| 5,091 |
Budget-aware Index Tuning with Reinforcement Learning |
2022 |
SIGMOD |
6.3669569e-05 |
| 5,105 |
SAM: Database Generation from Query Workloads with Supervised Autoregressive Models |
2022 |
SIGMOD |
6.3628539e-05 |
| 5,132 |
Facilitating SQL Query Composition and Analysis |
2020 |
SIGMOD |
6.3534526e-05 |
| 5,137 |
Exact Cardinality Query Optimization with Bounded Execution Cost |
2019 |
SIGMOD |
6.3507372e-05 |
| 5,148 |
LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems |
2022 |
SIGMOD |
6.3465986e-05 |
| 5,171 |
An Efficient Transfer Learning Based Configuration Adviser for Database Tuning |
2024 |
VLDB |
6.3347618e-05 |
| 5,277 |
FASTgres: Making Learned Query Optimizer Hinting Effective |
2023 |
VLDB |
6.2859099e-05 |
| 5,354 |
Can Large Language Models Predict Data Correlations from Column Names? |
2023 |
VLDB |
6.2515841e-05 |
| 5,399 |
Efficient Massively Parallel Join Optimization for Large Queries* |
2022 |
SIGMOD |
6.2319315e-05 |
| 5,461 |
HyperBench: A Benchmark and Tool for Hypergraphs and Empirical Findings |
2019 |
PODS |
6.2090515e-05 |
| 5,529 |
Debunking the Myth of Join Ordering: Toward Robust SQL Analytics |
2025 |
SIGMOD |
6.18591e-05 |
| 5,551 |
PGMJoins: Random Join Sampling with Graphical Models |
2021 |
SIGMOD |
6.1782856e-05 |
| 5,558 |
HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning |
2023 |
VLDB |
6.1749098e-05 |
| 5,573 |
Eraser: Eliminating Performance Regression on Learned Query Optimizer |
2024 |
VLDB |
6.1682747e-05 |
| 5,639 |
LpBound: Pessimistic Cardinality Estimation using ℓp-Norms of Degree Sequences |
2025 |
SIGMOD |
6.1385102e-05 |
| 5,677 |
Making SQL Queries Correct on Incomplete Databases: A Feasibility Study |
2016 |
PODS |
6.1248899e-05 |
| 5,701 |
Lemo: A Cache-Enhanced Learned Optimizer for Concurrent Queries |
2023 |
SIGMOD |
6.1167049e-05 |
| 5,712 |
Sample-Efficient Cardinality Estimation Using Geometric Deep Learning |
2024 |
VLDB |
6.1123894e-05 |
| 5,744 |
SQLStorm: Taking Database Benchmarking into the LLM Era |
2025 |
VLDB |
6.1019672e-05 |
| 5,767 |
A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies |
2024 |
VLDB |
6.0945741e-05 |
| 5,781 |
Free Join: Unifying Worst-Case Optimal and Traditional Joins |
2023 |
SIGMOD |
6.0910397e-05 |
| 5,792 |
Pre-training Summarization Models of Structured Datasets for Cardinality Estimation |
2022 |
VLDB |
6.0871213e-05 |
| 5,947 |
Revisiting Reuse in Main Memory Database Systems |
2017 |
SIGMOD |
6.0323707e-05 |
| 6,009 |
Optimization of Conjunctive Predicates for Main Memory Column Stores |
2016 |
VLDB |
6.0113733e-05 |
| 6,019 |
Robustness Metrics for Relational Query Execution Plans |
2018 |
VLDB |
6.0060149e-05 |
| 6,024 |
Expand your Training Limits! Generating Training Data for ML-based Data Management |
2021 |
SIGMOD |
6.0031118e-05 |
| 6,042 |
Pando: Enhanced Data Skipping with Logical Data Partitioning |
2023 |
VLDB |
5.9970052e-05 |
| 6,088 |
How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks |
2025 |
SIGMOD |
5.9813965e-05 |
| 6,253 |
Declarative Sub-Operators for Universal Data Processing |
2023 |
VLDB |
5.940599e-05 |
| 6,257 |
Join Size Bounds using l_p-Norms on Degree Sequences |
2024 |
PODS |
5.9397944e-05 |
| 6,271 |
Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective |
2024 |
VLDB |
5.9326197e-05 |
| 6,323 |
Modeling Shifting Workloads for Learned Database Systems |
2024 |
SIGMOD |
5.9141228e-05 |
| 6,327 |
Breaking It Down: An In-depth Study of Index Advisors |
2024 |
VLDB |
5.9124005e-05 |
| 6,357 |
A Unified Transferable Model for ML-Enhanced DBMS |
2022 |
CIDR |
5.9020843e-05 |
| 6,434 |
Yannakakis+: Practical Acyclic Query Evaluation with Theoretical Guarantees |
2025 |
SIGMOD |
5.8799421e-05 |
| 6,462 |
PilotScope: Steering Databases with Machine Learning Drivers |
2024 |
VLDB |
5.8717744e-05 |
| 6,543 |
Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation |
2023 |
SIGMOD |
5.8461929e-05 |
| 6,593 |
Simple Adaptive Query Processing vs. Learned Query Optimizers: Observations and Analysis |
2023 |
VLDB |
5.8297039e-05 |
| 6,600 |
A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning |
2023 |
SIGMOD |
5.8250114e-05 |
| 6,684 |
CrocodileDB: Efficient Database Execution through Intelligent Deferment |
2020 |
CIDR |
5.8036476e-05 |
| 6,704 |
ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation |
2024 |
SIGMOD |
5.797374e-05 |
| 6,735 |
Join Order Selection with Deep Reinforcement Learning: Fundamentals, Techniques, and Challenges |
2023 |
VLDB |
5.7878855e-05 |
| 6,760 |
LPLM: A Neural Language Model for Cardinality Estimation of LIKE-Queries |
2024 |
SIGMOD |
5.7826781e-05 |
| 6,997 |
E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model |
2025 |
VLDB |
5.7300324e-05 |
| 7,069 |
SKT: A One-Pass Multi-Sketch Data Analytics Accelerator |
2021 |
VLDB |
5.7117595e-05 |
| 7,076 |
Refactoring Index Tuning Process with Benefit Estimation |
2024 |
VLDB |
5.7098893e-05 |
| 7,112 |
Coresets over Multiple Tables for Feature-rich and Data-efficient Machine Learning |
2023 |
VLDB |
5.6990782e-05 |
| 7,193 |
dbET: Execution Time Distribution-based Plan Selection |
2023 |
SIGMOD |
5.6770249e-05 |
| 7,200 |
Intermittent Query Processing |
2019 |
VLDB |
5.6756294e-05 |
| 7,213 |
Scalable Multi-Query Execution using Reinforcement Learning |
2021 |
SIGMOD |
5.670422e-05 |