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Unlike DataBase Management Systems (DBMSs), Data Stream Management Systems (DSMSs) do not evaluate queries over static data sets - rather, they continuously produce result streams to standing queries, and often operate in a context where any interruption can lead to data loss. Support for schema evolution in such an environment is currently unaddressed. In this paper, the authors address evolution in DSMSs by introducing a new element to streams, called an accent that precedes and describes an evolution. They characterize how a subset of commonly used query operators in DSMS act on and propagate accents with respect to three evolution primitives: add attribute, drop attribute, and alter data.
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