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Exploring the tradeoff between performance and data freshness in database-driven Web servers

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Abstract.

Personalization, advertising, and the sheer volume of online data generate a staggering amount of dynamic Web content. In addition to Web caching, view materialization has been shown to accelerate the generation of dynamic Web content. View materialization is an attractive solution as it decouples the serving of access requests from the handling of updates. In the context of the Web, selecting which views to materialize must be decided online and needs to consider both performance and data freshness, which we refer to as the online view selection problem. In this paper, we define data freshness metrics, provide an adaptive algorithm for the online view selection problem that is based on user-specified data freshness requirements, and present experimental results. Furthermore, we examine alternative metrics for data freshness and extend our proposed algorithm to handle multiple users and alternative definitions of data freshness.

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Authors and Affiliations

  1. Department of Computer Science, University of Pittsburgh, PA, 15260, Pittburgh, USA

    Alexandros Labrinidis

  2. Department of Computer Science, University of Maryland, MD, 20742, College Park, USA

    Nick Roussopoulos

Authors
  1. Alexandros Labrinidis
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  2. Nick Roussopoulos
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Corresponding author

Correspondence to Alexandros Labrinidis.

Additional information

Received: 17 January 2004, Accepted: 23 March 2004, Published online: 19 August 2004

Edited by: S. Abiteboul

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Labrinidis, A., Roussopoulos, N. Exploring the tradeoff between performance and data freshness in database-driven Web servers. VLDB 13, 240–255 (2004). https://doi.org/10.1007/s00778-004-0131-7

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  • DOI: https://doi.org/10.1007/s00778-004-0131-7

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