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DAWAK
2008
Springer

Workload-Aware Histograms for Remote Applications

14 years 2 months ago
Workload-Aware Histograms for Remote Applications
Recently several database-based applications have emerged that are remote from data sources and need accurate histograms for query cardinality estimation. Traditional approaches for constructing histograms require complete access to data and are I/O and network intensive, and therefore no longer apply to these applications. Recent approaches use queries and their feedback to construct and maintain "workload aware" histograms. However, these approaches either employ heuristics, thereby providing no guarantees on the overall histogram accuracy, or rely on detailed query feedbacks, thus making them too expensive to use. In this paper, we propose a novel, incremental method for constructing histograms that uses minimum feedback and guarantees minimum overall residual error. Experiments on real, high dimensional data shows 30-40% higher estimation accuracy over currently known heuristic approaches, which translates to significant performance improvement of remote applications.
Tanu Malik, Randal C. Burns
Added 19 Oct 2010
Updated 19 Oct 2010
Type Conference
Year 2008
Where DAWAK
Authors Tanu Malik, Randal C. Burns
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