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Parallel Sorted Neighborhood Blocking with MapReduce


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Kolb, L.; Thor, A.; Rahm, E.
Parallel Sorted Neighborhood Blocking with MapReduce
Proc. 14th GI-Fachtagung für Datenbanksysteme in Business, Technologie und Web (BTW), 2011


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.



  • MapReduce, Hadoop
  • Entity Resolution, Object matching, Similarity Join, Pair-wise comparison
  • Blocking, Sliding Window, Sorted Neighborhood


  author    = {Lars Kolb and
               Andreas Thor and
               Erhard Rahm},
  title     = {{Parallel Sorted Neighborhood Blocking with MapReduce}},
  booktitle = {BTW},
  year      = {2011},
  pages     = {45-64},
  crossref  = {DBLP:conf/btw/2011},
  bibsource = {DBLP,}