Support for Schema Evolution in Data Stream Management Systems

Unlike database management systems (dbmss), data stream manage- ment 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 work we address evolution in dsmss by introducing a new element to streams, called an accent, that precedes and describes an evolution. we 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.