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

Yuzhe Tang; Ling Liu; Junichi Tatemura; Hakan Hacigumus

doi:10.1109/ICDCSW.2015.32

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/Entry/Poem › Conference 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 language	English (US)
Title of host publication	Proceedings - 2015 IEEE 35th International Conference on Distributed Computing Systems Workshops, ICDCSW 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	136-141
Number of pages	6
ISBN (Electronic)	9781467373036
DOIs	https://doi.org/10.1109/ICDCSW.2015.32
State	Published - Jul 22 2015
Event	2015 35th IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2015 - Columbus, United States Duration: Jun 29 2015 → Jul 2 2015

Publication series

Name	Proceedings - 2015 IEEE 35th International Conference on Distributed Computing Systems Workshops, ICDCSW 2015

Other

Other	2015 35th IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2015
Country/Territory	United States
City	Columbus
Period	6/29/15 → 7/2/15

ASJC Scopus subject areas

Computer Networks and Communications
Control and Systems Engineering

Access to Document

10.1109/ICDCSW.2015.32

Cite this

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). Article 7165096 (Proceedings - 2015 IEEE 35th International Conference on Distributed Computing Systems Workshops, ICDCSW 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDCSW.2015.32

KTV-tree: Interactive top-K aggregation on dynamic large dataset in the cloud. / Tang, Yuzhe; Liu, Ling; Tatemura, Junichi et al.
Proceedings - 2015 IEEE 35th International Conference on Distributed Computing Systems Workshops, ICDCSW 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 136-141 7165096 (Proceedings - 2015 IEEE 35th International Conference on Distributed Computing Systems Workshops, ICDCSW 2015).

Research output: Chapter in Book/Entry/Poem › Conference contribution

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., 7165096, Proceedings - 2015 IEEE 35th International Conference on Distributed Computing Systems Workshops, ICDCSW 2015, Institute of Electrical and Electronics Engineers Inc., pp. 136-141, 2015 35th IEEE International Conference on Distributed Computing Systems Workshops, ICDCSW 2015, Columbus, United States, 6/29/15. https://doi.org/10.1109/ICDCSW.2015.32

Tang Y, Liu L, Tatemura J, Hacigumus H. 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. Institute of Electrical and Electronics Engineers Inc. 2015. p. 136-141. 7165096. (Proceedings - 2015 IEEE 35th International Conference on Distributed Computing Systems Workshops, ICDCSW 2015). doi: 10.1109/ICDCSW.2015.32

Tang, Yuzhe ; Liu, Ling ; Tatemura, Junichi et al. / KTV-tree : Interactive top-K aggregation on dynamic large dataset in the cloud. Proceedings - 2015 IEEE 35th International Conference on Distributed Computing Systems Workshops, ICDCSW 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 136-141 (Proceedings - 2015 IEEE 35th International Conference on Distributed Computing Systems Workshops, ICDCSW 2015).

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AB - 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.

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

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