Batch data warehouse maintenance in dynamic environments

  • Authors:

  • Bin Liu;Songting Chen;Elke A. Rundensteiner

  • Affiliations:

  • Worcester Polytechnic Institute, MA;Worcester Polytechnic Institute, MA;Worcester Polytechnic Institute, MA

  • Venue:
  • Proceedings of the eleventh international conference on Information and knowledge management
  • Year:
  • 2002

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Abstract

Data warehouse view maintenance is an important issue due to the growing use of warehouse technology for information integration and data analysis. Given the dynamic nature of modern distributed environments, both data updates and schema changes are likely to occur in different data sources. In applications that the real-time refreshment of data warehouse extent under source changes is not critical, the source updates are usually maintained in a batch fashion to reduce the maintenance overhead. However, most prior work can only deal with batch source data updates. In this paper, we provide a solution strategy that is capable of batching both source data updates and schema changes. We propose techniques to first preprocess the initial source updates to summarize delta changes for each source. We then design a view adaptation algorithm to adapt the warehouse view under these delta changes. We have implemented our solutions and incorporated into an existing data warehouse prototype system. The experimental studies demonstrate excellent performance achievable by our batch techniques.