Processing sliding window multi-joins in continuous queries over data streams

  • Authors:
  • Lukasz Golab;M Tamer Özsu

  • Affiliations:
  • School of Computer Science, University of Waterloo, Waterloo, Canada;School of Computer Science, University of Waterloo, Waterloo, Canada

  • Venue:
  • VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
  • Year:
  • 2003

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Abstract

We study sliding window multi-join processing in continuous queries over data streams. Several algorithms are reported for performing continuous, incremental joins, under the assumption that all the sliding windows fit in main memory. The algorithms include multiway incremental nested loop joins (NLJs) and multi-way incremental hash joins. We also propose join ordering heuristics to minimize the processing cost per unit time. We test a possible implementation of these algorithms and show that, as expected, hash joins are faster than NLJs for performing equi-joins, and that the overall processing cost is influenced by the strategies used to remove expired tuples from the sliding windows.