Research issues in automatic database clustering

  • Authors:
  • Sylvain Guinepain;Le Gruenwald

  • Affiliations:
  • The University of Oklahoma, Norman, OK;The University of Oklahoma, Norman, OK

  • Venue:
  • ACM SIGMOD Record
  • Year:
  • 2005

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Abstract

While a lot of work has been published on clustering of data on storage medium, little has been done about automating this process. This is an important area because with data proliferation, human attention has become a precious and expensive resource. Our goal is to develop an automatic and dynamic database clustering technique that will dynamically re-cluster a database with little intervention of a database administrator (DBA) and maintain an acceptable query response time at all times. In this paper we describe the issues that need to be solved when developing such a technique.