Maintaining consistent results of continuous queries under diverse window specifications

Patroumpas, K; Sellis, T

dc.contributor.author	Patroumpas, K	en
dc.contributor.author	Sellis, T	en
dc.date.accessioned	2014-03-01T02:47:24Z
dc.date.available	2014-03-01T02:47:24Z
dc.date.issued	2011	en
dc.identifier.issn	0306-4379	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/33123
dc.subject	Continuous queries	en
dc.subject	Data streams	en
dc.subject	Monotonic-related patterns	en
dc.subject	Windows	en
dc.subject.classification	Computer Science, Information Systems	en
dc.subject.other	Algebraic expression	en
dc.subject.other	Arrival rates	en
dc.subject.other	Continuous queries	en
dc.subject.other	Data sets	en
dc.subject.other	Data stream	en
dc.subject.other	Formal foundation	en
dc.subject.other	Monotonic-related patterns	en
dc.subject.other	Potential benefits	en
dc.subject.other	Query optimization	en
dc.subject.other	Sliding Window	en
dc.subject.other	Stream processing	en
dc.subject.other	Update patterns	en
dc.subject.other	Hydraulics	en
dc.subject.other	Specifications	en
dc.subject.other	XML	en
dc.subject.other	Data communication systems	en
dc.title	Maintaining consistent results of continuous queries under diverse window specifications	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1016/j.is.2010.02.001	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.is.2010.02.001	en
heal.language	English	en
heal.publicationDate	2011	en
heal.abstract	Continuous queries applied over nonterminating data streams usually specify windows in order to obtain an evolving-yet restricted-set of tuples and thus provide timely and incremental results. Although sliding windows get frequently employed in many user requests, additional types like partitioned or landmark windows are also available in stream processing engines. In this paper, we set out to study the existence of monotonic-related semantics for a rich set of windowing constructs in order to facilitate a more efficient maintenance of their changing contents. After laying out a formal foundation for expressing windowed queries, we investigate update patterns observed in most common window variants as well as their impact on adaptations of typical operators (like windowed join, union or aggregation), thus offering more insight towards design and implementation of stream processing mechanisms. Furthermore, we identify syntactic equivalences in algebraic expressions involving windows, to the potential benefit of query optimizations. Finally, this framework is validated for several windowed operations against streaming datasets with simulations at diverse arrival rates and window specifications, providing concrete evidence of its significance. (C) 2010 Elsevier B.V. All rights reserved.	en
heal.publisher	PERGAMON-ELSEVIER SCIENCE LTD	en
heal.journalName	Information Systems	en
dc.identifier.doi	10.1016/j.is.2010.02.001	en
dc.identifier.isi	ISI:000283906900004	en
dc.identifier.volume	36	en
dc.identifier.issue	1	en
dc.identifier.spage	42	en
dc.identifier.epage	61	en