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The integration of data, especially from heterogeneous sources, is a hard and widely studied problem. One particularly challenging issue is the integration of sources that are semantically equivalent but schematically heterogeneous. While two such data sources may represent the same information, one may store the information inside tuples (data) while the other may store it in attribute or relation names (schema). The SchemaSQL query language is a recent solution to this problem powerful enough to restructure such sources into each other without the loss of information. In this paper, we propose the first incremental view maintenance strategy for such schema-restructuring views. Our strategy, based on an algebraic representation of the view query, correctly transforms a data update or a schema change to a source into sequences of schema and data updates to be applied to the view. We also introduce an optimization of incremental maintenance using batching. We present a proof of correctness of the propagation approach. We also describe the implementation of our SchemaSQL Query Processor and View Maintainer. Last, our experimental results demonstrate that, in many cases, incremental SchemaSQL view maintenance is significantly faster than complete view recomputation.
Heterogeneous databases, materialized views, SchemaSQL, incremental view maintenance, schema restructuring.

A. Koeller and E. A. Rundensteiner, "Incremental Maintenance of Schema-Restructuring Views in SchemaSQL," in IEEE Transactions on Knowledge & Data Engineering, vol. 16, no. , pp. 1096-1111, 2004.
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