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Author, Editor(s)

Author(s):

Neumann, Thomas
Bender, Matthias
Michel, Sebastian
Schenkel, Ralf
Triantafillou, Peter
Weikum, Gerhard

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Not MPG Author(s):

Michel, Sebastian
Triantafillou, Peter

BibTeX cite key*:

Neumann_DAPD09

Title

Title*:

Distributed Top-k aggregation queries at large

Journal

Journal Title*:

Distributed and Parallel Databases

Journal's URL:

http://www.springerlink.com/content/100257/

Download URL
for the article:

http://www.springerlink.com/content/27522320774lj282/fulltext.pdf

Language:

English

Publisher

Publisher's
Name:

Springer

Publisher's URL:


Publisher's
Address:

Berlin, Germany

ISSN:

0926-8782

Vol, No, pp, Date

Volume*:

26

Number:

1

Publishing Date:

August 2009

Pages*:

3-27

Number of
VG Pages:


Page Start:

3

Page End:

27

Sequence Number:


DOI:

10.1007/s10619-009-7041-z

Note, Abstract, ©

Note:

accepted June 4, 2009; published online June 18, 2009

(LaTeX) Abstract:

Top-$k$ query processing is a fundamental building block for efficient ranking in a large number of applications. Efficiency is a central issue, especially for distributed settings, when the data is spread across different nodes in a network. This paper introduces novel optimization methods for top-$k$ aggregation queries in such distributed environments. The optimizations can be applied to all algorithms that fall into the frameworks of the prior TPUT and KLEE methods. The optimizations address three degrees of freedom: 1) hierarchically
grouping input lists into top-$k$ operator trees and optimizing the tree structure, 2) computing data-adaptive scan depths for different input sources, and 3) data-adaptive sampling of a small subset of input sources in scenarios with hundreds or thousands of query-relevant network nodes. All optimizations are based on a statistical cost model that utilizes local synopses, e.g., in the form of histograms, efficiently computed convolutions, and estimators based on order statistics. The paper presents comprehensive experiments, with three different real-life datasets and using the ns-2 network simulator for
a packet-level simulation of a large Internet-style network.

URL for the Abstract:


Categories,
Keywords:


HyperLinks / References / URLs:


Copyright Message:


Personal Comments:


Download
Access Level:

Public

Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Databases and Information Systems Group

Appearance:

MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort


BibTeX Entry:

@ARTICLE{Neumann_DAPD09,
AUTHOR = {Neumann, Thomas and Bender, Matthias and Michel, Sebastian and Schenkel, Ralf and Triantafillou, Peter and Weikum, Gerhard},
TITLE = {Distributed Top-k aggregation queries at large},
JOURNAL = {Distributed and Parallel Databases},
PUBLISHER = {Springer},
YEAR = {2009},
NUMBER = {1},
VOLUME = {26},
PAGES = {3--27},
ADDRESS = {Berlin, Germany},
MONTH = {August},
ISBN = {0926-8782},
DOI = {10.1007/s10619-009-7041-z},
NOTE = {accepted June 4, 2009; published online June 18, 2009},
}


Entry last modified by Anja Becker, 03/23/2010
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Editor(s)
[Library]
Created
06/04/2009 11:03:54 AM
Revisions
3.
2.
1.
0.
Editor(s)
Anja Becker
Ralf Schenkel
Ralf Schenkel
Ralf Schenkel
Edit Dates
23.03.2010 12:01:51
29.07.2009 17:10:39
24.06.2009 14:52:26
04.06.2009 11:07:17
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