Detection and Correction of Conflicting Source Updates for View Maintenance

• Authors: Songting Chen;Jun Chen;Xin Zhang;Elke A. Rundensteiner
• Venue: ICDE '04 Proceedings of the 20th International Conference on Data Engineering
• Year: 2004

Data integration over multiple heterogeneous datasources has become increasingly important for modern applications. The integrated data is usually stored in materialized views for high availability and better performance. Such views must be maintained after the datasources change. In a loosely-coupled and dynamic environment, such as the Data Grid, the sources may autonomously change not only their data but also their schema, query capabilities or semantics, which may consequently cause theon-going view maintenance fail. In this paper, first, we analyze the maintenance errors and classify them into different classes of dependencies. We then propose severaldependency detection and correction algorithms to handle these new classes of concurrency. Our techniques arenot tied to specific maintenance algorithms nor to a particular data model. To our knowledge, this is the first completesolution to the view maintenance concurrency problems for both data and schema changes. We have implemented the proposed solutions and experimentally evaluated the impact of anomalies on maintenance performanceand trade-offs between different dependency detection algorithms.