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High-volume, high-speed data streams may overwhelm the capabilities of streamprocessing systems; techniques such as data prioritization, avoidance ofunnecessary processing and on-demand result production may be necessary toreduce processing requirements. However, the dynamic nature of data streams, interms of both rate and content, makes the application of such techniqueschallenging. Such techniques have been addressed in the context of static andcentralized query optimization; however, they have not been fully addressed fordata stream management systems. In this work, we present a comprehensiveframework that supports prioritization, avoidance of unnecessary work, andon-demand result production over distributed, unreliable, bursty, disordereddata sources, typical of many data streams. We propose a form of inter-operatorfeedback, which flows against the stream direction, to communicate theinformation needed to enable execution of these techniques. This feedbackleverages punctuations to describe the subsets of interest. We identifypotential sources of feedback information, characterize new types ofpunctuation to support feedback, and describe the roles of producers,exploiters, and relayers of feedback that query operators may implement. Wepresent initial experimental observations using the NiagaraST data-streamsystem.

Inter-Operator Feedback in Data Stream Management Systems via Punctuation