 One Model to Rule them All: Towards Zero-Shot Learning for Databases 2022 CIDR 5.6007779e-05
5,339 LEON: A New Framework for ML-Aided Query Optimization 2023 VLDB 5.5596755e-05
5,405 ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads 2024 VLDB 5.5243727e-05
5,412 Kepler: Robust Learning for Faster Parametric Query Optimization 2023 SIGMOD 5.5200608e-05
5,528 Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts 2022 SIGMOD 5.4571136e-05
5,682 LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems 2022 SIGMOD 5.3752251e-05
5,941 Eraser: Eliminating Performance Regression on Learned Query Optimizer 2024 VLDB 5.2594013e-05
7,326 Lemo: A Cache-Enhanced Learned Optimizer for Concurrent Queries 2023 SIGMOD 4.7563708e-05
7,564 Modeling Shifting Workloads for Learned Database Systems 2024 SIGMOD 4.7049893e-05
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