| 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 |
| 100 |
On the Propagation of Errors in the Size of Join Results |
1991 |
SIGMOD |
0.00050033475 |
| 181 |
LEO - DB2's LEarning Optimizer |
2001 |
VLDB |
0.00036970794 |
| 203 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00034868567 |
| 250 |
Adaptive Selectivity Estimation Using Query Feedback |
1994 |
SIGMOD |
0.00030640525 |
| 512 |
STHoles: A Multidimensional Workload-Aware Histogram |
2001 |
SIGMOD |
0.00021385343 |
| 527 |
Self-tuning Histograms: Building Histograms Without Looking at Data |
1999 |
SIGMOD |
0.00020862475 |
| 550 |
Tracking Join and Self-Join Sizes in Limited Storage |
1999 |
PODS |
0.00020346247 |
| 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 |
| 786 |
Exploiting Statistics on Query Expressions for Optimization |
2002 |
SIGMOD |
0.00016624743 |
| 838 |
Independence is Good: Dependency-Based Histogram Synopses for High-Dimensional Data |
2001 |
SIGMOD |
0.00016024923 |
| 896 |
Selectivity Estimation and Query Optimization in Large Databases with Highly Skewed Distributions of Column Values |
1988 |
VLDB |
0.00015486851 |
| 905 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00015423174 |
| 995 |
Approximating Multi-Dimensional Aggregate Range Queries Over Real Attributes |
2000 |
SIGMOD |
0.00014745185 |
| 1,239 |
Selectivity Estimation for Range Predicates using Lightweight Models |
2019 |
VLDB |
0.00013091459 |
| 1,638 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.00011050093 |
| 1,727 |
QuickSel: Quick Selectivity Learning with Mixture Models |
2020 |
SIGMOD |
0.00010731889 |
| 2,136 |
SASH: A Self-Adaptive Histogram Set for Dynamically Changing Workloads |
2003 |
VLDB |
9.4668797e-05 |
| 2,781 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
8.1282042e-05 |
| 2,937 |
DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems |
2021 |
VLDB |
7.8552033e-05 |
| 3,236 |
TPC-DS, Taking Decision Support Benchmarking to the Next Level |
2002 |
SIGMOD |
7.3294564e-05 |
| 3,924 |
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation |
2021 |
SIGMOD |
6.6227223e-05 |
| 3,955 |
Efficiently Approximating Selectivity Functions using Low Overhead Regression Models |
2020 |
VLDB |
6.5895015e-05 |
| 3,992 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
6.5519369e-05 |
| 4,413 |
Robust Query Driven Cardinality Estimation under Changing Workloads |
2023 |
VLDB |
6.1989918e-05 |
| 5,405 |
ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads |
2024 |
VLDB |
5.5243727e-05 |
| 5,978 |
SafeBound: A Practical System for Generating Cardinality Bounds |
2023 |
SIGMOD |
5.2424396e-05 |
| 7,118 |
ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation |
2024 |
SIGMOD |
4.8204951e-05 |
| 7,442 |
Selectivity Functions of Range Queries are Learnable* |
2022 |
SIGMOD |
4.7248554e-05 |
| 7,564 |
Modeling Shifting Workloads for Learned Database Systems |
2024 |
SIGMOD |
4.7049893e-05 |
| 8,695 |
Convolution and Cross-Correlation of Count Sketches Enables Fast Cardinality Estimation of Multi-Join Queries |
2024 |
SIGMOD |
4.461508e-05 |
| 9,811 |
A Practical Theory of Generalization in Selectivity Learning |
2025 |
VLDB |
4.2742278e-05 |