Continuous monitoring of top-k queries over sliding windows

Kyriakos Mouratidis, Spiridon Bakiras, Dimitris Papadias

Research output: Chapter in Book/Report/Conference proceedingConference contribution

162 Citations (Scopus)

Abstract

Given a dataset P and a preference function f, a top-k query retrieves the k tuples in P with the highest scores according to f. Even though the problem is well-studied in conventional databases, the existing methods are inapplicable to highly dynamic environments involving numerous long-running queries. This paper studies continuous monitoring of top-k queries over a fixed-size window W of the most recent data. The window size can be expressed either in terms of the number of active tuples or time units. We propose a general methodology for top-k monitoring that restricts processing to the sub-domains of the workspace that influence the result of some query. To cope with high stream rates and provide fast answers in an on-line fashion, the data in W reside in main memory. The valid records are indexed by a grid structure, which also maintains book-keeping information. We present two processing techniques: the first one computes the new answer of a query whenever some of the current top-k points expire; the second one partially pre-computes the future changes in the result, achieving better running time at the expense of slightly higher space requirements. We analyze the performance of both algorithms and evaluate their efficiency through extensive experiments. Finally, we extend the proposed framework to other query types and a different data stream model.

Original languageEnglish
Title of host publicationSIGMOD 2006 - Proceedings of the ACM SIGMOD International Conference on Management of Data
Pages635-646
Number of pages12
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event2006 ACM SIGMOD International Conference on Management of Data - Chicago, IL, United States
Duration: 27 Jun 200629 Jun 2006

Other

Other2006 ACM SIGMOD International Conference on Management of Data
CountryUnited States
CityChicago, IL
Period27/6/0629/6/06

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Monitoring
Processing
Data storage equipment
Experiments

Keywords

  • Continuous queries
  • Sliding windows
  • Top-k processing

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Mouratidis, K., Bakiras, S., & Papadias, D. (2006). Continuous monitoring of top-k queries over sliding windows. In SIGMOD 2006 - Proceedings of the ACM SIGMOD International Conference on Management of Data (pp. 635-646) https://doi.org/10.1145/1142473.1142544

Continuous monitoring of top-k queries over sliding windows. / Mouratidis, Kyriakos; Bakiras, Spiridon; Papadias, Dimitris.

SIGMOD 2006 - Proceedings of the ACM SIGMOD International Conference on Management of Data. 2006. p. 635-646.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Mouratidis, K, Bakiras, S & Papadias, D 2006, Continuous monitoring of top-k queries over sliding windows. in SIGMOD 2006 - Proceedings of the ACM SIGMOD International Conference on Management of Data. pp. 635-646, 2006 ACM SIGMOD International Conference on Management of Data, Chicago, IL, United States, 27/6/06. https://doi.org/10.1145/1142473.1142544
Mouratidis K, Bakiras S, Papadias D. Continuous monitoring of top-k queries over sliding windows. In SIGMOD 2006 - Proceedings of the ACM SIGMOD International Conference on Management of Data. 2006. p. 635-646 https://doi.org/10.1145/1142473.1142544
Mouratidis, Kyriakos ; Bakiras, Spiridon ; Papadias, Dimitris. / Continuous monitoring of top-k queries over sliding windows. SIGMOD 2006 - Proceedings of the ACM SIGMOD International Conference on Management of Data. 2006. pp. 635-646
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