Parallel sorted neighborhood blocking with MapeReduce

Zusammenfassung
Cloud infrastructures enable the efficient parallel execution of data-intensive tasks such as entity resolution on large datasets. We investigate challenges and possible solutions of using the MapReduce programming model for parallel entity resolution. In particular, we propose and evaluate two MapReduce-based implementations for Sorted Neighborhood blocking that either use multiple MapReduce jobs or apply a tailored data replication.
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  • BibTeX
Kolb, L., Thor, A. & Rahm, E., (2011). Parallel sorted neighborhood blocking with MapeReduce. In: Härder, T., Lehner, W., Mitschang, B., Schöning, H. & Schwarz, H. (Hrsg.), Datenbanksysteme für Business, Technologie und Web (BTW). Bonn: Gesellschaft für Informatik e.V.. (S. 45-64).
@inproceedings{mci/Kolb2011,
author = {Kolb, Lars AND Thor, Andreas AND Rahm, Erhard},
title = {Parallel sorted neighborhood blocking with MapeReduce},
booktitle = {Datenbanksysteme für Business, Technologie und Web (BTW)},
year = {2011},
editor = {Härder, Theo AND Lehner, Wolfgang AND Mitschang, Bernhard AND Schöning, Harald AND Schwarz, Holger} ,
pages = { 45-64 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
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Mehr Information

ISBN: 978-3-88579-274-1
ISSN: 1617-5468
Datum: 2011
Sprache: en (en)
Typ: Text/Conference Paper
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