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Adaptive Stream Processing

  • Living reference work entry
  • First Online:
Encyclopedia of Database Systems

  • 111 Accesses

Synonyms

Adaptive query processing

Definition

When querying long-lived data streams, the characteristics of the data may change over time or data may arrive in bursts – hence, the traditional model of optimizing a query prior to executing it is insufficient. As a result, most data stream management systems employ feedback-driven adaptive stream processing, which continuously re-optimizes the query execution plan based on data and stream properties, in order to meet certain performance or resource consumption goals. Adaptive stream processing is a special case of the more general problem of adaptive query processing, with the special property that intermediate results are bounded in size (by stream windows), but where query processing may have quality-of-service constraints.

Historical Background

The field of adaptive stream processing emerged in the early 2000s, as two separate developments converged. Adaptivetechniques for database query processing had become an area of increasing...

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Recommended Reading

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Author information

Authors and Affiliations

  1. Computer and Information Science Department, University of Pennsylvania, Philadelphia, PA, USA

    Zachary Ives

Authors
  1. Zachary Ives
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Corresponding author

Correspondence to Zachary Ives .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, Georgia, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, Ontario, Canada

    M. Tamer Özsu

Section Editor information

  1. Department of Computer Science, Brown University, Providence, RI, USA

    Ugur Cetintemel

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Ives, Z. (2017). Adaptive Stream Processing. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_11-2

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  • DOI: https://doi.org/10.1007/978-1-4899-7993-3_11-2

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  • Print ISBN: 978-1-4899-7993-3

  • Online ISBN: 978-1-4899-7993-3

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