Affiliation:
1. The University of Texas at Arlington
2. Oregon Graduate Institute of Science and Technology
Abstract
Object-oriented databases (OODBs) provide powerful data abstractions and modeling facilities, but they generally lack a suitable framework for query processing and optimization. The development of an effective query optimizer is one of the key factors for OODB systems to successfully compete with relational systems, as well as to meet the performance requirements of many nontraditional applications. We propose an effective framework with a solid theoretical basis for optimizing OODB query languages. Our calculus, called the monoid comprehension calculus, captures most features of ODMG OQL, and is a good basis for expressing various optimization algorithms concisely. This article concentrates on query unnesting (also known as query decorrelation), an optimization that, even though it improves performance considerably, is not treated properly (if at all) by most OODB systems. Our framework generalizes many unnesting techniques proposed recently in the literature, and is capable of removing any form of query nesting using a very simple and efficient algorithm. The simplicity of our method is due to the use of the monoid comprehension calculus as an intermediate form for OODB queries. The monoid comprehension calculus treats operations over multiple collection types, aggregates, and quantifiers in a similar way, resulting in a uniform method of unnesting queries, regardless of their type of nesting.
Publisher
Association for Computing Machinery (ACM)
Cited by
82 articles.
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