| 257 |
Making Database Systems Usable |
2007 |
SIGMOD |
0.00030237174 |
| 510 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.00021420477 |
| 754 |
Database Architecture Evolution: Mammals Flourished long before Dinosaurs became Extinct |
2009 |
VLDB |
0.00017093267 |
| 1,018 |
Automatic Physical Database Tuning: A Relaxation-based Approach |
2005 |
SIGMOD |
0.00014626746 |
| 1,346 |
NoDB: Efficient Query Execution on Raw Data Files |
2012 |
SIGMOD |
0.00012472598 |
| 1,533 |
PerfXplain: Debugging MapReduce Job Performance |
2012 |
VLDB |
0.00011462982 |
| 1,761 |
Tuning Schema Matching Software using Synthetic Scenarios |
2005 |
VLDB |
0.00010637364 |
| 1,856 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00010319105 |
| 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 |
| 2,211 |
ReStore: Reusing Results of MapReduce Jobs |
2012 |
VLDB |
9.2823037e-05 |
| 2,231 |
Self-organizing Tuple Reconstruction in Column-stores |
2009 |
SIGMOD |
9.2367968e-05 |
| 2,367 |
Here are my Data Files. Here are my Queries. Where are my Results? |
2011 |
CIDR |
8.9502761e-05 |
| 2,788 |
To Tune or not to Tune? A Lightweight Physical Design Alerter |
2006 |
VLDB |
8.121027e-05 |
| 2,834 |
Automatic Physical Design Tuning: Workload as a Sequence |
2006 |
SIGMOD |
8.0468556e-05 |
| 3,066 |
Learning a Partitioning Advisor for Cloud Databases |
2020 |
SIGMOD |
7.6255556e-05 |
| 3,077 |
Constrained Physical Design Tuning |
2008 |
VLDB |
7.6043371e-05 |
| 3,144 |
Active Learning for ML Enhanced Database Systems |
2020 |
SIGMOD |
7.4844943e-05 |
| 3,276 |
Configuration-Parametric Query Optimization for Physical Design Tuning |
2008 |
SIGMOD |
7.2880761e-05 |
| 3,345 |
Lero: A Learning-to-Rank Query Optimizer |
2023 |
VLDB |
7.1908499e-05 |
| 3,376 |
Storage Workload Estimation for Database Management Systems |
2007 |
SIGMOD |
7.1621421e-05 |
| 3,482 |
Optimal Column Layout for Hybrid Workloads |
2019 |
VLDB |
7.0514808e-05 |
| 3,655 |
Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation |
2022 |
VLDB |
6.8723042e-05 |
| 3,661 |
Database Tuning Advisor for Microsoft SQL Server 2005: Demo |
2005 |
SIGMOD |
6.8680306e-05 |
| 3,893 |
Slalom: Coasting Through Raw Data via Adaptive Partitioning and Indexing |
2017 |
VLDB |
6.653922e-05 |
| 3,897 |
Updating a Cracked Database |
2007 |
SIGMOD |
6.6526754e-05 |
| 3,923 |
Pushing Data-Induced Predicates Through Joins in Big-Data Clusters |
2020 |
VLDB |
6.6232068e-05 |
| 3,943 |
Exact Cardinality Query Optimization for Optimizer Testing |
2009 |
VLDB |
6.6067351e-05 |
| 4,107 |
Cracking the Database Store |
2005 |
CIDR |
6.4384924e-05 |
| 4,469 |
Comprehensive and Efficient Workload Compression |
2021 |
VLDB |
6.1535623e-05 |
| 4,507 |
Stochastic Database Cracking: Towards Robust Adaptive Indexing in Main-Memory Column-Stores |
2012 |
VLDB |
6.1271582e-05 |
| 4,621 |
Automated Generation of Materialized Views in Oracle |
2020 |
VLDB |
6.036749e-05 |
| 4,687 |
Deploying a Steered Query Optimizer in Production at Microsoft |
2022 |
SIGMOD |
5.9915268e-05 |
| 5,110 |
Only Aggressive Elephants are Fast Elephants |
2012 |
VLDB |
5.6868273e-05 |
| 5,111 |
Adaptive NUMA-aware data placement and task scheduling for analytical workloads in main-memory column-stores |
2017 |
VLDB |
5.6855393e-05 |
| 5,114 |
Columnstore and B+ tree – Are Hybrid Physical Designs Important? |
2018 |
SIGMOD |
5.6813929e-05 |
| 5,378 |
Holistic Indexing in Main-memory Column-stores |
2015 |
SIGMOD |
5.5379945e-05 |
| 5,834 |
An Efficient Transfer Learning Based Configuration Adviser for Database Tuning |
2024 |
VLDB |
5.3082111e-05 |
| 5,920 |
Breaking Down Memory Walls: Adaptive Memory Management in LSM-based Storage Systems |
2021 |
VLDB |
5.2686888e-05 |
| 6,160 |
Compression Aware Physical Database Design |
2011 |
VLDB |
5.1750659e-05 |
| 6,341 |
Operator and Query Progress Estimation in Microsoft SQL Server Live Query Statistics |
2016 |
SIGMOD |
5.0980049e-05 |
| 6,364 |
ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning |
2022 |
SIGMOD |
5.0895007e-05 |
| 6,394 |
Endure: A Robust Tuning Paradigm for LSM Trees Under Workload Uncertainty |
2022 |
VLDB |
5.0770427e-05 |
| 6,478 |
A Statistical Approach Towards Robust Progress Estimation |
2012 |
VLDB |
5.040535e-05 |
| 7,126 |
Guided automated learning for query workload re-optimization |
2019 |
VLDB |
4.8184704e-05 |
| 7,217 |
Breaking Down Memory Walls in LSM-based Storage Systems |
2020 |
SIGMOD |
4.7936491e-05 |
| 7,445 |
An Automated, Yet Interactive and Portable DB Designer |
2010 |
SIGMOD |
4.7235588e-05 |
| 8,003 |
The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions |
2024 |
VLDB |
4.6049527e-05 |
| 8,043 |
DISTILL: Low-Overhead Data-Driven Techniques for Filtering and Costing Indexes for Scalable Index Tuning |
2022 |
VLDB |
4.5954398e-05 |
| 8,095 |
Grep: A Graph Learning Based Database Partitioning System |
2023 |
SIGMOD |
4.5837691e-05 |