Database Paper Browser

Back to papers

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
13767
Venue
VLDB
Year
2024
Pagerank
5.2594013e-05
Overall Rank
5,941 | 58.72%
DOI
10.14778/3641204.3641205

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 10 of 10 citing papers.

Rank Citing Paper Year Venue Pagerank
6,883 PilotScope: Steering Databases with Machine Learning Drivers 2024 VLDB 4.8918682e-05
8,660 Learned Offline Query Planning via Bayesian Optimization 2025 SIGMOD 4.4680058e-05
9,282 DBG-PT: A Large Language Model Assisted Query Performance Regression Debugger 2024 VLDB 4.3598981e-05
9,350 LIMAO: A Framework for Lifelong Modular Learned Query Optimization 2025 VLDB 4.3494621e-05
9,581 Low Rank Learning for Offline Query Optimization 2025 SIGMOD 4.3186744e-05
9,643 Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment 2025 SIGMOD 4.3067693e-05
9,877 PRICE: A Pretrained Model for Cross-Database Cardinality Estimation 2025 VLDB 4.2615675e-05
10,018 GenJoin: Conditional Generative Plan-to-Plan Query Optimizer that Learns from Subplan Hints 2026 SIGMOD 4.1905499e-05
10,156 Divo: Learning a Stable and Effective Query Optimizer with a Diverse Workload 2026 SIGMOD 4.1905499e-05
10,271 OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning 2026 VLDB 4.1905499e-05
Previous Page 1 / 1 Next

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 0.0040465394
71 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059446482
203 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00034868567
237 An Efficient, Cost-Driven Index Selection Tool for Microsoft SQL Server 1997 VLDB 0.00031727601
329 Neo: A Learned Query Optimizer 2019 VLDB 0.00027301488
606 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00019251186
634 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00018844568
779 QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning 2019 VLDB 0.00016719473
804 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.0001643674
876 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.00015660534
1,185 JOSIE: Overlap Set Similarity Search for Finding Joinable Tables in Data Lakes 2019 SIGMOD 0.00013432692
1,536 Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions 2011 VLDB 0.00011458359
1,638 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00011050093
1,699 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00010848882
1,856 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00010319105
1,892 Black or White? How to Develop an AutoTuner for Memory-based Analytics 2020 SIGMOD 0.00010176219
1,921 Selecting Subexpressions to Materialize at Datacenter Scale 2018 VLDB 0.00010085899
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
3,345 Lero: A Learning-to-Rank Query Optimizer 2023 VLDB 7.1908499e-05
3,692 iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases 2019 VLDB 6.8328808e-05
3,729 Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection 2022 VLDB 6.8078013e-05
4,342 Identifying Robust Plans through Plan Diagram Reduction 2008 VLDB 6.2680535e-05
5,528 Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts 2022 SIGMOD 5.4571136e-05
6,860 Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data 2023 SIGMOD 4.9008421e-05
8,219 PerfGuard: Deploying ML-for-Systems without Performance Regressions, Almost! 2021 VLDB 4.551524e-05
Previous Page 1 / 1 Next

Semantically Similar Papers

Overall Rank Paper Year Venue Pagerank
5,412 Kepler: Robust Learning for Faster Parametric Query Optimization 2023 SIGMOD 5.5200608e-05
329 Neo: A Learned Query Optimizer 2019 VLDB 0.00027301488
3,729 Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection 2022 VLDB 6.8078013e-05
3,955 Efficiently Approximating Selectivity Functions using Low Overhead Regression Models 2020 VLDB 6.5895015e-05
8,479 Can Large Language Models Be Query Optimizer for Relational Databases? 2026 SIGMOD 4.4967983e-05
10,219 Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking 2026 SIGMOD 4.1905499e-05
3,345 Lero: A Learning-to-Rank Query Optimizer 2023 VLDB 7.1908499e-05
7,009 Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective 2024 VLDB 4.8597992e-05
7,220 Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation 2023 SIGMOD 4.7926382e-05
4,464 LOGER: A Learned Optimizer towards Generating Efficient and Robust Query Execution Plans 2023 VLDB 6.1552798e-05