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Smart scheme: an efficient query execution scheme for event-driven stream processing

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Abstract

With the increase in stream data, a demand for stream processing has become diverse and complicated. To meet this demand, several stream processing engines (SPEs) have been developed which execute continuous queries (CQs) to process continuous data streams. Event-driven stream processing, which is one of the important requirements, continuously gets the incoming stream data and, however, generates query results only on the occurrence of specified events. In the basic query execution scheme, even when no event is raised, input stream tuples are continuously processed by query operators, though they do not generate any query result. This results in increased system load and wastage of system resources. For this problem, we propose a smart event-driven stream processing scheme, which makes use of smart windows to buffer the stream tuples during the absence of an event. When the event is raised, the buffered tuples are flushed and processed by the downstream operators. If the buffered tuples in the smart window expire due to the window size before the occurrence of an event, they are deleted directly from the smart window. Since CQs once registered are executed for several weeks, months or even years, SPEs usually execute several CQs in parallel and merge their query plans whenever possible to save processing cost. Due to the presence of smart window, existing multi-query optimization techniques cannot work for smart event-driven stream processing. Hence, this work proposes a multi-query optimization for the proposed smart scheme to cover the cases where multiple continuous queries are registered. Extensive experiments are performed on real and synthetic data streams to show the effectiveness of the proposed smart scheme and its multi-query optimization.

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Notes

  1. https://zephoria.com/—accessed 01/21/2017.

  2. http://www.internetlivestats.com/—accessed 01/21/2017.

  3. http://www.internetlivestats.com/—accessed 01/21/2017.

  4. For simplicity, we assume that a new tuple arrives at every time instant t.

  5. Tsukuba mobility data stream is provided by Tsukuba city, National Institute for Land and Infrastructure Management and University of Tsukuba.

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Acknowledgements

This research was partly supported by the program “Research and Development on Real World Big Data Integration and Analysis” of the Ministry of Education, Culture, Sports, Science and Technology (MEXT) and RIKEN, Japan.

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Authors and Affiliations

  1. Center for Computational Sciences, University of Tsukuba, Tsukuba, Japan

    Salman Ahmed Shaikh & Hiroyuki Kitagawa

  2. Institute of Innovation for Future Society, Nagoya University, Nagoya, Japan

    Yousuke Watanabe

  3. Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Japan

    Yan Wang

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  1. Salman Ahmed Shaikh
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  2. Yousuke Watanabe
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  3. Yan Wang
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  4. Hiroyuki Kitagawa
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Correspondence to Salman Ahmed Shaikh.

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Shaikh, S.A., Watanabe, Y., Wang, Y. et al. Smart scheme: an efficient query execution scheme for event-driven stream processing. Knowl Inf Syst 58, 341–370 (2019). https://doi.org/10.1007/s10115-018-1195-9

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