| 257 |
Making Database Systems Usable |
2007 |
SIGMOD |
0.00030223397 |
| 514 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.0002124895 |
| 757 |
Database Architecture Evolution: Mammals Flourished long before Dinosaurs became Extinct |
2009 |
VLDB |
0.00017078358 |
| 1,017 |
Automatic Physical Database Tuning: A Relaxation-based Approach |
2005 |
SIGMOD |
0.00014634307 |
| 1,343 |
NoDB: Efficient Query Execution on Raw Data Files |
2012 |
SIGMOD |
0.00012482538 |
| 1,534 |
PerfXplain: Debugging MapReduce Job Performance |
2012 |
VLDB |
0.00011468393 |
| 1,762 |
Tuning Schema Matching Software using Synthetic Scenarios |
2005 |
VLDB |
0.00010646894 |
| 1,855 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00010315245 |
| 2,020 |
Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms |
2020 |
VLDB |
9.762624e-05 |
| 2,047 |
Automatically Indexing Millions of Databases in Microsoft Azure SQL Database |
2019 |
SIGMOD |
9.6920209e-05 |
| 2,205 |
ReStore: Reusing Results of MapReduce Jobs |
2012 |
VLDB |
9.2920002e-05 |
| 2,229 |
Self-organizing Tuple Reconstruction in Column-stores |
2009 |
SIGMOD |
9.2350274e-05 |
| 2,367 |
Here are my Data Files. Here are my Queries. Where are my Results? |
2011 |
CIDR |
8.9511058e-05 |
| 2,787 |
To Tune or not to Tune? A Lightweight Physical Design Alerter |
2006 |
VLDB |
8.1263608e-05 |
| 2,828 |
Automatic Physical Design Tuning: Workload as a Sequence |
2006 |
SIGMOD |
8.0548516e-05 |
| 3,072 |
Constrained Physical Design Tuning |
2008 |
VLDB |
7.6114086e-05 |
| 3,076 |
Learning a Partitioning Advisor for Cloud Databases |
2020 |
SIGMOD |
7.6107677e-05 |
| 3,142 |
Active Learning for ML Enhanced Database Systems |
2020 |
SIGMOD |
7.4815444e-05 |
| 3,284 |
Configuration-Parametric Query Optimization for Physical Design Tuning |
2008 |
SIGMOD |
7.2790444e-05 |
| 3,348 |
Lero: A Learning-to-Rank Query Optimizer |
2023 |
VLDB |
7.1904529e-05 |
| 3,370 |
Storage Workload Estimation for Database Management Systems |
2007 |
SIGMOD |
7.1704153e-05 |
| 3,488 |
Optimal Column Layout for Hybrid Workloads |
2019 |
VLDB |
7.0479329e-05 |
| 3,653 |
Database Tuning Advisor for Microsoft SQL Server 2005: Demo |
2005 |
SIGMOD |
6.8743355e-05 |
| 3,812 |
Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation |
2022 |
VLDB |
6.7373184e-05 |
| 3,891 |
Slalom: Coasting Through Raw Data via Adaptive Partitioning and Indexing |
2017 |
VLDB |
6.659442e-05 |
| 3,896 |
Updating a Cracked Database |
2007 |
SIGMOD |
6.6575888e-05 |
| 3,922 |
Pushing Data-Induced Predicates Through Joins in Big-Data Clusters |
2020 |
VLDB |
6.6291079e-05 |
| 3,952 |
Exact Cardinality Query Optimization for Optimizer Testing |
2009 |
VLDB |
6.5939652e-05 |
| 4,108 |
Cracking the Database Store |
2005 |
CIDR |
6.4440088e-05 |
| 4,468 |
Comprehensive and Efficient Workload Compression |
2021 |
VLDB |
6.1584035e-05 |
| 4,506 |
Stochastic Database Cracking: Towards Robust Adaptive Indexing in Main-Memory Column-Stores |
2012 |
VLDB |
6.1319277e-05 |
| 4,623 |
Automated Generation of Materialized Views in Oracle |
2020 |
VLDB |
6.0411909e-05 |
| 4,690 |
Deploying a Steered Query Optimizer in Production at Microsoft |
2022 |
SIGMOD |
5.997226e-05 |
| 5,105 |
Only Aggressive Elephants are Fast Elephants |
2012 |
VLDB |
5.694494e-05 |
| 5,109 |
Adaptive NUMA-aware data placement and task scheduling for analytical workloads in main-memory column-stores |
2017 |
VLDB |
5.6908086e-05 |
| 5,113 |
Columnstore and B+ tree – Are Hybrid Physical Designs Important? |
2018 |
SIGMOD |
5.687445e-05 |
| 5,376 |
Holistic Indexing in Main-memory Column-stores |
2015 |
SIGMOD |
5.5417421e-05 |
| 5,918 |
Breaking Down Memory Walls: Adaptive Memory Management in LSM-based Storage Systems |
2021 |
VLDB |
5.2737135e-05 |
| 6,151 |
An Efficient Transfer Learning Based Configuration Adviser for Database Tuning |
2024 |
VLDB |
5.183652e-05 |
| 6,157 |
Compression Aware Physical Database Design |
2011 |
VLDB |
5.1801143e-05 |
| 6,345 |
Operator and Query Progress Estimation in Microsoft SQL Server Live Query Statistics |
2016 |
SIGMOD |
5.1023048e-05 |
| 6,366 |
ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning |
2022 |
SIGMOD |
5.0943443e-05 |
| 6,398 |
Endure: A Robust Tuning Paradigm for LSM Trees Under Workload Uncertainty |
2022 |
VLDB |
5.0819209e-05 |
| 6,484 |
A Statistical Approach Towards Robust Progress Estimation |
2012 |
VLDB |
5.0453762e-05 |
| 7,127 |
Guided automated learning for query workload re-optimization |
2019 |
VLDB |
4.8230386e-05 |
| 7,218 |
Breaking Down Memory Walls in LSM-based Storage Systems |
2020 |
SIGMOD |
4.7982543e-05 |
| 7,445 |
An Automated, Yet Interactive and Portable DB Designer |
2010 |
SIGMOD |
4.7278675e-05 |
| 8,020 |
The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions |
2024 |
VLDB |
4.6040862e-05 |
| 8,041 |
DISTILL: Low-Overhead Data-Driven Techniques for Filtering and Costing Indexes for Scalable Index Tuning |
2022 |
VLDB |
4.5998045e-05 |
| 8,103 |
Grep: A Graph Learning Based Database Partitioning System |
2023 |
SIGMOD |
4.5852201e-05 |