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ChunkSim: A Tool and Analysis of Performance and Availability Balancing

ChunkSim: A Tool and Analysis of Performance and Availability Balancing

Pedro Furtado
Copyright: © 2010 |Pages: 19
ISBN13: 9781605667560|ISBN10: 1605667560|ISBN13 Softcover: 9781616924492|EISBN13: 9781605667577
DOI: 10.4018/978-1-60566-756-0.ch008
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MLA

Furtado, Pedro. "ChunkSim: A Tool and Analysis of Performance and Availability Balancing." Data Warehousing Design and Advanced Engineering Applications: Methods for Complex Construction, edited by Ladjel Bellatreche, IGI Global, 2010, pp. 131-149. https://doi.org/10.4018/978-1-60566-756-0.ch008

APA

Furtado, P. (2010). ChunkSim: A Tool and Analysis of Performance and Availability Balancing. In L. Bellatreche (Ed.), Data Warehousing Design and Advanced Engineering Applications: Methods for Complex Construction (pp. 131-149). IGI Global. https://doi.org/10.4018/978-1-60566-756-0.ch008

Chicago

Furtado, Pedro. "ChunkSim: A Tool and Analysis of Performance and Availability Balancing." In Data Warehousing Design and Advanced Engineering Applications: Methods for Complex Construction, edited by Ladjel Bellatreche, 131-149. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-60566-756-0.ch008

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Abstract

Self-tuning physical database organization involves tools that determine automatically the best solution concerning partitioning, placement, creation and tuning of auxiliary structures (e.g. indexes), based on the workload. To the best of our knowledge, no tool has focused on a relevant issue in parallel databases and in particular data warehouses running on common off-the-shelf hardware in a sharednothing configuration: determining the adequate tradeoff for balancing load and availability with costs (storage and loading costs). In previous work, we argued that effective load and availability balancing over partitioned datasets can be obtained through chunk-wise placement and replication, together with on-demand processing. In this work, we propose ChunkSim, a simulator for system size planning, performance analysis against replication degree and availability analysis. We apply the tool to illustrate the kind of results that can be obtained by it. The whole discussion in the chapter provides very important insight into data allocation and query processing over shared-nothing data warehouses and how a good simulation analysis tool can be built to predict and analyze actual systems and intended deployments.

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