| 204 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00034784455 |
| 806 |
An End-to-End Learning-based Cost Estimator |
2020 |
VLDB |
0.00016434274 |
| 1,105 |
Cardinality Estimation Done Right: Index-Based Join Sampling |
2017 |
CIDR |
0.00013990395 |
| 1,369 |
Random Sampling over Joins Revisited |
2018 |
SIGMOD |
0.00012339777 |
| 1,703 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00010836769 |
| 1,855 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00010315245 |
| 2,156 |
SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning |
2018 |
VLDB |
9.4170209e-05 |
| 2,219 |
SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning |
2019 |
SIGMOD |
9.2623533e-05 |
| 3,449 |
Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation |
2022 |
VLDB |
7.0824319e-05 |
| 3,511 |
Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs |
2022 |
VLDB |
7.0254052e-05 |
| 4,571 |
Adaptive Statistics in Oracle 12c |
2017 |
VLDB |
6.0773174e-05 |
| 4,833 |
MNC: Structure-Exploiting Sparsity Estimation for Matrix Expressions |
2019 |
SIGMOD |
5.8916346e-05 |
| 5,337 |
Learned Index Benefits: Machine Learning Based Index Performance Estimation |
2022 |
VLDB |
5.5635208e-05 |
| 5,423 |
Kepler: Robust Learning for Faster Parametric Query Optimization |
2023 |
SIGMOD |
5.5130233e-05 |
| 5,622 |
Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach |
2020 |
SIGMOD |
5.4060403e-05 |
| 5,685 |
Exact Cardinality Query Optimization with Bounded Execution Cost |
2019 |
SIGMOD |
5.3717535e-05 |
| 5,840 |
Logical and Physical Optimizations for SQL Query Execution over Large Language Models |
2025 |
SIGMOD |
5.3042561e-05 |
| 6,493 |
Joins on Samples: A Theoretical Guide for Practitioners |
2020 |
VLDB |
5.0424713e-05 |
| 6,885 |
PilotScope: Steering Databases with Machine Learning Drivers |
2024 |
VLDB |
4.895386e-05 |
| 7,221 |
Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation |
2023 |
SIGMOD |
4.797194e-05 |
| 7,467 |
Yannakakis+: Practical Acyclic Query Evaluation with Theoretical Guarantees |
2025 |
SIGMOD |
4.7218691e-05 |
| 7,776 |
Plan Stitch: Harnessing the Best of Many Plans |
2018 |
VLDB |
4.6537231e-05 |
| 7,854 |
dbET: Execution Time Distribution-based Plan Selection |
2023 |
SIGMOD |
4.6350172e-05 |
| 8,127 |
Robust Query Processing: Mission Possible |
2020 |
VLDB |
4.579056e-05 |
| 8,158 |
MONSOON: Multi-Step Optimization and Execution of Queries with Partially Obscured Predicates |
2020 |
SIGMOD |
4.5730772e-05 |
| 8,164 |
Efficiently Computing Join Orders with Heuristic Search |
2023 |
SIGMOD |
4.5718104e-05 |
| 8,384 |
Consistent and Flexible Selectivity Estimation for High-Dimensional Data |
2021 |
SIGMOD |
4.5304673e-05 |
| 8,775 |
SkinnerMT: Parallelizing for Efficiency and Robustness in Adaptive Query Processing on Multicore Platforms |
2023 |
VLDB |
4.4553047e-05 |
| 9,662 |
Efficient Query Re-optimization with Judicious Subquery Selections |
2023 |
SIGMOD |
4.3097631e-05 |
| 9,693 |
ROME: Robust Query Optimization via Parallel Multi-Plan Execution |
2024 |
SIGMOD |
4.3027391e-05 |
| 9,930 |
Wii: Dynamic Budget Reallocation In Index Tuning |
2024 |
SIGMOD |
4.2510122e-05 |
| 10,125 |
Understanding and Detecting Query Performance Regression in Practical Index Tuning: [Experiments & Analysis] |
2026 |
SIGMOD |
4.1945683e-05 |
| 10,543 |
Esc: An Early-Stopping Checker for Budget-aware Index Tuning |
2025 |
VLDB |
4.1945683e-05 |
| 10,868 |
LEAP: A Low-cost Spark SQL Query Optimizer using Pairwise Comparison |
2025 |
VLDB |
4.1945683e-05 |