Lazy data structure maintenance for main-memory analytics over sliding windows

  • Authors:
  • Chang Ge;Lukasz Golab

  • Affiliations:
  • University of Waterloo, Waterloo, ON, Canada;University of Waterloo, Waterloo, ON, Canada

  • Venue:
  • Proceedings of the sixteenth international workshop on Data warehousing and OLAP
  • Year:
  • 2013

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Abstract

We address the problem of maintaining data structures used by memory-resident data warehouses that store sliding windows. We propose a framework that eagerly expires data from the sliding window to save space and/or satisfy data retention policies, but lazily maintains the associated data structures to reduce maintenance overhead. Using a dictionary as an example, we show that our framework enables maintenance algorithms that outperform existing approaches in terms of space overhead, maintenance overhead, and dictionary lookup overhead during query execution.