| 320 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00021128745 |
| 355 |
Bao: Making Learned Query Optimization Practical |
2021 |
SIGMOD |
0.00020146245 |
| 411 |
QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning |
2019 |
VLDB |
0.0001874043 |
| 508 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00017108973 |
| 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 |
| 1,583 |
Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries |
2020 |
SIGMOD |
0.00010148362 |
| 1,740 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
9.7289523e-05 |
| 2,169 |
QueryFormer: A Tree Transformer Model for Query Plan Representation |
2022 |
VLDB |
8.9151935e-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 |
| 2,389 |
A Learned Query Rewrite System using Monte Carlo Tree Search |
2022 |
VLDB |
8.5228689e-05 |
| 2,481 |
Learning a Partitioning Advisor for Cloud Databases |
2020 |
SIGMOD |
8.3862675e-05 |
| 2,523 |
Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation |
2022 |
VLDB |
8.3316032e-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 |
| 2,768 |
Query Performance Prediction for Concurrent Queries using Graph Embedding |
2020 |
VLDB |
8.0199086e-05 |
| 2,852 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
7.9201312e-05 |
| 2,913 |
AI Meets Database: AI4DB and DB4AI |
2021 |
SIGMOD |
7.855786e-05 |
| 3,060 |
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation |
2021 |
SIGMOD |
7.6828463e-05 |
| 3,105 |
A Learned Sketch for Subgraph Counting |
2021 |
SIGMOD |
7.6278115e-05 |
| 3,481 |
LOGER: A Learned Optimizer towards Generating Efficient and Robust Query Execution Plans |
2023 |
VLDB |
7.2463722e-05 |
| 3,555 |
Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning |
2021 |
VLDB |
7.1877332e-05 |
| 3,687 |
openGauss: An Autonomous Database System |
2021 |
VLDB |
7.0797286e-05 |
| 3,709 |
Stable Learned Bloom Filters for Data Streams |
2020 |
VLDB |
7.0586477e-05 |
| 3,740 |
FACE: A Normalizing Flow based Cardinality Estimator |
2022 |
VLDB |
7.0398782e-05 |
| 3,959 |
MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems |
2021 |
SIGMOD |
6.8804723e-05 |
| 3,967 |
Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload |
2021 |
SIGMOD |
6.8772718e-05 |
| 4,063 |
The Art of Balance: A RateupDB Experience of Building a CPU/GPU Hybrid Database Product |
2021 |
VLDB |
6.812902e-05 |
| 4,101 |
Towards Dynamic and Safe Configuration Tuning for Cloud Databases |
2022 |
SIGMOD |
6.7930727e-05 |
| 4,247 |
LEON: A New Framework for ML-Aided Query Optimization |
2023 |
VLDB |
6.6920059e-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 |
| 4,703 |
Learned Cardinality Estimation for Similarity Queries |
2021 |
SIGMOD |
6.4458272e-05 |
| 4,720 |
PreQR: Pre-training Representation for SQL Understanding |
2022 |
SIGMOD |
6.4353798e-05 |
| 4,726 |
Learned Index Benefits: Machine Learning Based Index Performance Estimation |
2022 |
VLDB |
6.4329878e-05 |
| 4,765 |
Machine Learning for Databases |
2021 |
VLDB |
6.4166895e-05 |
| 4,792 |
Learned Approximate Query Processing: Make it Light, Accurate and Fast |
2021 |
CIDR |
6.4010108e-05 |
| 4,833 |
Stage: Query Execution Time Prediction in Amazon Redshift |
2024 |
SIGMOD |
6.3834856e-05 |
| 5,043 |
Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing |
2022 |
VLDB |
6.28918e-05 |
| 5,153 |
Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach |
2020 |
SIGMOD |
6.2375324e-05 |
| 5,211 |
Database Workload Characterization with Query Plan Encoders |
2022 |
VLDB |
6.2141929e-05 |
| 5,245 |
FASTgres: Making Learned Query Optimizer Hinting Effective |
2023 |
VLDB |
6.1995935e-05 |
| 5,453 |
Eraser: Eliminating Performance Regression on Learned Query Optimizer |
2024 |
VLDB |
6.1077838e-05 |
| 5,457 |
Sample-Efficient Cardinality Estimation Using Geometric Deep Learning |
2024 |
VLDB |
6.1058928e-05 |
| 5,484 |
A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies |
2024 |
VLDB |
6.0980944e-05 |
| 5,854 |
Modeling Shifting Workloads for Learned Database Systems |
2024 |
SIGMOD |
5.9520525e-05 |