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Load Shedding

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

  • 165 Accesses

Definition

Data stream management systems may be subject to higher input rates than they can immediately process with their available system resources (e.g., CPU, memory). When input rates exceed the resource capacity, the system becomes overloaded and the query answers are delayed. Load shedding is a technique to remove excess load from the system in order to keep query processing up with the input arrival rates. As a result of load shedding, the system delivers approximate query answers with reduced latency.

Historical Background

Load shedding is a term that originally comes from electric power management, where it refers to the process of intentionally cutting off the electric current on certain lines when the demand for electricity exceeds the available supply, in order to save the electric grid from collapsing. The same term has also been used in computer networking to refer to a certain form of congestion control approach, where a network router drops packets when its buffers...

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Recommended Reading

  1. Amini L, Jain N, Sehgal A, Silber J, Verscheure O. Adaptive control of extreme-scale stream processing systems. In: Proceedings of the 23rd international conference on distributed computing systems. 2006.

    Google Scholar 

  2. Ayad A, Naughton JF. Static optimization of conjunctive queries with sliding windows over infinite streams. In: Proceedings ACM SIGMOD international conference on management of data. 2004.

    Google Scholar 

  3. Babcock B, Datar M, Motwani R. Load shedding for aggregation queries over data streams. In: Proceedings of the 20th international conference on data engineering. 2004.

    Google Scholar 

  4. Carney D, Çetintemel U, Cherniack M, Convey C, Lee S, Seidman G, Stonebraker M, Tatbul N, Zdonik S Monitoring streams – a new class of data management applications. In: Proceedings of the 28th international conference on very large databases. 2002.

    Google Scholar 

  5. Chandrasekaran S, Franklin MJ. Remembrance of streams past: overload-sensitive management of archived streams. In: Proceedings of the 30th international conference on very large data bases. 2004.

    Google Scholar 

  6. Chi Y, Yu PS, Wang H, Muntz RR Loadstar: a load shedding scheme for classifying data streams. In: Proceedings of the SIAM international conference on data mining. 2005.

    Google Scholar 

  7. Das A, Gehrke J, Riedewald M. Approximate join processing over data streams. In: Proceedings of the ACM SIGMOD international conference on management of data. 2003.

    Google Scholar 

  8. Gedik B, Wu K, Yu PS, Liu L. CPU load shedding for binary stream joins. Knowl Inf Syst. 2006;13(3):271–303.

    Article  Google Scholar 

  9. Jain A, Chang EY, Wang Y. Adaptive stream resource management using Kalman Filters. In: Proceedings of the ACM SIGMOD international conference on management of data. 2004.

    Google Scholar 

  10. Kang J, Naughton JF, Viglas S. Evaluating window joins over unbounded streams. In: Proceedings of the 19th international conference on data engineering. 2003.

    Google Scholar 

  11. Reiss F, Hellerstein JM. Data triage: an adaptive architecture for load shedding in TelegraphCQ. In: Proceedings of the 19th international conference on data engineering. 2005.

    Google Scholar 

  12. Srivastava U, Widom J. Memory limited execution of windowed stream joins. In: Proceedings of the 30th international conference on very large data bases. 2004.

    Google Scholar 

  13. Tatbul N, Çetintemel U, Zdonik S. Staying FIT: efficient load shedding techniques for distributed stream processing. In: Proceedings of the 33rd international conference on very large data bases. 2007.

    Google Scholar 

  14. Tatbul N, Çetintemel U, Zdonik S, Cherniack M, Stonebraker M. Load shedding in a data stream manager. In: Proceedings of the 29th international conference on very large data bases. 2003.

    Google Scholar 

  15. Tatbul N, Zdonik S. Window-aware load shedding for aggregation queries over data streams. In: Proceedings of the 32nd international conference on very large data bases. 2006.

    Google Scholar 

  16. Tu Y, Liu S, Prabhakar S, Yao B. Load shedding in stream databases: a control-based approach. In: Proceedings of the 32nd international conference on very large data bases. 2006.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Intel Labs and MIT, Cambridge, MA, USA

    Nesime Tatbul

Authors
  1. Nesime Tatbul
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Correspondence to Nesime Tatbul .

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. Brown University, Providence, RI, USA

    Uĝur Çetintemel

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© 2016 Springer Science+Business Media LLC

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Tatbul, N. (2016). Load Shedding. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_211-2

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  • DOI: https://doi.org/10.1007/978-1-4899-7993-3_211-2

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  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4899-7993-3

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