| 84 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00035838391 |
| 323 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00021264788 |
| 401 |
Deep Unsupervised Cardinality Estimation |
2020 |
VLDB |
0.00019092557 |
| 465 |
An End-to-End Learning-based Cost Estimator |
2020 |
VLDB |
0.0001803934 |
| 513 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00017190574 |
| 1,061 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00012369764 |
| 1,122 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.0001209124 |
| 1,499 |
Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities |
2019 |
SIGMOD |
0.00010564536 |
| 1,536 |
Improved Selectivity Estimation by Combining Knowledge from Sampling and Synopses |
2018 |
VLDB |
0.00010460864 |
| 1,573 |
Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries |
2020 |
SIGMOD |
0.00010328171 |
| 1,876 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
9.5717543e-05 |
| 1,988 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
9.3501502e-05 |
| 2,203 |
Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models |
2017 |
VLDB |
8.9610447e-05 |
| 2,543 |
Learned Cardinality Estimation: An In-depth Study |
2022 |
SIGMOD |
8.4445934e-05 |
| 2,620 |
Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation |
2021 |
VLDB |
8.3363963e-05 |
| 2,723 |
Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation |
2022 |
VLDB |
8.2049453e-05 |
| 2,991 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
7.8880723e-05 |
| 3,070 |
Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs |
2022 |
VLDB |
7.7900444e-05 |
| 3,086 |
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation |
2021 |
SIGMOD |
7.7708642e-05 |
| 3,162 |
Efficiently Approximating Selectivity Functions using Low Overhead Regression Models |
2020 |
VLDB |
7.6785856e-05 |
| 3,215 |
Every Row Counts: Combining Sketches and Sampling for Accurate Group-By Result Estimates |
2019 |
CIDR |
7.6324234e-05 |
| 3,228 |
Correlation Sketches for Approximate Join-Correlation Queries |
2021 |
SIGMOD |
7.6215176e-05 |
| 3,545 |
Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning |
2021 |
VLDB |
7.3249967e-05 |
| 3,688 |
FACE: A Normalizing Flow based Cardinality Estimator |
2022 |
VLDB |
7.201795e-05 |
| 3,959 |
Simplicity Done Right for Join Ordering |
2021 |
CIDR |
6.9879431e-05 |
| 4,409 |
MNC: Structure-Exploiting Sparsity Estimation for Matrix Expressions |
2019 |
SIGMOD |
6.7178579e-05 |
| 4,800 |
Scalable Reservoir Sampling on Many-Core CPUs |
2019 |
SIGMOD |
6.502434e-05 |
| 4,900 |
COMPASS: Online Sketch-based Query Optimization for In-Memory Databases |
2021 |
SIGMOD |
6.4534715e-05 |
| 5,277 |
FASTgres: Making Learned Query Optimizer Hinting Effective |
2023 |
VLDB |
6.2859099e-05 |
| 5,368 |
Density-optimized Intersection-free Mapping and Matrix Multiplication for Join-Project Operations |
2022 |
VLDB |
6.2448114e-05 |
| 5,743 |
Joins on Samples: A Theoretical Guide for Practitioners |
2020 |
VLDB |
6.1025457e-05 |
| 6,325 |
Combining Sampling and Synopses with Worst-Case Optimal Runtime and Quality Guarantees for Graph Pattern Cardinality Estimation |
2021 |
SIGMOD |
5.9125893e-05 |
| 6,543 |
Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation |
2023 |
SIGMOD |
5.8461929e-05 |
| 6,704 |
ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation |
2024 |
SIGMOD |
5.797374e-05 |
| 7,193 |
dbET: Execution Time Distribution-based Plan Selection |
2023 |
SIGMOD |
5.6770249e-05 |
| 7,503 |
Disclosure-Compliant Query Answering |
2024 |
SIGMOD |
5.6029996e-05 |
| 7,721 |
Identifying Insufficient Data Coverage in Databases with Multiple Relations |
2020 |
VLDB |
5.5587371e-05 |
| 7,829 |
Robust Query Processing: Mission Possible |
2020 |
VLDB |
5.5360082e-05 |
| 7,967 |
Thrifty Query Execution via Incrementability |
2020 |
SIGMOD |
5.5169373e-05 |
| 8,183 |
alpha to omega: The Greek Alphabet of Sampling |
2020 |
CIDR |
5.4714466e-05 |
| 9,455 |
Small Selectivities Matter: Lifting the Burden of Empty Samples |
2021 |
SIGMOD |
5.2653318e-05 |
| 9,756 |
Efficient Query Re-optimization with Judicious Subquery Selections |
2023 |
SIGMOD |
5.2258278e-05 |
| 10,028 |
PRICE: A Pretrained Model for Cross-Database Cardinality Estimation |
2025 |
VLDB |
5.1745962e-05 |
| 10,108 |
An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL |
2025 |
SIGMOD |
5.1347137e-05 |
| 10,206 |
Bridging the Gap: Cardinality Estimation for Semantic Queries on Unstructured Data |
2026 |
SIGMOD |
5.093636e-05 |
| 10,438 |
CorrBound: Cardinality Estimation Accounting for Inter- and Intra-relation Correlations |
2026 |
SIGMOD |
5.093636e-05 |
| 10,486 |
Qualitative Join Discovery in Data Lakes using Examples |
2026 |
SIGMOD |
5.093636e-05 |
| 11,083 |
Graph Transformers for Query Plan Representation: Potentials and Challenges |
2025 |
VLDB |
5.093636e-05 |
| 11,264 |
Agile-Ant: Self-managing Distributed Cache Management for Cost Optimization of Big Data Applications |
2024 |
VLDB |
5.093636e-05 |
| 11,290 |
Presto’s History-based Query Optimizer |
2024 |
VLDB |
5.093636e-05 |