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  KLEE: A Framework for Distributed Top-k Query Algorithms

Michel, S., Triantafillou, P., & Weikum, G. (2005). KLEE: A Framework for Distributed Top-k Query Algorithms. In Proceedings of the 31st International Conference on Very Large Data Bases (VLDB 2005) (pp. 637-648). New York, USA: ACM.

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 Creators:
Michel, Sebastian1, Author           
Triantafillou, Peter1, Author           
Weikum, Gerhard1, Author           
Böhm, Klemens, Editor
Jensen, Christian S., Editor
Haas, Laura M., Editor
Kersten, Martin L., Editor
Larson, Per-{\AA}ke, Editor
Ooi, Beng Chin, Editor
Affiliations:
1Databases and Information Systems, MPI for Informatics, Max Planck Society, ou_24018              

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 Abstract: This paper addresses the efficient processing of top-k queries in wide-area distributed data repositories where the index lists for the attribute values (or text terms) of a query are distributed across a number of data peers and the computational costs include network latency, bandwidth consumption, and local peer work. We present KLEE, a novel algorithmic framework for distributed top-k queries, designed for high performance and flexibility. KLEE makes a strong case for approximate top-k algorithms over widely distributed data sources. It shows how great gains in efficiency can be enjoyed at low result-quality penalties. Further, KLEE affords the query-initiating peer the flexibility to trade-off result quality and expected performance and to trade-off the number of communication phases engaged during query execution versus network bandwidth performance. We have implemented KLEE and related algorithms and conducted a comprehensive performance evaluation. Our evaluation employed real-world and synthetic large, web-data collections, and query benchmarks. Our experimental results show that KLEE can achieve major performance gains in terms of network bandwidth, query response times, and much lighter peer loads, all with small errors in result precision and other result-quality measures.

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Language(s): eng - English
 Dates: 2006-06-142005
 Publication Status: Issued
 Pages: -
 Publishing info: New York, USA : ACM
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 278909
Other: Local-ID: C1256DBF005F876D-3FB7AE2E062D3889C1257015004C2279-MichelTW05
 Degree: -

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Title: Untitled Event
Place of Event: Trondheim, Norway
Start-/End Date: 2005-08-30

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Title: Proceedings of the 31st International Conference on Very Large Data Bases (VLDB 2005)
Source Genre: Proceedings
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Publ. Info: New York, USA : ACM
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 637 - 648 Identifier: ISBN: 1-59593-154-6