Chapter

Advances in Conceptual Modeling - Challenging Perspectives

Volume 5833 of the series Lecture Notes in Computer Science pp 85-94

Toward Formal Semantics for Data and Schema Evolution in Data Stream Management Systems

  • Rafael J. Fernández-MoctezumaAffiliated withDepartment of Computer Science, Portland State University
  • , James F. TerwilligerAffiliated withMicrosoft Research
  • , Lois M. L. DelcambreAffiliated withDepartment of Computer Science, Portland State University
  • , David MaierAffiliated withDepartment of Computer Science, Portland State University

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Abstract

Data Stream Management Systems (DSMSs) do not statically respond to issued queries — 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 continuous query processing is currently unaddressed. In this work we address evolution in DSMSs by proposing semantics for three evolution primitives: Add Attribute and Drop Attribute (schema evolution), and Alter Data (data evolution). We characterize how a subset of commonly used query operators in a DSMS act on and propagate these primitives.