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The EVE approach: view synchronization in dynamic distributed environments

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3 Author(s)
A. J. Lee ; Center for Human Resources, Columbus, OH, USA ; A. Nica ; E. A. Rundensteiner

The construction and maintenance of data warehouses (views) in large-scale environments composed of numerous distributed and evolving information sources (ISs) such as the WWW has received great attention recently. Such environments are plagued with changing information because ISs tend to continuously evolve by modifying not only their content but also their query capabilities and interface and by joining or leaving the environment at any time. We are the first to introduce and address the problem of schema changes of ISs, while previous work in this area, such as incremental view maintenance, has mainly dealt with data changes at ISs. We outline our solution approach to this challenging new problem of how to adapt views in such evolving environments. We identify a new view adaptation problem for view evolution in the context of ISs schema changes, which we call view synchronization. We also outline the Evolvable View Environment (EVE) approach that we propose as framework for solving the view synchronization problem, along with our decisions concerning the key design issues surrounding EVE. The main contributions of this paper are: 1) we provide an E-SQL view definition language with which the view definer can direct the view evolution process, 2) we introduce a model for information source description which allows a large class of ISs to participate in our system dynamically, 3) we formally define what constitutes a legal view rewriting, 4) we develop replacement strategies for affected view components which are designed to meet the preferences expressed by E-SQL, 5) we prove the correctness of the replacement strategies, and 6) we provide a set of view synchronization algorithms based on those strategies. A prototype of our EVE system has successfully been built using Java, JDBC, Oracle, and MS Access.

Published in:

IEEE Transactions on Knowledge and Data Engineering  (Volume:14 ,  Issue: 5 )