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Eraser: Eliminating Performance Regression on Learned Query Optimizer

Summary: Eraser removes performance regressions in learned query optimizers by estimating per-plan prediction reliability with a two-stage approach: a coarse filter for unseen features and cluster-based fine-grained reliability scoring. Pluggable across systems (Postgres, Spark), it preserves learned-optimizer gains while largely eliminating regressions and adapting to dynamic workloads. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
h6a4a4f77eaa7a777
Venue
VLDB
Year
2024
Pagerank
6.1239873e-05
Overall Rank
5,456 | 63.32%
DOI
10.14778/3641204.3641205

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{weng_vldb24,
        title = {{Eraser: Eliminating Performance Regression on Learned Query Optimizer}},
        author = {Weng, Lianggui and Zhu, Rong and Wu, Di and Ding, Bolin and Zheng, Bolong and Zhou, Jingren},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {5},
        pages = {926--938},
        doi = {10.14778/3641204.3641205},
        url = {https://doi.org/10.14778/3641204.3641205},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 11 of 11 citing papers.

Rank Citing Paper Year Venue Pagerank
5,871 PilotScope: Steering Databases with Machine Learning Drivers 2024 VLDB 5.9639223e-05
7,764 DBG-PT: A Large Language Model Assisted Query Performance Regression Debugger 2024 VLDB 5.4564979e-05
8,332 Learned Offline Query Planning via Bayesian Optimization 2025 SIGMOD 5.3528188e-05
9,023 Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment 2025 SIGMOD 5.2348677e-05
9,300 GenJoin: Conditional Generative Plan-to-Plan Query Optimizer that Learns from Subplan Hints 2026 SIGMOD 5.1987909e-05
9,610 LIMAO: A Framework for Lifelong Modular Learned Query Optimization 2025 VLDB 5.1526493e-05
9,670 Low Rank Learning for Offline Query Optimization 2025 SIGMOD 5.1452097e-05
10,216 PRICE: A Pretrained Model for Cross-Database Cardinality Estimation 2025 VLDB 5.0584922e-05
10,633 Divo: Learning a Stable and Effective Query Optimizer with a Diverse Workload 2026 SIGMOD 4.9793485e-05
10,741 OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning 2026 VLDB 4.9793485e-05
10,941 Ultron: History-Based Query Optimization at Databricks 2026 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 26 of 26 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 0.0023947656
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061066921
85 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035864347
145 Neo: A Learned Query Optimizer 2019 VLDB 0.0002908188
151 An Efficient, Cost-Driven Index Selection Tool for Microsoft SQL Server 1997 VLDB 0.00028672526
318 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021167555
362 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00019989474
437 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00018315867
461 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.00017829982
560 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.00016403151
694 JOSIE: Overlap Set Similarity Search for Finding Joinable Tables in Data Lakes 2019 SIGMOD 0.00014727089
982 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00012714044
1,060 Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions 2011 VLDB 0.00012224575
1,064 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012202282
1,199 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 0.00011563985
1,279 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011226878
1,699 Black or White? How to Develop an AutoTuner for Memory-based Analytics 2020 SIGMOD 9.8445322e-05
1,745 Selecting Subexpressions to Materialize at Datacenter Scale 2018 VLDB 9.7343818e-05
2,004 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 9.2065719e-05
2,210 Lero: A Learning-to-Rank Query Optimizer 2023 VLDB 8.8257742e-05
2,690 Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection 2022 VLDB 8.1258173e-05
3,032 iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases 2019 VLDB 7.7351139e-05
3,527 Identifying Robust Plans through Plan Diagram Reduction 2008 VLDB 7.2310714e-05
4,563 Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts 2022 SIGMOD 6.5320994e-05
5,716 Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data 2023 SIGMOD 6.0194657e-05
7,363 PerfGuard: Deploying ML-for-Systems without Performance Regressions, Almost! 2021 VLDB 5.5418564e-05
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