"Physical Data Independence, Constraints and Optimization with Universa" by Alin Deutsch, Lucian Popa et al.

Database Research Group (CIS)

Title

Physical Data Independence, Constraints and Optimization with Universal Plans

Author(s)

Alin Deutsch, University of Pennsylvania
Lucian Popa, University of Pennsylvania
Val Tannen, University of Pennsylvania

Document Type

Conference Paper

Date of this Version

September 1999

Comments

Postprint version. Published in International Conference on Very Large Databases (VLDB) (1999), pages 459-470.
Publisher URL: http://www.dcs.napier.ac.uk/~vldb99/

Abstract

We present an optimization method and al gorithm designed for three objectives: physi cal data independence, semantic optimization, and generalized tableau minimization. The method relies on generalized forms of chase and "backchase" with constraints (dependen cies). By using dictionaries (finite functions) in physical schemas we can capture with con straints useful access structures such as indexes, materialized views, source capabilities, access support relations, gmaps, etc. The search space for query plans is defined and enumerated in a novel manner: the chase phase rewrites the original query into a "universal" plan that integrates all the access structures and alternative pathways that are allowed by appli cable constraints. Then, the backchase phase produces optimal plans by eliminating various combinations of redundancies, again according to constraints. This method is applicable (sound) to a large class of queries, physical access structures, and semantic constraints. We prove that it is in fact complete for "path-conjunctive" queries and views with complex objects, classes and dictio naries, going beyond previous theoretical work on processing queries using materialized views.

Download