| 1 |
Access Path Selection in a Relational Database Management System |
1979 |
SIGMOD |
0.0040465394 |
| 71 |
How Good Are Query Optimizers, Really? |
2016 |
VLDB |
0.00059446482 |
| 167 |
The Snowflake Elastic Data Warehouse |
2016 |
SIGMOD |
0.00039408116 |
| 183 |
Automatic Database Management System Tuning Through Large-scale Machine Learning |
2017 |
SIGMOD |
0.00036859633 |
| 203 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00034868567 |
| 310 |
The Vertica Analytic Database: C-Store 7 Years Later |
2012 |
VLDB |
0.0002815547 |
| 380 |
Towards Estimation Error Guarantees for Distinct Values |
2000 |
PODS |
0.00024943236 |
| 486 |
TiDB: A Raft-based HTAP Database |
2020 |
VLDB |
0.00022039625 |
| 510 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.00021420477 |
| 606 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00019251186 |
| 752 |
Deep Unsupervised Cardinality Estimation |
2020 |
VLDB |
0.00017138049 |
| 804 |
An End-to-End Learning-based Cost Estimator |
2020 |
VLDB |
0.0001643674 |
| 905 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00015423174 |
| 950 |
Runtime Measurements in the Cloud: Observing, Analyzing, and Reducing Variance |
2010 |
VLDB |
0.00015100872 |
| 1,239 |
Selectivity Estimation for Range Predicates using Lightweight Models |
2019 |
VLDB |
0.00013091459 |
| 1,273 |
Amazon Redshift Re-invented |
2022 |
SIGMOD |
0.00012870386 |
| 1,313 |
Cost-Based Optimization for Magic: Algebra and Implementation |
1996 |
SIGMOD |
0.00012629432 |
| 1,590 |
Column-oriented Database Systems |
2009 |
VLDB |
0.00011230525 |
| 1,638 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.00011050093 |
| 2,769 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
8.1512848e-05 |
| 3,153 |
AnalyticDB: Real-time OLAP Database System at Alibaba Cloud |
2019 |
VLDB |
7.4706916e-05 |
| 3,455 |
Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation |
2022 |
VLDB |
7.0760196e-05 |
| 3,492 |
Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation |
2021 |
VLDB |
7.0435484e-05 |
| 3,623 |
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings |
2020 |
SIGMOD |
6.9017341e-05 |
| 3,797 |
Constructing and Analyzing the LSM Compaction Design Space |
2021 |
VLDB |
6.7552936e-05 |
| 3,819 |
Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction |
2022 |
VLDB |
6.7267885e-05 |
| 3,992 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
6.5519369e-05 |
| 3,995 |
ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases |
2021 |
SIGMOD |
6.5475871e-05 |
| 4,151 |
openGauss: An Autonomous Database System |
2021 |
VLDB |
6.4020605e-05 |
| 4,413 |
Robust Query Driven Cardinality Estimation under Changing Workloads |
2023 |
VLDB |
6.1989918e-05 |
| 4,543 |
FACE: A Normalizing Flow based Cardinality Estimator |
2022 |
VLDB |
6.0953507e-05 |
| 4,592 |
Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift |
2023 |
SIGMOD |
6.056004e-05 |
| 5,250 |
One Model to Rule them All: Towards Zero-Shot Learning for Databases |
2022 |
CIDR |
5.6007779e-05 |
| 5,537 |
Presto: A Decade of SQL Analytics at Meta |
2023 |
SIGMOD |
5.453017e-05 |
| 5,639 |
Analyzing the Impact of Cardinality Estimation on Execution Plans in Microsoft SQL Server |
2023 |
VLDB |
5.3972261e-05 |
| 6,774 |
A Unified Transferable Model for ML-Enhanced DBMS |
2022 |
CIDR |
4.9253635e-05 |
| 7,611 |
Learning to be a Statistician: Learned Estimator for Number of Distinct Values |
2022 |
VLDB |
4.6920008e-05 |
| 8,434 |
SageDB: An Instance-Optimized Data Analytics System |
2022 |
VLDB |
4.5077955e-05 |