| 182 |
LEO - DB2's LEarning Optimizer |
2001 |
VLDB |
0.00036962631 |
| 204 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00034784455 |
| 333 |
Neo: A Learned Query Optimizer |
2019 |
VLDB |
0.00027206884 |
| 608 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00019235898 |
| 629 |
Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors |
2009 |
VLDB |
0.00018942366 |
| 640 |
Bao: Making Learned Query Optimization Practical |
2021 |
SIGMOD |
0.00018759152 |
| 735 |
Umbra: A Disk-Based System with In-Memory Performance |
2020 |
CIDR |
0.00017452467 |
| 806 |
An End-to-End Learning-based Cost Estimator |
2020 |
VLDB |
0.00016434274 |
| 884 |
Plan-Structured Deep Neural Network Models for Query Performance Prediction |
2019 |
VLDB |
0.00015654004 |
| 910 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00015423056 |
| 1,101 |
Generic Database Cost Models for Hierarchical Memory Systems |
2002 |
VLDB |
0.00014070632 |
| 1,512 |
Estimating Progress of Execution for SQL Queries |
2004 |
SIGMOD |
0.00011597041 |
| 1,619 |
Adaptive Optimization of Very Large Join Queries |
2018 |
SIGMOD |
0.00011111678 |
| 1,826 |
Analysis of Two Existing and One New Dynamic Programming Algorithm for the Generation of Optimal Bushy Join Trees without Cross Products |
2006 |
VLDB |
0.00010400425 |
| 2,111 |
When Can We Trust Progress Estimators for SQL Queries? |
2005 |
SIGMOD |
9.5286436e-05 |
| 2,121 |
Balsa: Learning a Query Optimizer Without Expert Demonstrations |
2022 |
SIGMOD |
9.5017232e-05 |
| 2,772 |
Quickstep: A Data Platform Based on the Scaling-Up Approach |
2018 |
VLDB |
8.1401661e-05 |
| 3,169 |
QueryFormer: A Tree Transformer Model for Query Plan Representation |
2022 |
VLDB |
7.4498425e-05 |
| 3,216 |
WiSeDB: A Learning-based Workload Management Advisor for Cloud Databases |
2016 |
VLDB |
7.3601267e-05 |
| 3,348 |
Lero: A Learning-to-Rank Query Optimizer |
2023 |
VLDB |
7.1904529e-05 |
| 3,580 |
Query Performance Prediction for Concurrent Queries using Graph Embedding |
2020 |
VLDB |
6.9500996e-05 |
| 3,625 |
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings |
2020 |
SIGMOD |
6.9055212e-05 |
| 3,725 |
Estimating Cardinalities with Deep Sketches |
2019 |
SIGMOD |
6.8170734e-05 |
| 3,828 |
Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction |
2022 |
VLDB |
6.7208524e-05 |
| 4,088 |
Towards Predicting Query Execution Time for Concurrent and Dynamic Database Workloads |
2013 |
VLDB |
6.4603918e-05 |
| 4,593 |
Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift |
2023 |
SIGMOD |
6.0606891e-05 |
| 5,258 |
One Model to Rule them All: Towards Zero-Shot Learning for Databases |
2022 |
CIDR |
5.5998705e-05 |
| 5,368 |
Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing |
2022 |
VLDB |
5.5457532e-05 |
| 5,401 |
ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads |
2024 |
VLDB |
5.5285035e-05 |
| 5,640 |
AutoSteer: Learned Query Optimization for Any SQL Database |
2023 |
VLDB |
5.3933314e-05 |
| 5,832 |
Stage: Query Execution Time Prediction in Amazon Redshift |
2024 |
SIGMOD |
5.3111109e-05 |
| 6,278 |
Uncertainty Aware Query Execution Time Prediction |
2014 |
VLDB |
5.1309442e-05 |
| 6,519 |
Expand your Training Limits! Generating Training Data for ML-based Data Management |
2021 |
SIGMOD |
5.0316686e-05 |
| 7,008 |
Is Your Learned Query Optimizer Behaving As You Expect? A Machine Learning Perspective |
2024 |
VLDB |
4.8643538e-05 |
| 7,753 |
Rethinking Learned Cost Models: Why Start from Scratch? |
2023 |
SIGMOD |
4.660151e-05 |
| 7,990 |
Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD |
2024 |
VLDB |
4.6117441e-05 |
| 8,578 |
Robust and Budget-Constrained Encoding Configurations for In-Memory Database Systems |
2022 |
VLDB |
4.4923477e-05 |
| 9,892 |
DBMS Fitting: Why should we learn what we already know? |
2020 |
CIDR |
4.261445e-05 |