| 85 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00035876108 |
| 144 |
Neo: A Learned Query Optimizer |
2019 |
VLDB |
0.00029090793 |
| 318 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00021166957 |
| 361 |
Bao: Making Learned Query Optimization Practical |
2021 |
SIGMOD |
0.00020000855 |
| 373 |
Umbra: A Disk-Based System with In-Memory Performance |
2020 |
CIDR |
0.00019705706 |
| 406 |
Deep Unsupervised Cardinality Estimation |
2020 |
VLDB |
0.00019050182 |
| 462 |
An End-to-End Learning-based Cost Estimator |
2020 |
VLDB |
0.00017836105 |
| 510 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00017059914 |
| 688 |
Cardinality Estimation Done Right: Index-Based Join Sampling |
2017 |
CIDR |
0.00014749318 |
| 713 |
Optimizing Subgraph Queries by Combining Binary and Worst-Case Optimal Joins |
2019 |
VLDB |
0.00014571507 |
| 772 |
VerdictDB: Universalizing Approximate Query Processing |
2018 |
SIGMOD |
0.0001409096 |
| 981 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.00012713454 |
| 1,065 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00012202293 |
| 1,185 |
Adaptive Optimization of Very Large Join Queries |
2018 |
SIGMOD |
0.00011607329 |
| 1,195 |
Balsa: Learning a Query Optimizer Without Expert Demonstrations |
2022 |
SIGMOD |
0.00011574218 |
| 1,280 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00011224914 |
| 1,396 |
Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms |
2020 |
VLDB |
0.00010788714 |
| 1,432 |
Towards a Learning Optimizer for Shared Clouds |
2019 |
VLDB |
0.00010676754 |
| 1,465 |
Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities |
2019 |
SIGMOD |
0.00010572023 |
| 1,488 |
Efficient Discovery of Approximate Dependencies |
2018 |
VLDB |
0.00010513265 |
| 1,515 |
DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems |
2021 |
VLDB |
0.00010418766 |
| 1,516 |
Automatically Indexing Millions of Databases in Microsoft Azure SQL Database |
2019 |
SIGMOD |
0.00010398346 |
| 1,543 |
Improved Selectivity Estimation by Combining Knowledge from Sampling and Synopses |
2018 |
VLDB |
0.00010305662 |
| 1,580 |
Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries |
2020 |
SIGMOD |
0.00010177136 |
| 1,596 |
Adopting Worst-Case Optimal Joins in Relational Database Systems |
2020 |
VLDB |
0.00010122962 |
| 1,605 |
SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning |
2019 |
SIGMOD |
0.00010095581 |
| 1,735 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
9.7566604e-05 |
| 1,786 |
Procedural Extensions of SQL: Understanding their usage in the wild |
2021 |
VLDB |
9.6281276e-05 |
| 1,800 |
SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning |
2018 |
VLDB |
9.6082185e-05 |
| 1,849 |
Diagnosing Root Causes of Intermittent Slow Queries in Cloud Databases |
2020 |
VLDB |
9.5032324e-05 |
| 1,949 |
Quantifying TPC-H Choke Points and Their Optimizations |
2020 |
VLDB |
9.3172855e-05 |
| 1,975 |
CodexDB: Synthesizing Code for Query Processing from Natural Language Instructions using GPT-3 Codex |
2022 |
VLDB |
9.2801545e-05 |
| 2,002 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
9.2076835e-05 |
| 2,037 |
LLM-R^2: A Large Language Model Enhanced Rule-based Rewrite System for Boosting Query Efficiency |
2025 |
VLDB |
9.1494269e-05 |
| 2,209 |
Lero: A Learning-to-Rank Query Optimizer |
2023 |
VLDB |
8.8360101e-05 |
| 2,217 |
Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models |
2017 |
VLDB |
8.8151982e-05 |
| 2,218 |
Computing the Shapley Value of Facts in Query Answering |
2022 |
SIGMOD |
8.8130445e-05 |
| 2,248 |
QueryFormer: A Tree Transformer Model for Query Plan Representation |
2022 |
VLDB |
8.7567205e-05 |
| 2,317 |
BtrBlocks: Efficient Columnar Compression for Data Lakes |
2023 |
SIGMOD |
8.6492924e-05 |
| 2,342 |
Learned Cardinality Estimation: An In-depth Study |
2022 |
SIGMOD |
8.6074783e-05 |
| 2,393 |
A Learned Query Rewrite System using Monte Carlo Tree Search |
2022 |
VLDB |
8.5298464e-05 |
| 2,476 |
Learning a Partitioning Advisor for Cloud Databases |
2020 |
SIGMOD |
8.407183e-05 |
| 2,518 |
Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation |
2022 |
VLDB |
8.3532841e-05 |
| 2,583 |
Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation |
2021 |
VLDB |
8.2589842e-05 |
| 2,635 |
Neural Subgraph Counting with Wasserstein Estimator |
2022 |
SIGMOD |
8.1954989e-05 |
| 2,686 |
Cost-based or Learning-based? A Hybrid Query Optimizer for Query Plan Selection |
2022 |
VLDB |
8.1300913e-05 |
| 2,770 |
Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation |
2022 |
VLDB |
8.0343719e-05 |
| 2,818 |
To Partition, or Not to Partition, That is the Join Question in a Real System |
2021 |
SIGMOD |
7.9703078e-05 |
| 2,824 |
G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching |
2020 |
SIGMOD |
7.9662478e-05 |
| 2,833 |
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings |
2020 |
SIGMOD |
7.9539771e-05 |