| 982 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.00012714044 |
| 1,064 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00012202282 |
| 1,156 |
QuickSel: Quick Selectivity Learning with Mixture Models |
2020 |
SIGMOD |
0.00011777105 |
| 1,734 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
9.7545773e-05 |
| 2,583 |
Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation |
2021 |
VLDB |
8.2589758e-05 |
| 2,634 |
Neural Subgraph Counting with Wasserstein Estimator |
2022 |
SIGMOD |
8.1993804e-05 |
| 2,824 |
G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching |
2020 |
SIGMOD |
7.9698957e-05 |
| 2,846 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
7.9453616e-05 |
| 2,974 |
Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs |
2022 |
VLDB |
7.7938744e-05 |
| 3,052 |
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation |
2021 |
SIGMOD |
7.7052471e-05 |
| 3,160 |
A Learned Sketch for Subgraph Counting |
2021 |
SIGMOD |
7.5807496e-05 |
| 3,327 |
Robust Query Driven Cardinality Estimation under Changing Workloads |
2023 |
VLDB |
7.4207879e-05 |
| 3,982 |
Simplicity Done Right for Join Ordering |
2021 |
CIDR |
6.8750228e-05 |
| 4,457 |
Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process |
2022 |
SIGMOD |
6.5913732e-05 |
| 4,852 |
LpBound: Pessimistic Cardinality Estimation using ℓp-Norms of Degree Sequences |
2025 |
SIGMOD |
6.3806134e-05 |
| 5,003 |
COMPASS: Online Sketch-based Query Optimization for In-Memory Databases |
2021 |
SIGMOD |
6.3188773e-05 |
| 5,126 |
Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach |
2020 |
SIGMOD |
6.261175e-05 |
| 5,219 |
SafeBound: A Practical System for Generating Cardinality Bounds |
2023 |
SIGMOD |
6.222726e-05 |
| 5,241 |
FASTgres: Making Learned Query Optimizer Hinting Effective |
2023 |
VLDB |
6.2154384e-05 |
| 5,496 |
Density-optimized Intersection-free Mapping and Matrix Multiplication for Join-Project Operations |
2022 |
VLDB |
6.1049663e-05 |
| 5,901 |
Combining Sampling and Synopses with Worst-Case Optimal Runtime and Quality Guarantees for Graph Pattern Cardinality Estimation |
2021 |
SIGMOD |
5.9539374e-05 |
| 5,902 |
Yannakakis+: Practical Acyclic Query Evaluation with Theoretical Guarantees |
2025 |
SIGMOD |
5.9536872e-05 |
| 5,918 |
Join Size Bounds using l_p-Norms on Degree Sequences |
2024 |
PODS |
5.9481539e-05 |
| 6,791 |
dbET: Execution Time Distribution-based Plan Selection |
2023 |
SIGMOD |
5.6811782e-05 |
| 6,818 |
ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation |
2024 |
SIGMOD |
5.672718e-05 |
| 7,566 |
Convolution and Cross-Correlation of Count Sketches Enables Fast Cardinality Estimation of Multi-Join Queries |
2024 |
SIGMOD |
5.4952834e-05 |
| 7,647 |
Disclosure-Compliant Query Answering |
2024 |
SIGMOD |
5.4772833e-05 |
| 8,035 |
JoinSketch: A Sketch Algorithm for Accurate and Unbiased Inner-Product Estimation |
2023 |
SIGMOD |
5.4025473e-05 |
| 8,131 |
Thrifty Query Execution via Incrementability |
2020 |
SIGMOD |
5.3936608e-05 |
| 8,164 |
Efficient Query Re-optimization with Judicious Subquery Selections |
2023 |
SIGMOD |
5.3852872e-05 |
| 8,477 |
TreeSensing: Linearly Compressing Sketches with Flexibility |
2023 |
SIGMOD |
5.3332727e-05 |
| 8,650 |
PostCENN: PostgreSQL with Machine Learning Models for Cardinality Estimation |
2021 |
VLDB |
5.2948655e-05 |
| 8,682 |
Galley: Modern Query Optimization for Sparse Tensor Programs |
2025 |
SIGMOD |
5.2905577e-05 |
| 9,478 |
LpBound in Action: Cardinality Estimation with One-Sided Guarantees |
2025 |
SIGMOD |
5.1708619e-05 |
| 9,950 |
HoneyComb: A Parallel Worst-Case Optimal Join on Multicores |
2025 |
SIGMOD |
5.1038322e-05 |
| 9,976 |
Selectivity Estimation for Queries Containing Predicates over Set-Valued Attributes |
2023 |
SIGMOD |
5.1031384e-05 |
| 10,182 |
Efficient Algorithms for Cardinality Estimation and Conjunctive Query Evaluation With Simple Degree Constraints |
2025 |
PODS |
5.0651993e-05 |
| 10,184 |
Path-centric Cardinality Estimation for Subgraph Matching |
2025 |
VLDB |
5.0651993e-05 |
| 10,205 |
Turbo-Charging SPJ Query Plans with Learned Physical Join Operator Selections |
2022 |
VLDB |
5.0603873e-05 |
| 10,215 |
Color: A Framework for Applying Graph Coloring to Subgraph Cardinality Estimation |
2025 |
VLDB |
5.0584922e-05 |
| 10,336 |
An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL |
2025 |
SIGMOD |
5.0200193e-05 |
| 10,365 |
Size Bound-Adorned Datalog |
2026 |
PODS |
4.9793485e-05 |
| 10,508 |
Succinct Structure Representations for Efficient Query Optimization |
2026 |
SIGMOD |
4.9793485e-05 |
| 10,627 |
CorrBound: Cardinality Estimation Accounting for Inter- and Intra-relation Correlations |
2026 |
SIGMOD |
4.9793485e-05 |
| 10,900 |
ANNiE: A Learned Query Cost Estimator for Graph-Based Approximate Nearest Neighbor Search |
2026 |
VLDB |
4.9793485e-05 |
| 11,286 |
Efficient and Accurate Subgraph Counting: A Bottom-up Flow-learning Based Approach |
2025 |
VLDB |
4.9793485e-05 |
| 11,507 |
Sub-optimal Join Order Identification with L1-error |
2024 |
SIGMOD |
4.9793485e-05 |
| 11,536 |
Enabling Adaptive Sampling for Intra-Window Join: Simultaneously Optimizing Quantity and Quality |
2024 |
SIGMOD |
4.9793485e-05 |