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DEXA
2008
Springer

Compressing Very Large Database Workloads for Continuous Online Index Selection

14 years 10 months ago
Compressing Very Large Database Workloads for Continuous Online Index Selection
The paper presents a novel method for compressing large database workloads for purpose of autonomic, continuous index selection. The compressed workload contains a small subset of representative queries from the original workload. A single pass clustering algorithm with a simple and elegant selectivity based query distance metric guarantees low memory and time complexity. Experiments on two real-world database workloads show the method achieves high compression ratio without decreasing the quality of the index selection problem solutions. Key words: database workload compression, automatic index selection
Piotr Kolaczkowski
Added 19 Oct 2010
Updated 19 Oct 2010
Type Conference
Year 2008
Where DEXA
Authors Piotr Kolaczkowski
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