Parallel sorted neighborhood blocking with MapeReduce
dc.contributor.author | Kolb, Lars | |
dc.contributor.author | Thor, Andreas | |
dc.contributor.author | Rahm, Erhard | |
dc.contributor.editor | Härder, Theo | |
dc.contributor.editor | Lehner, Wolfgang | |
dc.contributor.editor | Mitschang, Bernhard | |
dc.contributor.editor | Schöning, Harald | |
dc.contributor.editor | Schwarz, Holger | |
dc.date.accessioned | 2019-01-17T10:36:48Z | |
dc.date.available | 2019-01-17T10:36:48Z | |
dc.date.issued | 2011 | |
dc.description.abstract | 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. | en |
dc.identifier.isbn | 978-3-88579-274-1 | |
dc.identifier.pissn | 1617-5468 | |
dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/19619 | |
dc.language.iso | en | |
dc.publisher | Gesellschaft für Informatik e.V. | |
dc.relation.ispartof | Datenbanksysteme für Business, Technologie und Web (BTW) | |
dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-180 | |
dc.title | Parallel sorted neighborhood blocking with MapeReduce | en |
dc.type | Text/Conference Paper | |
gi.citation.endPage | 64 | |
gi.citation.publisherPlace | Bonn | |
gi.citation.startPage | 45 | |
gi.conference.date | 02.-04.03.2011 | |
gi.conference.location | Kaiserslautern | |
gi.conference.sessiontitle | Regular Research Papers |
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