| 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 |
| 141 |
Selectivity Estimation Without the Attribute Value Independence Assumption |
1997 |
VLDB |
0.00041819767 |
| 181 |
LEO - DB2's LEarning Optimizer |
2001 |
VLDB |
0.00036970794 |
| 203 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00034868567 |
| 373 |
Selectivity Estimation using Probabilistic Models |
2001 |
SIGMOD |
0.00025354685 |
| 512 |
STHoles: A Multidimensional Workload-Aware Histogram |
2001 |
SIGMOD |
0.00021385343 |
| 606 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00019251186 |
| 627 |
Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors |
2009 |
VLDB |
0.00018959896 |
| 752 |
Deep Unsupervised Cardinality Estimation |
2020 |
VLDB |
0.00017138049 |
| 804 |
An End-to-End Learning-based Cost Estimator |
2020 |
VLDB |
0.0001643674 |
| 838 |
Independence is Good: Dependency-Based Histogram Synopses for High-Dimensional Data |
2001 |
SIGMOD |
0.00016024923 |
| 905 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00015423174 |
| 941 |
Wander Join: Online Aggregation via Random Walks |
2016 |
SIGMOD |
0.00015147831 |
| 995 |
Approximating Multi-Dimensional Aggregate Range Queries Over Real Attributes |
2000 |
SIGMOD |
0.00014745185 |
| 1,104 |
Cardinality Estimation Done Right: Index-Based Join Sampling |
2017 |
CIDR |
0.0001398479 |
| 1,239 |
Selectivity Estimation for Range Predicates using Lightweight Models |
2019 |
VLDB |
0.00013091459 |
| 1,372 |
Random Sampling over Joins Revisited |
2018 |
SIGMOD |
0.0001233325 |
| 1,536 |
Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions |
2011 |
VLDB |
0.00011458359 |
| 1,699 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00010848882 |
| 2,080 |
Towards a Learning Optimizer for Shared Clouds |
2019 |
VLDB |
9.5954034e-05 |
| 2,143 |
Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities |
2019 |
SIGMOD |
9.4437798e-05 |
| 2,167 |
Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation |
2015 |
SIGMOD |
9.3879598e-05 |
| 2,364 |
Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries |
2020 |
SIGMOD |
8.955077e-05 |
| 2,769 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
8.1512848e-05 |
| 2,781 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
8.1282042e-05 |
| 2,971 |
Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models |
2017 |
VLDB |
7.7935535e-05 |
| 3,644 |
G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching |
2020 |
SIGMOD |
6.8842065e-05 |
| 3,924 |
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation |
2021 |
SIGMOD |
6.6227223e-05 |
| 3,943 |
Exact Cardinality Query Optimization for Optimizer Testing |
2009 |
VLDB |
6.6067351e-05 |
| 4,352 |
Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning |
2021 |
VLDB |
6.2542257e-05 |
| 5,128 |
Efficient Join Synopsis Maintenance for Data Warehouse |
2020 |
SIGMOD |
5.6728511e-05 |
| 5,696 |
Exact Cardinality Query Optimization with Bounded Execution Cost |
2019 |
SIGMOD |
5.367449e-05 |
| 6,774 |
A Unified Transferable Model for ML-Enhanced DBMS |
2022 |
CIDR |
4.9253635e-05 |
| 8,423 |
SPRINTER: A Fast n-ary Join Query Processing Method for Complex OLAP Queries |
2020 |
SIGMOD |
4.5112315e-05 |