Database tuning advisor for microsoft SQL server 2005: demo

By Sanjay Agrawal, Surajit Chaudhuri, L. Kollár, A. Marathe, Vivek R. Narasayya, M. Syamala. ACM SIGMOD Conference, 2005

320 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Signal Processing

View Paper: https://www.semanticscholar.org/paper/ba800a2afe15498b3961a13831d982c9fe495547

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Vivek R. Narasayya
2. Surajit Chaudhuri
3. Nicolas Bruno

In Computer Networks and Communications

1. Surajit Chaudhuri
2. Vivek R. Narasayya
3. Nicolas Bruno
4. Yannis E. Ioannidis
5. Yannis Papakonstantinou
6. Vagelis Hristidis

In Signal Processing

1. Surajit Chaudhuri
2. Vivek R. Narasayya
3. Nicolas Bruno
4. Yannis E. Ioannidis
5. Yannis Papakonstantinou
6. Vagelis Hristidis

Citations in the corpus

• To Tune or not to Tune? A Lightweight Physical Design Alerter (2006, methodology): “When experiments require a comprehensive tuning tool, we use Microsoft SQL Server Database Tuning Advisor [1].”
• Self-Tuning Database Systems: A Decade of Progress (2007, methodology): “Thus only a “shell” database is imported into the test server [ 7 ] before tuning.”
• DISTILL: Low-Overhead Data-Driven Techniques for Filtering and Costing Indexes for Scalable Index Tuning (2022, methodology): “For instance, Table 2 depicts a set of rules similar to the ones used by DTA [6].”