This paper concentrates on query unnesting (also known as query decorrelation), an optimization that, even though 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 way of unnesting queries, regardless of their type of nesting.

Even though XML was rst introduced as a schema-less, self-describing data representation

View materialization is an important technique for high performance query processing, data integration and replication. Solutions to the problem of incrementally maintaining materialized views are very relevant. So far, most work on this problem has been confined to relational settings and solutions have not been comprehensively evaluated. This paper describes MOVIE, a complete, implemented and evaluated solution to the problem of incrementally maintaining materialized OQL views in ODMG-compliant object databases. The evaluation throws light into how the e#ectiveness of incremental maintenance is a#ected by issues such as database size, and the complexity and selectivity of views.

This work presents a rule-based approach for declarative query optimizer generation considering parallel execution in object-oriented databases. The main goal of this work is to provide a framework that can capture relevant aspects of parallel query optimization in a declarative way, combining procedural techniques with the advantages of rule processing. One of those techniques was used for determining repartitioning and selecting the algorithms to evaluate operator in a query tree considering the trade-offs between processing costs and repartitioning costs. This technique was proposed as a procedural algorithm and it was adapted to be used as rules in the context of object-oriented database optimizers. Another algorithm, used for query operator reordering in object-oriented databases, was adapted in order to consider repartitioning cost and was added to the framework. Finally, a new module for processing rules for parallelism extraction was added to the framework, providing a better support for inter-operator parallelism optimization techniques. 1

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