| 203 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00034868567 |
| 329 |
Neo: A Learned Query Optimizer |
2019 |
VLDB |
0.00027301488 |
| 606 |
DeepDB: Learn from Data, not from Queries! |
2020 |
VLDB |
0.00019251186 |
| 634 |
Bao: Making Learned Query Optimization Practical |
2021 |
SIGMOD |
0.00018844568 |
| 729 |
Umbra: A Disk-Based System with In-Memory Performance |
2020 |
CIDR |
0.00017448059 |
| 752 |
Deep Unsupervised Cardinality Estimation |
2020 |
VLDB |
0.00017138049 |
| 804 |
An End-to-End Learning-based Cost Estimator |
2020 |
VLDB |
0.0001643674 |
| 905 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00015423174 |
| 1,104 |
Cardinality Estimation Done Right: Index-Based Join Sampling |
2017 |
CIDR |
0.0001398479 |
| 1,161 |
VerdictDB: Universalizing Approximate Query Processing |
2018 |
SIGMOD |
0.00013579831 |
| 1,334 |
Optimizing Subgraph Queries by Combining Binary and Worst-Case Optimal Joins |
2019 |
VLDB |
0.00012543633 |
| 1,621 |
Adaptive Optimization of Very Large Join Queries |
2018 |
SIGMOD |
0.00011105663 |
| 1,631 |
CodexDB: Synthesizing Code for Query Processing from Natural Language Instructions using GPT-3 Codex |
2022 |
VLDB |
0.00011071662 |
| 1,638 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.00011050093 |
| 1,699 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00010848882 |
| 1,856 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00010319105 |
| 1,978 |
Improved Selectivity Estimation by Combining Knowledge from Sampling and Synopses |
2018 |
VLDB |
9.8764627e-05 |
| 2,022 |
Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms |
2020 |
VLDB |
9.7623022e-05 |
| 2,050 |
Automatically Indexing Millions of Databases in Microsoft Azure SQL Database |
2019 |
SIGMOD |
9.6883066e-05 |
| 2,080 |
Towards a Learning Optimizer for Shared Clouds |
2019 |
VLDB |
9.5954034e-05 |
| 2,082 |
Efficient Discovery of Approximate Dependencies |
2018 |
VLDB |
9.5875364e-05 |
| 2,090 |
Balsa: Learning a Query Optimizer Without Expert Demonstrations |
2022 |
SIGMOD |
9.5668285e-05 |
| 2,140 |
Diagnosing Root Causes of Intermittent Slow Queries in Cloud Databases |
2020 |
VLDB |
9.4565836e-05 |
| 2,143 |
Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities |
2019 |
SIGMOD |
9.4437798e-05 |
| 2,154 |
SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning |
2018 |
VLDB |
9.4176683e-05 |
| 2,222 |
SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning |
2019 |
SIGMOD |
9.2598438e-05 |
| 2,242 |
Procedural Extensions of SQL: Understanding their usage in the wild |
2021 |
VLDB |
9.2124242e-05 |
| 2,281 |
Adopting Worst-Case Optimal Joins in Relational Database Systems |
2020 |
VLDB |
9.122455e-05 |
| 2,364 |
Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries |
2020 |
SIGMOD |
8.955077e-05 |
| 2,769 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
8.1512848e-05 |
| 2,781 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
8.1282042e-05 |
| 2,876 |
Computing the Shapley Value of Facts in Query Answering |
2022 |
SIGMOD |
7.9739469e-05 |
| 2,914 |
Quantifying TPC-H Choke Points and Their Optimizations |
2020 |
VLDB |
7.9197583e-05 |
| 2,937 |
DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems |
2021 |
VLDB |
7.8552033e-05 |
| 2,971 |
Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models |
2017 |
VLDB |
7.7935535e-05 |
| 2,988 |
Neural Subgraph Counting with Wasserstein Estimator |
2022 |
SIGMOD |
7.7752463e-05 |
| 3,066 |
Learning a Partitioning Advisor for Cloud Databases |
2020 |
SIGMOD |
7.6255556e-05 |
| 3,167 |
QueryFormer: A Tree Transformer Model for Query Plan Representation |
2022 |
VLDB |
7.4561078e-05 |
| 3,241 |
A Learned Query Rewrite System using Monte Carlo Tree Search |
2022 |
VLDB |
7.32744e-05 |
| 3,269 |
Learned Cardinality Estimation: An In-depth Study |
2022 |
SIGMOD |
7.3026051e-05 |
| 3,270 |
RHEEM: Enabling Cross-Platform Data Processing - May The Big Data Be With You! - |
2018 |
VLDB |
7.3013196e-05 |
| 3,345 |
Lero: A Learning-to-Rank Query Optimizer |
2023 |
VLDB |
7.1908499e-05 |
| 3,455 |
Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation |
2022 |
VLDB |
7.0760196e-05 |
| 3,465 |
LLM-R2: A Large Language Model Enhanced Rule-based Rewrite System for Boosting Query Efficiency |
2025 |
VLDB |
7.0668293e-05 |
| 3,492 |
Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation |
2021 |
VLDB |
7.0435484e-05 |
| 3,516 |
Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs |
2022 |
VLDB |
7.018912e-05 |
| 3,580 |
Query Performance Prediction for Concurrent Queries using Graph Embedding |
2020 |
VLDB |
6.9460425e-05 |
| 3,623 |
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings |
2020 |
SIGMOD |
6.9017341e-05 |
| 3,642 |
BtrBlocks: Efficient Columnar Compression for Data Lakes |
2023 |
SIGMOD |
6.8876984e-05 |
| 3,644 |
G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching |
2020 |
SIGMOD |
6.8842065e-05 |