Tuning Database Configuration Parameters with iTuned
Summary: Adaptive Sampling identifies high-impact DB configuration parameters and optimal settings. Online production experiments via a cycle-stealing executor incur near-zero overhead and portable across DBMS, validated by diverse workloads. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Songyun Duan
- 2. Vamsidhar Thummala
- 3. Shivnath Babu
Incoming Citations (Sorted by Pagerank)
Showing 11 of 61 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 14 | Online Aggregation | 1997 | SIGMOD | 0.0010813443 |
| 477 | Model-Driven Data Acquisition in Sensor Networks | 2004 | VLDB | 0.00022205608 |
| 517 | AutoAdmin "What-if" Index Analysis Utility | 1998 | SIGMOD | 0.00021193179 |
| 661 | Adaptive Self-Tuning Memory in DB2 | 2006 | VLDB | 0.00018488168 |
| 841 | Self-tuning Database Technology and Information Services: from Wishful Thinking to Viable Engineering | 2002 | VLDB | 0.00015987128 |
| 886 | Automatic Virtual Machine Configuration for Database Workloads | 2008 | SIGMOD | 0.00015563003 |
| 1,443 | Compressing SQL Workloads | 2002 | SIGMOD | 0.00011944621 |
| 1,790 | Effective Use of Block-Level Sampling in Statistics Estimation | 2004 | SIGMOD | 0.00010529479 |
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