Cost Models for Selecting Materialized Views in Public Clouds

Romain Perriot, Jérémy Pfeifer, Laurent d'Orazio, Bruno Bachelet, Sandro Bimonte and Jérôme Darmont
Additional contact information
Romain Perriot: Clermont Université, Université Blaise Pascal, Aubière Cedex, France
Jérémy Pfeifer: Clermont Université, Université Blaise Pascal, Aubière Cedex, France
Laurent d'Orazio: Clermont Université, Université Blaise Pascal, Aubière Cedex, France
Bruno Bachelet: Clermont Université, Université Blaise Pascal, Aubière Cedex, France
Sandro Bimonte: IRSTEA, Clermont-Ferrand, France
Jérôme Darmont: Laboratoire ERIC, Université de Lyon, Lyon, France

International Journal of Data Warehousing and Mining (IJDWM), 2014, vol. 10, issue 4, 1-25

Abstract: Data warehouse performance is usually achieved through physical data structures such as indexes or materialized views. In this context, cost models can help select a relevant set of such performance optimization structures. Nevertheless, selection becomes more complex in the cloud. The criterion to optimize is indeed at least two-dimensional, with monetary cost balancing overall query response time. This paper introduces new cost models that fit into the pay-as-you-go paradigm of cloud computing. Based on these cost models, an optimization problem is defined to discover, among candidate views, those to be materialized to minimize both the overall cost of using and maintaining the database in a public cloud and the total response time of a given query workload. It experimentally shows that maintaining materialized views is always advantageous, both in terms of performance and cost.

Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/ijdwm.2014100101 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jdwm00:v:10:y:2014:i:4:p:1-25

Access Statistics for this article

International Journal of Data Warehousing and Mining (IJDWM) is currently edited by Eric Pardede

More articles in International Journal of Data Warehousing and Mining (IJDWM) from IGI Global
Bibliographic data for series maintained by Journal Editor ().