Smart scheme: an efficient query execution scheme for event-driven stream processing.
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| Title: | Smart scheme: an efficient query execution scheme for event-driven stream processing. |
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| Authors: | Shaikh, Salman Ahmed1 salman@kde.cs.tsukuba.ac.jp, Watanabe, Yousuke2 watanabe@coi.nagoya-u.ac.jp, Wang, Yan3 wangyan@kde.cs.tsukuba.ac.jp, Kitagawa, Hiroyuki1 kitagawa@cs.tsukuba.ac.jp |
| Source: | Knowledge & Information Systems. Feb2019, Vol. 58 Issue 2, p341-370. 30p. |
| Subjects: | Event driven systems (Computer science), Querying (Computer science), Streaming technology, Electrochromic windows, Mathematical optimization |
| 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. [ABSTRACT FROM AUTHOR] |
| Copyright of Knowledge & Information Systems is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Items | – Name: Title Label: Title Group: Ti Data: Smart scheme: an efficient query execution scheme for event-driven stream processing. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Shaikh%2C+Salman+Ahmed%22">Shaikh, Salman Ahmed</searchLink><relatesTo>1</relatesTo><i> salman@kde.cs.tsukuba.ac.jp</i><br /><searchLink fieldCode="AR" term="%22Watanabe%2C+Yousuke%22">Watanabe, Yousuke</searchLink><relatesTo>2</relatesTo><i> watanabe@coi.nagoya-u.ac.jp</i><br /><searchLink fieldCode="AR" term="%22Wang%2C+Yan%22">Wang, Yan</searchLink><relatesTo>3</relatesTo><i> wangyan@kde.cs.tsukuba.ac.jp</i><br /><searchLink fieldCode="AR" term="%22Kitagawa%2C+Hiroyuki%22">Kitagawa, Hiroyuki</searchLink><relatesTo>1</relatesTo><i> kitagawa@cs.tsukuba.ac.jp</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Knowledge+%26+Information+Systems%22">Knowledge & Information Systems</searchLink>. Feb2019, Vol. 58 Issue 2, p341-370. 30p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Event+driven+systems+%28Computer+science%29%22">Event driven systems (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Querying+%28Computer+science%29%22">Querying (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Streaming+technology%22">Streaming technology</searchLink><br /><searchLink fieldCode="DE" term="%22Electrochromic+windows%22">Electrochromic windows</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: 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. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Knowledge & Information Systems is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10115-018-1195-9 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 30 StartPage: 341 Subjects: – SubjectFull: Event driven systems (Computer science) Type: general – SubjectFull: Querying (Computer science) Type: general – SubjectFull: Streaming technology Type: general – SubjectFull: Electrochromic windows Type: general – SubjectFull: Mathematical optimization Type: general Titles: – TitleFull: Smart scheme: an efficient query execution scheme for event-driven stream processing. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Shaikh, Salman Ahmed – PersonEntity: Name: NameFull: Watanabe, Yousuke – PersonEntity: Name: NameFull: Wang, Yan – PersonEntity: Name: NameFull: Kitagawa, Hiroyuki IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2019 Type: published Y: 2019 Identifiers: – Type: issn-print Value: 02191377 Numbering: – Type: volume Value: 58 – Type: issue Value: 2 Titles: – TitleFull: Knowledge & Information Systems Type: main |
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