文摘
A data warehouse is a repository (database) that integrates information extracted from various remote sources, with the purpose of efficiently supporting decision support queries. The information stored at the warehouse is in the form of database tables, referred to as materialized views, derived from the data in the sources. In order to keep a materialized view consistent with the data at sources, the view needs to be incrementally maintained. The two important issues that arise in the design of a data warehouse are selection of views to materialize and incremental maintenance of materialized views. This doctoral thesis looks at these two design issues and presents comprehensive solutions to both problems.;Selection of views to materialize. We develop a theoretical framework for the general problem of selection of views in a data warehouse. Given a set of queries to be supported, the view selection problem is to select a set of views to materialize minimizing the query response time given some resource constraint. For different resource constraints and settings, we have designed approximation algorithms that provably return a set of views having a query benefit within a constant factor of the optimal.;Incremental maintenance of general view expressions. Traditional maintenance algorithms maintain view expressions in response to changes at the base relations by computing and propagating insertions and deletions through intermediate subexpressions. In this thesis, we have developed a change-table technique, that computes and propagates “change-tables” through subexpressions, for incremental maintenance of general view expressions involving aggregate and outerjoin operators. We show that the presented change-table technique outperforms the previously proposed techniques by orders of magnitude.
