ACM Transactions on Database Systems (TODS)
Continuous queries over data streams
Continuous queries over data streams
Monitoring streams: a new class of data management applications
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Towards a streaming SQL standard
Proceedings of the VLDB Endowment
Rule-based multi-query optimization
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Window Update Patterns in Stream Operators
ADBIS '09 Proceedings of the 13th East European Conference on Advances in Databases and Information Systems
Window specification over data streams
EDBT'06 Proceedings of the 2006 international conference on Current Trends in Database Technology
Revisiting formal ordering in data stream querying
Proceedings of the 27th Annual ACM Symposium on Applied Computing
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Querying streams of data from the sensors or other devices requires several operators. One of the most important operators is called Windowing. Creating windows consists in grouping of tuples from data streams at a specific rate according to a certain pattern. A large variety of window patterns exist and reflect different data management semantics that are useful for different purposes. Prior arts mainly focused on simple windows, like landmark and sliding windows, and only a few properties were considered in the case of query rewriting. This paper goes one step forward by proposing an algebraic model for generic windows. Our proposed model supports temporal, positional and cross-domain windows. Window's creation time can be specified by a complex function. This proposal subsumes most popular system formalizations and extends the possibilities of window management. This paper also demonstrates associativity and transposition properties useful for algebraic rewriting in query optimization. The implementation of this model is briefly presented.