Title
Goals and benchmarks for autonomic configuration recommenders
Abstract
We are witnessing an explosive increase in the complexity of the information systems we rely upon, Autonomic systems address this challenge by continuously configuring and tuning themselves. Recently, a number of autonomic features have been incorporated into commercial RDBMS; tools for recommending database configurations (i.e., indexes, materialized views, partitions) for a given workload are prominent examples of this promising trend.In this paper, we introduce a flexible characterization of the performance goals of configuration recommenders and develop an experimental evaluation approach to benchmark the effectiveness of these autonomic tools. We focus on exploratory queries and present extensive experimental results using both real and synthetic data that demonstrate the validity of the approach introduced. Our results identify a specific index configuration based on single-column indexes as a very useful baseline for comparisons in the exploratory setting. Furthermore, the experimental results demonstrate the unfulfilled potential for achieving improvements of several orders of magnitude.
Year
DOI
Venue
2005
10.1145/1066157.1066185
SIGMOD Conference
Keywords
Field
DocType
database configuration,autonomic configuration recommenders,exploratory query,autonomic feature,configuration recommenders,autonomic tool,present extensive experimental result,exploratory setting,experimental evaluation approach,autonomic system,synthetic data,navigation,information system,metadata,materialized views,indexation,information retrieval
Information system,Metadata,Data mining,Information retrieval,Workload,Computer science,Explosive material,Synthetic data,Relational database management system,Materialized view,Database
Conference
ISBN
Citations 
PageRank 
1-59593-060-4
12
0.78
References 
Authors
18
4
Name
Order
Citations
PageRank
Mariano P. Consens11203387.78
Denilson Barbosa261043.52
Adrian Teisanu3120.78
Laurent Mignet434529.41