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A Data-Descriptive Feedback Framework for Data Stream Management Systems
Author(s) -
Rafael Fernández Moctezuma
Publication year - 2000
Language(s) - English
Resource type - Reports
DOI - 10.15760/etd.116
Subject(s) - computer science , tuple , adaptation (eye) , stream processing , data stream mining , data stream , query plan , operator (biology) , state (computer science) , distributed computing , data mining , database , information retrieval , algorithm , search engine , sargable , telecommunications , biochemistry , chemistry , physics , mathematics , discrete mathematics , repressor , web search query , transcription factor , gene , optics
Data Stream Management Systems (DSMSs) provide support for continuous query evaluation over data streams. Data streams provide processing challenges due to their unbounded nature and varying characteristics, such as rate and density fluctuations. DSMSs need to adapt stream processing to these changes within certain constraints, such as available computational resources and minimum latency requirements in producing results. The proposed research develops an inter-operator feedback framework, where opportunities for run-time adaptation of stream processing are expressed in terms of descriptions of substreams and actions applicable to the substreams, called feedback punctuations. Both the discovery of adaptation opportunities and the exploitation of these opportunities are performed in the query operators. DSMSs are also concerned with state management, in particular, state derived from tuple processing. The proposed research also introduces the Contracts Framework, which provides execution guarantees about state purging in continuous query evaluation for systems with and without inter-operator feedback. This research provides both theoretical and design contributions. The research also includes an implementation and evaluation of the feedback techniques in the NiagaraST DSMS, and a reference implementation of the Contracts Framework.

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