Efficient query evaluation on probabilistic databases
The VLDB Journal — The International Journal on Very Large Data Bases
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Proceedings of the VLDB Endowment
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Evolving data has attracted considerable research attention. Researchers have focused on modeling and querying of schema/instance-level structural changes, such as, insertion, deletion and modification of attributes. Databases with such a functionality are known as temporal databases. A limitation of the temporal databases is that they treat changes as independent events, while often the appearance (or elimination) of some structure in the database is the result of an evolution of some existing structure. We claim that maintaining the causal relationship between the two structures is of major importance since it allows additional reasoning to be performed and answers to be generated for queries that previously had no answers. We present the TrenDS, a system for exploiting the evolution relationships between the structures in the database. In particular, our system combines different structures that are associated through evolution relationships into virtual structures to be used during query answering. The virtual structures define ``possible'' database instances, in a fashion similar to the possible worlds in the probabilistic databases. TrenDS uses a query answering mechanism that allows queries to be answered over these possible databases without materializing them. Evaluation of such queries raises many technical challenges, since it requires the discovery of Steiner forests on the evolution graphs.