KTV-tree: Interactive top-K aggregation on dynamic large dataset in the cloud

Yuzhe Tang, Ling Liu, Junichi Tatemura, Hakan Hacigumus

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

1 Scopus citations

Abstract

This paper studies the problem of supporting interactive top-kaggregation query over dynamic data in the cloud. We propose TV-TREE, a top-K Threshold-based materialized View TREE, which achieves the fast processing of top-k aggregation queries by efficiently materialized views. A segment tree based structure is adopted to organize the views in a hierarchical manner. A suite of protocols are proposed for incrementally maintaining the views. Experiments are performed for evaluating the effectiveness of our solutions, in terms of query accuracy, costs and maintenance overhead.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE 35th International Conference on Distributed Computing Systems Workshops, ICDCSW 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages136-141
Number of pages6
ISBN (Print)9781467373036
DOIs
StatePublished - Jul 22 2015
Event2015 35th IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2015 - Columbus, United States
Duration: Jun 29 2015Jul 2 2015

Other

Other2015 35th IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2015
CountryUnited States
CityColumbus
Period6/29/157/2/15

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Control and Systems Engineering

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    Tang, Y., Liu, L., Tatemura, J., & Hacigumus, H. (2015). KTV-tree: Interactive top-K aggregation on dynamic large dataset in the cloud. In Proceedings - 2015 IEEE 35th International Conference on Distributed Computing Systems Workshops, ICDCSW 2015 (pp. 136-141). [7165096] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDCSW.2015.32