| 15 |
How Good Are Query Optimizers, Really? |
2016 |
VLDB |
0.00061463175 |
| 142 |
Neo: A Learned Query Optimizer |
2019 |
VLDB |
0.00029114937 |
| 160 |
CORDS: Automatic Discovery of Correlations and Soft Functional Dependencies |
2004 |
SIGMOD |
0.00027775994 |
| 254 |
The History of Histograms (abridged) |
2003 |
VLDB |
0.00022999992 |
| 355 |
Bao: Making Learned Query Optimization Practical |
2021 |
SIGMOD |
0.00020146245 |
| 405 |
Deep Unsupervised Cardinality Estimation |
2020 |
VLDB |
0.00019020138 |
| 471 |
Robust Query Processing through Progressive Optimization |
2004 |
SIGMOD |
0.00017691682 |
| 508 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00017108973 |
| 545 |
Plan-Structured Deep Neural Network Models for Query Performance Prediction |
2019 |
VLDB |
0.0001657599 |
| 646 |
Exploiting Statistics on Query Expressions for Optimization |
2002 |
SIGMOD |
0.00015166402 |
| 676 |
Robust Estimation of Resource Consumption for SQL Queries using Statistical Techniques |
2012 |
VLDB |
0.00014838681 |
| 689 |
Cardinality Estimation Done Right: Index-Based Join Sampling |
2017 |
CIDR |
0.00014725904 |
| 690 |
Selectivity Estimation for Range Predicates using Lightweight Models |
2019 |
VLDB |
0.00014703258 |
| 775 |
Self-tuning Database Technology and Information Services: from Wishful Thinking to Viable Engineering |
2002 |
VLDB |
0.00014062388 |
| 824 |
Adaptive Ordering of Pipelined Stream Filters |
2004 |
SIGMOD |
0.0001360282 |
| 983 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.00012677179 |
| 996 |
Analyzing Plan Diagrams of Database Query Optimizers |
2005 |
VLDB |
0.00012595827 |
| 1,156 |
QuickSel: Quick Selectivity Learning with Mixture Models |
2020 |
SIGMOD |
0.00011759683 |
| 1,159 |
Toward a Progress Indicator for Database Queries |
2004 |
SIGMOD |
0.00011739527 |
| 1,246 |
Compressing SQL Workloads |
2002 |
SIGMOD |
0.00011355447 |
| 1,261 |
Sampling-Based Query Re-Optimization |
2016 |
SIGMOD |
0.00011289724 |
| 1,282 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00011197535 |
| 1,436 |
Towards a Learning Optimizer for Shared Clouds |
2019 |
VLDB |
0.00010658836 |
| 1,587 |
Estimating Progress of Execution for SQL Queries |
2004 |
SIGMOD |
0.00010119368 |
| 1,604 |
The Picasso Database Query Optimizer Visualizer |
2010 |
VLDB |
0.00010086711 |
| 1,609 |
SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning |
2019 |
SIGMOD |
0.0001007196 |
| 1,670 |
BHUNT: Automatic Discovery of Fuzzy Algebraic Constraints in Relational Data |
2003 |
VLDB |
9.9124313e-05 |
| 1,803 |
SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning |
2018 |
VLDB |
9.5987229e-05 |
| 1,888 |
WeTune: Automatic Discovery and Verification of Query Rewrite Rules |
2022 |
SIGMOD |
9.4148912e-05 |
| 1,935 |
Consistently Estimating the Selectivity of Conjuncts of Predicates |
2005 |
VLDB |
9.3407959e-05 |
| 1,987 |
Plan Bouquets: Query Processing without Selectivity Estimation |
2014 |
SIGMOD |
9.2323722e-05 |
| 2,009 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
9.1813272e-05 |
| 2,154 |
SASH: A Self-Adaptive Histogram Set for Dynamically Changing Workloads |
2003 |
VLDB |
8.9382906e-05 |
| 2,174 |
A Black-Box Approach to Query Cardinality Estimation |
2007 |
CIDR |
8.9067128e-05 |
| 2,228 |
Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models |
2017 |
VLDB |
8.7912743e-05 |
| 2,290 |
Active Learning for ML Enhanced Database Systems |
2020 |
SIGMOD |
8.6813363e-05 |
| 2,305 |
GORDIAN: Efficient and Scalable Discovery of Composite Keys |
2006 |
VLDB |
8.6550507e-05 |
| 2,584 |
Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation |
2021 |
VLDB |
8.2435322e-05 |
| 2,614 |
Statistical Learning Techniques for Costing XML Queries |
2005 |
VLDB |
8.2023561e-05 |
| 2,828 |
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings |
2020 |
SIGMOD |
7.9476509e-05 |
| 2,852 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
7.9201312e-05 |
| 2,888 |
Query Optimizers: Time to Rethink the Contract? |
2009 |
SIGMOD |
7.8895201e-05 |
| 2,971 |
Proving Query Equivalence Using Linear Integer Arithmetic |
2023 |
SIGMOD |
7.7851336e-05 |
| 2,972 |
Scalable and Adaptive Online Joins |
2014 |
VLDB |
7.7844791e-05 |
| 3,001 |
Adapting to Source Properties in Processing Data Integration Queries |
2004 |
SIGMOD |
7.7492907e-05 |
| 3,060 |
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation |
2021 |
SIGMOD |
7.6828463e-05 |
| 3,062 |
Towards a Hands-Free Query Optimizer through Deep Learning |
2019 |
CIDR |
7.6809918e-05 |
| 3,269 |
Robust Query Driven Cardinality Estimation under Changing Workloads |
2023 |
VLDB |
7.463682e-05 |
| 3,271 |
How to Fit when No One Size Fits |
2013 |
CIDR |
7.4609627e-05 |
| 3,361 |
Exact Cardinality Query Optimization for Optimizer Testing |
2009 |
VLDB |
7.3621595e-05 |