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

Authors:
Rafael J. Fernández-Moctezuma;James F. Terwilliger;Lois M. Delcambre;David Maier
Affiliations:
Department of Computer Science, Portland State University, Portland, USA 97207;Microsoft Research, Redmond, USA 98052;Department of Computer Science, Portland State University, Portland, USA 97207;Department of Computer Science, Portland State University, Portland, USA 97207
Venue:
ER '09 Proceedings of the ER 2009 Workshops (CoMoL, ETheCoM, FP-UML, MOST-ONISW, QoIS, RIGiM, SeCoGIS) on Advances in Conceptual Modeling - Challenging Perspectives
Year:
2009

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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.