A statistics propagation approach to enable cost-based optimization of statement sequences

  • Authors:

  • Tobias Kraft;Holger Schwarz;Bernhard Mitschang

  • Affiliations:

  • Institute of Parallel and Distributed Systems, University of Stuttgart, Stuttgart, Germany;Institute of Parallel and Distributed Systems, University of Stuttgart, Stuttgart, Germany;Institute of Parallel and Distributed Systems, University of Stuttgart, Stuttgart, Germany

  • Venue:
  • ADBIS'07 Proceedings of the 11th East European conference on Advances in databases and information systems
  • Year:
  • 2007

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Abstract

Query generators producing sequences of SQL statements are embedded in many applications. As the response time of such sequences is often far from optimal, their optimization is an important issue. CGO (Coarse-Grained Optimization) is an appropriate optimization approach that applies rewrite rules to statement sequences. In previous work on CGO, a heuristic, priority-based control strategy was utilized to choose and execute rewrite rules. In this paper, we present an approach to enable cost-based optimization of statement sequences. We show how to exploit histogram propagation and the costing component of the underlying database system for this purpose. Our work extends previous work on histogram propagation. We conclude with experiments demonstrating the effectiveness of our approach.