Ling Hu
Kenneth A. Ross
Abstract
Reading and perceiving complex SQL queries has been a time consuming task in traditional database applications for decades. When it comes to decision support systems with automatically generated and sometimes highly nested SQL queries, human understanding or tuning of these workloads becomes even more challenging. This demonstration explores visualization methods to represent queries as graphs. We developed the QueryScope tool to help visualize and understand critical elements of a query, thereby cutting down the learning curve. We show how the tool allows the user to drill down on particular queries or to find similarly structured queries that may exhibit similar tuning opportunities. The queries shown in the demonstration are taken from real tuning engagements.
- R. Ahuja. Self-tuning Memory in DB2 Version 9. http://www.ibm.com/developerworks/db2/library/techarticle/dm-0606ahuja/, 2006.Google Scholar
- N. Bruno and S. Chaudhuri. Automatic Physical Database Tuning: A Relaxation-based Approach. In SIGMOD, pages 227--238, 2005. Google ScholarDigital Library
- N. Bruno and S. Chaudhuri. To Tune or not to Tune? A Lightweight Physical Design Alerter. In VLDB, pages 499--510, 2006. Google ScholarDigital Library
- S. Chaudhuri and V. R. Narasayya. Self-Tuning Database Systems: A Decade of Progress. In VLDB, pages 3--14, 2007. Google ScholarDigital Library
- R. Chirkova, A. Y. Halevy, and D. Suciu. A Formal Perspective on the View Selection Problem. In VLDB, pages 59--69, 2001. Google ScholarDigital Library
- K. Dias, M. Ramacher, U. Shaft, V. Venkataramani, and G. Wood. Automatic Performance Diagnosis and Tuning in Oracle. In CIDR, pages 84--94, 2005.Google Scholar
- D. Shasha and P. Bonnet. Database Tuning: Principles, Experiments, and Troubleshooting Techniques. Morgan Kaufmann, 2002. Google ScholarDigital Library
- E. R. Tufte. Envisioning Information. Graphics Press, 1990. Google ScholarDigital Library
- D. C. Zilio, J. Rao, S. Lightstone, G. M. Lohman, A. Storm, C. Garcia-Arellano, and S. Fadden. DB2 Design Advisor: Integrated Automatic Physical Database Design. In VLDB, pages 1087--1097, 2004. Google ScholarDigital Library
- D. C. Zilio, C. Zuzarte, S. Lightstone, and W. M. et al. Recommending Materialized Views and Indexes With the IBM DB2 Design Advisor. In International Conference on Autonomic Computing, 2004. Google ScholarDigital Library
Index Terms
- QueryScope: visualizing queries for repeatable database tuning
Recommendations
A Model and Framework for Visualization Exploration
Visualization exploration is the process of extracting insight from data via interaction with visual depictions of that data. Visualization exploration is more than presentation; the interaction with both the data and its depiction is as important as ...
Browsing Zoomable Treemaps: Structure-Aware Multi-Scale Navigation Techniques
Treemaps provide an interesting solution for representing hierarchical data. However, most studies have mainly focused on layout algorithms and paid limited attention to the interaction with treemaps. This makes it difficult to explore large data sets ...
Comments