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In Map-Reduce for Machine Learning on Multicore Chu et al describe "algorithms that fit the Statistical Query model can be written in a certain “summation form,” which allows them to be easily parallelized on multicore computers." They specifically implement 10 algorithms including e.g. weighted linear regression, k-Means, Naive Bayes, and SVM, using a map-reduce framework.
The Apache Mahout project has released a recent Hadoop (Java) implementation of some methods based on the ideas from this paper.
For problems requiring processing and generating large data sets. Say running an interest generation query over all accounts a bank hold. Say processing audit data for all transactions that happened in the past year in a bank. The best use case is from Google - generating search index for google search engine.