| 355 |
Bao: Making Learned Query Optimization Practical |
2021 |
SIGMOD |
0.00020146245 |
| 983 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.00012677179 |
| 1,064 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00012181459 |
| 1,175 |
Balsa: Learning a Query Optimizer Without Expert Demonstrations |
2022 |
SIGMOD |
0.00011630532 |
| 1,513 |
DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems |
2021 |
VLDB |
0.00010394557 |
| 1,740 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
9.7289523e-05 |
| 2,009 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
9.1813272e-05 |
| 2,190 |
Lero: A Learning-to-Rank Query Optimizer |
2023 |
VLDB |
8.8848923e-05 |
| 2,348 |
Learned Cardinality Estimation: An In-depth Study |
2022 |
SIGMOD |
8.5910072e-05 |
| 2,523 |
Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation |
2022 |
VLDB |
8.3316032e-05 |
| 2,584 |
Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation |
2021 |
VLDB |
8.2435322e-05 |
| 2,619 |
Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction |
2022 |
VLDB |
8.1985665e-05 |
| 2,635 |
Neural Subgraph Counting with Wasserstein Estimator |
2022 |
SIGMOD |
8.1795762e-05 |
| 2,696 |
Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection |
2022 |
VLDB |
8.1068354e-05 |
| 2,772 |
Instance-Optimized Data Layouts for Cloud Analytics Workloads |
2021 |
SIGMOD |
8.0148928e-05 |
| 2,852 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
7.9201312e-05 |
| 3,060 |
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation |
2021 |
SIGMOD |
7.6828463e-05 |
| 3,269 |
Robust Query Driven Cardinality Estimation under Changing Workloads |
2023 |
VLDB |
7.463682e-05 |
| 3,687 |
openGauss: An Autonomous Database System |
2021 |
VLDB |
7.0797286e-05 |
| 3,740 |
FACE: A Normalizing Flow based Cardinality Estimator |
2022 |
VLDB |
7.0398782e-05 |
| 4,101 |
Towards Dynamic and Safe Configuration Tuning for Cloud Databases |
2022 |
SIGMOD |
6.7930727e-05 |
| 4,202 |
Kepler: Robust Learning for Faster Parametric Query Optimization |
2023 |
SIGMOD |
6.7258607e-05 |
| 4,247 |
LEON: A New Framework for ML-Aided Query Optimization |
2023 |
VLDB |
6.6920059e-05 |
| 4,315 |
ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads |
2024 |
VLDB |
6.6545412e-05 |
| 4,479 |
Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process |
2022 |
SIGMOD |
6.5665703e-05 |
| 4,549 |
One Model to Rule them All: Towards Zero-Shot Learning for Databases |
2022 |
CIDR |
6.5328866e-05 |
| 4,641 |
How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks |
2025 |
SIGMOD |
6.4739208e-05 |
| 4,683 |
AutoSteer: Learned Query Optimization for Any SQL Database |
2023 |
VLDB |
6.4545989e-05 |
| 4,720 |
PreQR: Pre-training Representation for SQL Understanding |
2022 |
SIGMOD |
6.4353798e-05 |
| 4,833 |
Stage: Query Execution Time Prediction in Amazon Redshift |
2024 |
SIGMOD |
6.3834856e-05 |
| 4,882 |
LpBound: Pessimistic Cardinality Estimation using ℓp-Norms of Degree Sequences |
2025 |
SIGMOD |
6.3565046e-05 |
| 4,971 |
Debunking the Myth of Join Ordering: Toward Robust SQL Analytics |
2025 |
SIGMOD |
6.3209003e-05 |
| 5,043 |
Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing |
2022 |
VLDB |
6.28918e-05 |
| 5,075 |
SafeBound: A Practical System for Generating Cardinality Bounds |
2023 |
SIGMOD |
6.2721634e-05 |
| 5,126 |
Steering Query Optimizers: A Practical Take on Big Data Workloads |
2021 |
SIGMOD |
6.2493606e-05 |
| 5,237 |
SAM: Database Generation from Query Workloads with Supervised Autoregressive Models |
2022 |
SIGMOD |
6.2027113e-05 |
| 5,457 |
Sample-Efficient Cardinality Estimation Using Geometric Deep Learning |
2024 |
VLDB |
6.1058928e-05 |
| 5,671 |
PGMJoins: Random Join Sampling with Graphical Models |
2021 |
SIGMOD |
6.026372e-05 |
| 5,713 |
PilotScope: Steering Databases with Machine Learning Drivers |
2024 |
VLDB |
6.0090633e-05 |
| 5,728 |
Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data |
2023 |
SIGMOD |
5.9979958e-05 |
| 5,837 |
Pre-training Summarization Models of Structured Datasets for Cardinality Estimation |
2022 |
VLDB |
5.9600736e-05 |
| 5,854 |
Modeling Shifting Workloads for Learned Database Systems |
2024 |
SIGMOD |
5.9520525e-05 |
| 5,982 |
Towards instance-optimized data systems |
2021 |
VLDB |
5.9096991e-05 |
| 6,109 |
Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective |
2024 |
VLDB |
5.8676956e-05 |
| 6,402 |
A Unified Transferable Model for ML-Enhanced DBMS |
2022 |
CIDR |
5.7800842e-05 |
| 6,654 |
Coresets over Multiple Tables for Feature-rich and Data-efficient Machine Learning |
2023 |
VLDB |
5.7038474e-05 |
| 6,672 |
Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation |
2023 |
SIGMOD |
5.6975871e-05 |
| 6,812 |
dbET: Execution Time Distribution-based Plan Selection |
2023 |
SIGMOD |
5.6597129e-05 |
| 6,840 |
ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation |
2024 |
SIGMOD |
5.6513231e-05 |
| 7,238 |
Refactoring Index Tuning Process with Benefit Estimation |
2024 |
VLDB |
5.5624225e-05 |