| 1 |
Access Path Selection in a Relational Database Management System |
1979 |
SIGMOD |
0.0040449103 |
| 71 |
How Good Are Query Optimizers, Really? |
2016 |
VLDB |
0.00059038975 |
| 141 |
Selectivity Estimation Without the Attribute Value Independence Assumption |
1997 |
VLDB |
0.00041786333 |
| 182 |
LEO - DB2's LEarning Optimizer |
2001 |
VLDB |
0.00036962631 |
| 204 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00034784455 |
| 372 |
Selectivity Estimation using Probabilistic Models |
2001 |
SIGMOD |
0.00025354779 |
| 512 |
STHoles: A Multidimensional Workload-Aware Histogram |
2001 |
SIGMOD |
0.00021380733 |
| 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 |
| 758 |
Deep Unsupervised Cardinality Estimation |
2020 |
VLDB |
0.0001706608 |
| 806 |
An End-to-End Learning-based Cost Estimator |
2020 |
VLDB |
0.00016434274 |
| 842 |
Independence is Good: Dependency-Based Histogram Synopses for High-Dimensional Data |
2001 |
SIGMOD |
0.00016031973 |
| 910 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00015423056 |
| 943 |
Wander Join: Online Aggregation via Random Walks |
2016 |
SIGMOD |
0.00015145883 |
| 996 |
Approximating Multi-Dimensional Aggregate Range Queries Over Real Attributes |
2000 |
SIGMOD |
0.00014741524 |
| 1,105 |
Cardinality Estimation Done Right: Index-Based Join Sampling |
2017 |
CIDR |
0.00013990395 |
| 1,254 |
Selectivity Estimation for Range Predicates using Lightweight Models |
2019 |
VLDB |
0.00013027411 |
| 1,369 |
Random Sampling over Joins Revisited |
2018 |
SIGMOD |
0.00012339777 |
| 1,547 |
Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions |
2011 |
VLDB |
0.00011442359 |
| 1,703 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00010836769 |
| 2,083 |
Towards a Learning Optimizer for Shared Clouds |
2019 |
VLDB |
9.5834572e-05 |
| 2,142 |
Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities |
2019 |
SIGMOD |
9.4507296e-05 |
| 2,165 |
Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation |
2015 |
SIGMOD |
9.389622e-05 |
| 2,364 |
Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries |
2020 |
SIGMOD |
8.9554751e-05 |
| 2,762 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
8.1585394e-05 |
| 2,783 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
8.1293383e-05 |
| 2,969 |
Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models |
2017 |
VLDB |
7.7974762e-05 |
| 3,646 |
G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching |
2020 |
SIGMOD |
6.8853079e-05 |
| 3,924 |
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation |
2021 |
SIGMOD |
6.6271553e-05 |
| 3,952 |
Exact Cardinality Query Optimization for Optimizer Testing |
2009 |
VLDB |
6.5939652e-05 |
| 4,359 |
Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning |
2021 |
VLDB |
6.2569955e-05 |
| 5,150 |
Efficient Join Synopsis Maintenance for Data Warehouse |
2020 |
SIGMOD |
5.6626586e-05 |
| 5,685 |
Exact Cardinality Query Optimization with Bounded Execution Cost |
2019 |
SIGMOD |
5.3717535e-05 |
| 6,775 |
A Unified Transferable Model for ML-Enhanced DBMS |
2022 |
CIDR |
4.9299192e-05 |
| 8,432 |
SPRINTER: A Fast n-ary Join Query Processing Method for Complex OLAP Queries |
2020 |
SIGMOD |
4.5153924e-05 |