| 508 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00017108973 |
| 983 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.00012677179 |
| 1,740 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
9.7289523e-05 |
| 1,839 |
DBEst: Revisiting Approximate Query Processing Engines with Machine Learning Models |
2019 |
SIGMOD |
9.5187688e-05 |
| 2,009 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
9.1813272e-05 |
| 2,348 |
Learned Cardinality Estimation: An In-depth Study |
2022 |
SIGMOD |
8.5910072e-05 |
| 2,465 |
Towards Practical Oblivious Join |
2022 |
SIGMOD |
8.4071729e-05 |
| 2,523 |
Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation |
2022 |
VLDB |
8.3316032e-05 |
| 2,635 |
Neural Subgraph Counting with Wasserstein Estimator |
2022 |
SIGMOD |
8.1795762e-05 |
| 2,766 |
Answering (Unions of) Conjunctive Queries using Random Access and Random-Order Enumeration |
2020 |
PODS |
8.0221503e-05 |
| 2,829 |
G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching |
2020 |
SIGMOD |
7.9469964e-05 |
| 2,852 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
7.9201312e-05 |
| 3,060 |
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation |
2021 |
SIGMOD |
7.6828463e-05 |
| 3,105 |
A Learned Sketch for Subgraph Counting |
2021 |
SIGMOD |
7.6278115e-05 |
| 3,502 |
On Join Sampling and the Hardness of Combinatorial Output-Sensitive Join Algorithms |
2023 |
PODS |
7.2308675e-05 |
| 3,740 |
FACE: A Normalizing Flow based Cardinality Estimator |
2022 |
VLDB |
7.0398782e-05 |
| 3,995 |
Simplicity Done Right for Join Ordering |
2021 |
CIDR |
6.8530469e-05 |
| 4,011 |
Guaranteeing the O~(AGM/OUT) Runtime for Uniform Sampling and Size Estimation over Joins |
2023 |
PODS |
6.842581e-05 |
| 4,315 |
ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads |
2024 |
VLDB |
6.6545412e-05 |
| 4,479 |
Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process |
2022 |
SIGMOD |
6.5665703e-05 |
| 4,661 |
Efficient Join Synopsis Maintenance for Data Warehouse |
2020 |
SIGMOD |
6.4656621e-05 |
| 5,153 |
Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach |
2020 |
SIGMOD |
6.2375324e-05 |
| 5,245 |
FASTgres: Making Learned Query Optimizer Hinting Effective |
2023 |
VLDB |
6.1995935e-05 |
| 5,271 |
Cardinality Estimation of Subgraph Matching: A Filtering-Sampling Approach |
2024 |
VLDB |
6.1891764e-05 |
| 5,435 |
Towards Distribution-aware Query Answering in Data Markets |
2022 |
VLDB |
6.1167862e-05 |
| 5,622 |
Responsible Data Integration: Next-generation Challenges |
2022 |
SIGMOD |
6.0460189e-05 |
| 5,671 |
PGMJoins: Random Join Sampling with Graphical Models |
2021 |
SIGMOD |
6.026372e-05 |
| 5,717 |
Combining Sampling and Synopses with Worst-Case Optimal Runtime and Quality Guarantees for Graph Pattern Cardinality Estimation |
2021 |
SIGMOD |
6.0067263e-05 |
| 5,728 |
Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data |
2023 |
SIGMOD |
5.9979958e-05 |
| 5,841 |
Joins on Samples: A Theoretical Guide for Practitioners |
2020 |
VLDB |
5.9569427e-05 |
| 6,198 |
Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing |
2021 |
SIGMOD |
5.8362492e-05 |
| 6,485 |
Cardinality Estimation over Knowledge Graphs with Embeddings and Graph Neural Networks |
2024 |
SIGMOD |
5.7525455e-05 |
| 6,562 |
JoinBoost: Grow Trees Over Normalized Data Using Only SQL |
2023 |
VLDB |
5.7287508e-05 |
| 6,654 |
Coresets over Multiple Tables for Feature-rich and Data-efficient Machine Learning |
2023 |
VLDB |
5.7038474e-05 |
| 6,906 |
LPLM: A Neural Language Model for Cardinality Estimation of LIKE-Queries |
2024 |
SIGMOD |
5.634971e-05 |
| 7,175 |
Learning to Sample: Counting with Complex Queries |
2020 |
VLDB |
5.5779755e-05 |
| 7,267 |
Efficient Dynamic Weighted Set Sampling and Its Extension |
2024 |
VLDB |
5.5539363e-05 |
| 7,490 |
Reservoir Sampling over Joins |
2024 |
SIGMOD |
5.499011e-05 |
| 7,537 |
Computing A Well-Representative Summary of Conjunctive Query Results |
2024 |
PODS |
5.4841462e-05 |
| 7,745 |
PilotDB: Database-Agnostic Online Approximate Query Processing with A Priori Error Guarantees |
2025 |
SIGMOD |
5.4457135e-05 |
| 8,300 |
Subset Sampling over Joins |
2026 |
PODS |
5.3434957e-05 |
| 8,363 |
alpha to omega: The Greek Alphabet of Sampling |
2020 |
CIDR |
5.3305234e-05 |
| 8,685 |
ShadowAQP: Efficient Approximate Group-by and Join Query via Attribute-oriented Sample Size Allocation and Data Generation |
2023 |
VLDB |
5.2730954e-05 |
| 8,790 |
One Size Does Not Fit All: A Bandit-Based Sampler Combination Framework with Theoretical Guarantees |
2022 |
SIGMOD |
5.2633515e-05 |
| 9,176 |
One Seed, Two Birds: A Unified Learned Structure for Exact and Approximate Counting |
2024 |
SIGMOD |
5.200391e-05 |
| 9,669 |
Poisson Sampling over Acyclic Joins |
2026 |
SIGMOD |
5.1275185e-05 |
| 9,684 |
gSWORD: GPU-accelerated Sampling for Subgraph Counting |
2024 |
SIGMOD |
5.1258854e-05 |
| 9,810 |
Color: A Framework for Applying Graph Coloring to Subgraph Cardinality Estimation |
2025 |
VLDB |
5.112328e-05 |
| 9,837 |
NeuSO: Neural Optimizer for Subgraph Queries |
2026 |
SIGMOD |
5.1064323e-05 |
| 10,192 |
Threshold Queries in Theory and in the Wild |
2022 |
VLDB |
5.052396e-05 |