Malting multiple views self-maintainable in a data warehouse

A data warehouse collects and maintains a large amount of data from several distributed and heterogeneous data sources. Often the data is stored in th e form of materialized views in order to provide fast access to the integra ted data, regardless of the availability of the data sources. In this paper we focus on the following problem: for a given set of materialized select- project-join (SPJ) views, how can we find and minimize the auxiliary data s tored in a data warehouse in order to make all materialized views in the da ta warehouse self-maintainable? For this problem we first devise an algorit hm for finding such an auxiliary view set by exploiting information sharing among the auxiliary views and materialized views themselves to reduce the total size of auxiliary views. We then consider how to make the data wareho use still self-maintainable by minor modifications when there is a view add ition to or deletion from it by giving an algorithm for this incremental ma intenance purpose. (C) 1999 Elsevier Science B.V. All rights reserved.