  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.
