| 160 |
Automated Selection of Materialized Views and Indexes for SQL Databases |
2000 |
VLDB |
0.00040053897 |
| 183 |
Automatic Database Management System Tuning Through Large-scale Machine Learning |
2017 |
SIGMOD |
0.00036859633 |
| 258 |
DB2 Design Advisor: Integrated Automatic Physical Database Design |
2004 |
VLDB |
0.00030196528 |
| 283 |
Integrating Vertical and Horizontal Partitioning into Automated Physical Database Design |
2004 |
SIGMOD |
0.00029024583 |
| 371 |
Self-Driving Database Management Systems |
2017 |
CIDR |
0.00025382677 |
| 423 |
Tuning Database Configuration Parameters with iTuned |
2009 |
VLDB |
0.00023628474 |
| 430 |
Approximate Query Processing: Taming the TeraBytes! A Tutorial |
2001 |
VLDB |
0.00023406426 |
| 510 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.00021420477 |
| 662 |
Database Tuning Advisor for Microsoft SQL Server 2005 |
2004 |
VLDB |
0.00018478597 |
| 679 |
Skew-Aware Automatic Database Partitioning in Shared-Nothing, Parallel OLTP Systems |
2012 |
SIGMOD |
0.00018211621 |
| 786 |
Exploiting Statistics on Query Expressions for Optimization |
2002 |
SIGMOD |
0.00016624743 |
| 1,018 |
Automatic Physical Database Tuning: A Relaxation-based Approach |
2005 |
SIGMOD |
0.00014626746 |
| 1,533 |
PerfXplain: Debugging MapReduce Job Performance |
2012 |
VLDB |
0.00011462982 |
| 1,709 |
Microsoft Index Tuning Wizard for SQL Server 7.0 |
1998 |
SIGMOD |
0.00010799651 |
| 1,816 |
An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems |
2021 |
VLDB |
0.00010438512 |
| 1,856 |
AI Meets AI: Leveraging Query Executions to Improve Index Recommendations |
2019 |
SIGMOD |
0.00010319105 |
| 2,050 |
Automatically Indexing Millions of Databases in Microsoft Azure SQL Database |
2019 |
SIGMOD |
9.6883066e-05 |
| 2,309 |
On Predictive Modeling for Optimizing Transaction Execution in Parallel OLTP Systems |
2012 |
VLDB |
9.0630462e-05 |
| 2,410 |
Automated Partitioning Design in Parallel Database Systems |
2011 |
SIGMOD |
8.8643562e-05 |
| 2,738 |
The Case for Data Visualization Management Systems [Vision Paper] |
2014 |
VLDB |
8.2039241e-05 |
| 2,788 |
To Tune or not to Tune? A Lightweight Physical Design Alerter |
2006 |
VLDB |
8.121027e-05 |
| 3,077 |
Constrained Physical Design Tuning |
2008 |
VLDB |
7.6043371e-05 |
| 3,276 |
Configuration-Parametric Query Optimization for Physical Design Tuning |
2008 |
SIGMOD |
7.2880761e-05 |
| 3,376 |
Storage Workload Estimation for Database Management Systems |
2007 |
SIGMOD |
7.1621421e-05 |
| 3,661 |
Database Tuning Advisor for Microsoft SQL Server 2005: Demo |
2005 |
SIGMOD |
6.8680306e-05 |
| 3,878 |
Data Canopy: Accelerating Exploratory Statistical Analysis |
2017 |
SIGMOD |
6.6669911e-05 |
| 4,151 |
openGauss: An Autonomous Database System |
2021 |
VLDB |
6.4020605e-05 |
| 4,280 |
Primitives for Workload Summarization and Implications for SQL |
2003 |
VLDB |
6.28375e-05 |
| 4,621 |
Automated Generation of Materialized Views in Oracle |
2020 |
VLDB |
6.036749e-05 |
| 4,635 |
Mining Precision Interfaces From Query Logs |
2019 |
SIGMOD |
6.0275975e-05 |
| 4,863 |
COLT: Continuous On-Line Database Tuning |
2006 |
SIGMOD |
5.8646122e-05 |
| 5,114 |
Columnstore and B+ tree – Are Hybrid Physical Designs Important? |
2018 |
SIGMOD |
5.6813929e-05 |
| 5,343 |
Learned Index Benefits: Machine Learning Based Index Performance Estimation |
2022 |
VLDB |
5.5582234e-05 |
| 5,378 |
Holistic Indexing in Main-memory Column-stores |
2015 |
SIGMOD |
5.5379945e-05 |
| 5,445 |
Materialized View and Index Selection Tool for Microsoft SQL Server 2000 |
2001 |
SIGMOD |
5.499851e-05 |
| 5,673 |
Budget-aware Index Tuning with Reinforcement Learning |
2022 |
SIGMOD |
5.3789277e-05 |
| 5,695 |
Optimal Indexing Using Near-Minimal Space [Extended Abstract] |
2003 |
PODS |
5.3675705e-05 |
| 5,742 |
Efficient Computation of Multiple Group By Queries |
2005 |
SIGMOD |
5.3432178e-05 |
| 5,750 |
JECB: a Join-Extension, Code-Based Approach to OLTP Data Partitioning |
2014 |
SIGMOD |
5.340715e-05 |
| 5,925 |
HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning |
2023 |
VLDB |
5.2669029e-05 |
| 6,298 |
Towards instance-optimized data systems |
2021 |
VLDB |
5.1182917e-05 |
| 6,328 |
A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies |
2024 |
VLDB |
5.1034426e-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 |
| 6,708 |
Just-In-Time Data Structures |
2015 |
CIDR |
4.948865e-05 |
| 7,000 |
Progressive Indexes: Indexing for Interactive Data Analysis |
2019 |
VLDB |
4.862486e-05 |
| 7,127 |
Jigsaw: A Data Storage and Query Processing Engine for Irregular Table Partitioning |
2021 |
SIGMOD |
4.8184276e-05 |
| 7,332 |
Refactoring Index Tuning Process with Benefit Estimation |
2024 |
VLDB |
4.7553758e-05 |
| 7,591 |
Automated design of multidimensional clustering tables for relational databases |
2004 |
VLDB |
4.6986414e-05 |
| 7,787 |
Cost-Intelligent Data Analytics in the Cloud |
2024 |
CIDR |
4.6468106e-05 |