Efficient Optimization of Iterative Queries

  • Leonidas Fegaras
Conference paper
Part of the Workshops in Computing book series (WORKSHOPS COMP.)

Abstract

This paper presents a new query algebra based on fold iterations that facilitates database implementation. An algebraic normalization algorithm is introduced that reduces any program expressed in this algebra to a canonical form that generates no intermediate data structures and has no more nested iterations than the initial program. Given any inductive data type, our system can automatically synthesize the definition of the fold operator that traverses instances of this type, and, more importantly, it can produce the necessary transformations for optimizing expressions involving this fold operator.

Database implementation in our framework is controlled by userdefined mappings from abstract types to physical structures. The optimizer uses this information to translate abstract programs and queries into concrete algorithms that conform to the type transformation. Database query optimization can be viewed as a search over the reduced space of all canonical forms which are equivalent to the query after type transformation and normalization. The optimization space can be expanded to capture semantic information expressed as integrity constraints attached to types. This information may include specifications of materialized views and of alternative access paths.

The contribution of this paper is twofold. First, a new efficient algebraic optimization algorithm is introduced, based on loop fusion and partial evaluation, that normalizes a large class of queries over a wide spectrum of bulk data structures. Second, an effective query optimizer is described that searches the limited space of equivalent canonical forms for optimal programs, using additional semantic information to generate more alternatives.

Keywords

Canonical Form Integrity Constraint Query Optimizer Normalization Algorithm Type Transformation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • Leonidas Fegaras
    • 1
  1. 1.Department of Computer Science and EngineeringOregon Graduate Institute of Science & TechnologyPortlandUSA

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