Self-monitoring query execution for adaptive query processing

  • Authors:

  • Anastasios Gounaris;Norman W. Paton;Alvaro A. A. Fernandes;Rizos Sakellariou

  • Affiliations:

  • Department of Computer Science, University of Manchester, Oxford Road, Manchester M13 9PL, UK;Department of Computer Science, University of Manchester, Oxford Road, Manchester M13 9PL, UK;Department of Computer Science, University of Manchester, Oxford Road, Manchester M13 9PL, UK;Department of Computer Science, University of Manchester, Oxford Road, Manchester M13 9PL, UK

  • Venue:
  • Data & Knowledge Engineering
  • Year:
  • 2004

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Abstract

Adaptive query processing generally involves a feedback loop comprising monitoring, assessment and response. So far, individual proposals have tended to group together an approach to monitoring, a means of assessment, and a form of response. However, there are many benefits in decoupling these three phases, and in constructing generic frameworks for each of them. To this end, this paper discusses monitoring of query plan execution as a topic in its own right, and advocates an approach based on self-monitoring algebraic operators. This approach is shown to be generic and independent of any specific adaptation mechanism, easily implementable and portable, sufficiently comprehensive, appropriate for heterogeneous distributed environments, and more importantly, capable of driving on-the-fly adaptations of query plan execution. An experimental evaluation of the overheads and of the quality of the results obtained by monitoring is also presented.