Publikation: Frames : Data-driven Windows
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2016
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Proceedings of the 10th ACM International Conference on Distributed and Event-Based Systems (DEBS). New York, NY: ACM, 2016, pp. 13-24. ISBN 978-1-4503-4021-2. Available under: doi: 10.1145/2933267.2933304
Zusammenfassung
Traditional Data Stream Management Systems (DSMS) segment data streams using windows that are defined either by a time interval or a number of tuples. Such windows are fixed—the definition unvarying over the course of a stream—and are defined based on external properties unrelated to the data content of the stream. However, streams and their con- tent do vary over time—the rate of a data stream may vary or the data distribution of the content may vary. The mismatch between a fixed stream segmentation and a variable stream motivates the need for a more flexible, expressive and physically independent stream segmentation. We introduce a new stream segmentation technique, called frames. Frames segment streams based on data content. We present a theory and implementation of frames and show the utility of frames for a variety of applications.
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004 Informatik
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data streams, stream processing, stream segmentation
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10th ACM International Conference on Distributed and Event-Based Systems, 20. Juni 2016 - 24. Juni 2016, Irvine, CA, USA
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GROSSNIKLAUS, Michael, David MAIER, James MILLER, Sharmadha MOORTHY, Kristin TUFTE, 2016. Frames : Data-driven Windows. 10th ACM International Conference on Distributed and Event-Based Systems. Irvine, CA, USA, 20. Juni 2016 - 24. Juni 2016. In: Proceedings of the 10th ACM International Conference on Distributed and Event-Based Systems (DEBS). New York, NY: ACM, 2016, pp. 13-24. ISBN 978-1-4503-4021-2. Available under: doi: 10.1145/2933267.2933304BibTex
@inproceedings{Grossniklaus2016Frame-33848,
year={2016},
doi={10.1145/2933267.2933304},
title={Frames : Data-driven Windows},
isbn={978-1-4503-4021-2},
publisher={ACM},
address={New York, NY},
booktitle={Proceedings of the 10th ACM International Conference on Distributed and Event-Based Systems (DEBS)},
pages={13--24},
author={Grossniklaus, Michael and Maier, David and Miller, James and Moorthy, Sharmadha and Tufte, Kristin}
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