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Kepler: Robust Learning for Faster Parametric Query Optimization

Summary: Kepler: end-to-end learning-based parametric query optimization that bypasses unreliable cost models. Row Count Evolution perturbs sub-plans; candidates are evaluated by actual executions, and uncertainty-aware ML predicts the fastest plan for PostgreSQL speedups. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6613
Venue
SIGMOD
Year
2023
Pagerank
5.5200608e-05
Overall Rank
5,412 | 62.39%
DOI
10.1145/3588963

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 19 of 19 citing papers.

Rank Citing Paper Year Venue Pagerank
6,687 How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks 2025 SIGMOD 4.957987e-05
7,118 ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation 2024 SIGMOD 4.8204951e-05
8,003 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 4.6049527e-05
8,440 PARQO: Penalty-Aware Robust Plan Selection in Query Optimization 2024 VLDB 4.505741e-05
8,660 Learned Offline Query Planning via Bayesian Optimization 2025 SIGMOD 4.4680058e-05
8,854 Optimizing the cloud? Don't train models. Build oracles! 2024 CIDR 4.4306537e-05
9,350 LIMAO: A Framework for Lifelong Modular Learned Query Optimization 2025 VLDB 4.3494621e-05
9,692 ROME: Robust Query Optimization via Parallel Multi-Plan Execution 2024 SIGMOD 4.2986161e-05
9,824 Athena: An Effective Learning-based Framework for Query Optimizer Performance Improvement 2025 SIGMOD 4.2710095e-05
9,959 An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL 2025 SIGMOD 4.2254157e-05
10,050 APQO: An Adaptive Framework for Parametric Query Optimization 2026 SIGMOD 4.1905499e-05
10,112 SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer 2026 SIGMOD 4.1905499e-05
10,203 Reqo: A Comprehensive Learning-Based Cost Model for Robust and Explainable Query Optimization 2026 SIGMOD 4.1905499e-05
10,219 Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking 2026 SIGMOD 4.1905499e-05
10,241 Robust Predicate Transfer with Dynamic Execution 2026 VLDB 4.1905499e-05
10,300 TATA: An Efficient Framework for Task Transfer in Query Plan Representation 2026 VLDB 4.1905499e-05
10,638 Conformal Prediction for Verifiable Learned Query Optimization 2025 VLDB 4.1905499e-05
10,757 PAR2QO: Parametric Penalty-Aware Robust Query Optimization 2025 VLDB 4.1905499e-05
10,884 RankPQO: Learning-to-Rank for Parametric Query Optimization 2025 VLDB 4.1905499e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 24 of 24 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
71 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059446482
203 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00034868567
329 Neo: A Learned Query Optimizer 2019 VLDB 0.00027301488
339 OLTP-Bench: An Extensible Testbed for Benchmarking Relational Databases 2014 VLDB 0.00026895683
634 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00018844568
752 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00017138049
905 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00015423174
1,064 Analyzing Plan Diagrams of Database Query Optimizers 2005 VLDB 0.00014348262
1,638 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00011050093
1,644 Parametric Query Optimization for Linear and Piecewise Linear Cost Functions 2002 VLDB 0.0001102889
1,699 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00010848882
1,756 Sampling-Based Query Re-Optimization 2016 SIGMOD 0.00010659753
1,856 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00010319105
2,090 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 9.5668285e-05
2,781 Flow-Loss: Learning Cardinality Estimates That Matter 2021 VLDB 8.1282042e-05
3,269 Learned Cardinality Estimation: An In-depth Study 2022 SIGMOD 7.3026051e-05
3,455 Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation 2022 VLDB 7.0760196e-05
3,658 Towards a Hands-Free Query Optimizer through Deep Learning 2019 CIDR 6.8700949e-05
3,943 Exact Cardinality Query Optimization for Optimizer Testing 2009 VLDB 6.6067351e-05
4,480 Variance Aware Optimization of Parameterized Queries 2010 SIGMOD 6.1433292e-05
5,696 Exact Cardinality Query Optimization with Bounded Execution Cost 2019 SIGMOD 5.367449e-05
6,365 Pre-training Summarization Models of Structured Datasets for Cardinality Estimation 2022 VLDB 5.0892829e-05
6,471 Leveraging Re-costing for Online Optimization of Parameterized Queries with Guarantees 2017 SIGMOD 5.0438582e-05
6,639 Leveraging Query Logs and Machine Learning for Parametric Query Optimization 2022 VLDB 4.976781e-05
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Overall Rank Paper Year Venue Pagerank
7,009 Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective 2024 VLDB 4.8597992e-05
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3,729 Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection 2022 VLDB 6.8078013e-05
7,220 Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation 2023 SIGMOD 4.7926382e-05
10,219 Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking 2026 SIGMOD 4.1905499e-05
10,050 APQO: An Adaptive Framework for Parametric Query Optimization 2026 SIGMOD 4.1905499e-05
10,635 Robust Plan Evaluation based on Approximate Probabilistic Machine Learning 2025 VLDB 4.1905499e-05
10,757 PAR2QO: Parametric Penalty-Aware Robust Query Optimization 2025 VLDB 4.1905499e-05
6,639 Leveraging Query Logs and Machine Learning for Parametric Query Optimization 2022 VLDB 4.976781e-05
10,884 RankPQO: Learning-to-Rank for Parametric Query Optimization 2025 VLDB 4.1905499e-05