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Contribution Details

Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings Yes
Title Supporting Set Operations in Temporal-Probabilistic Databases
Organization Unit
Authors
  • Katerina Papaioannou
  • Martin Theobald
  • Michael Böhlen
Presentation Type paper
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
Page Range 1180 - 1191
Event Title 34th IEEE International Conference on Data Engineering, ICDE 2018
Event Type conference
Event Location Paris, France
Event Start Date April 16 - 2018
Event End Date April 19 - 2018
Publisher IEEE
Abstract Text In temporal-probabilistic (TP) databases, the combination of the temporal and the probabilistic dimension adds significant overhead to the computation of set operations. Although set queries are guaranteed to yield linearly sized output relations, all of the existing solutions exhibit a quadratic runtime complexity. They suffer from redundant interval comparisons and additional joins for the formation of lineage expressions. In this paper, we formally define TP set operations and study their properties. For their efficient computation, we introduce the lineage-aware temporal window, a mechanism that binds intervals with lineage expressions. We suggest the lineage-aware window advancer (LAWA) for producing lineage-aware temporal windows, which enable direct filtering of irrelevant intervals and finalization of output lineage expressions. This way, we compute TP set operations in linearithmic time. A series of experiments over both synthetic and real-world datasets show that (a) our approach has predictable performance, which depends only on the size of the input relations and not on the number of time intervals per fact or the overlap of the time intervals, and that (b) it outperforms state-of-the-art approaches.
Official URL http://orbilu.uni.lu/bitstream/10993/37837/1/377_ICDE2018.pdf
Digital Object Identifier 10.1109/ICDE.2018.00109
Other Identification Number merlin-id:16908
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