Is it correct to say that any statistical learning algorithm (linear/logistic regression, SVM, neural network, random forest) can be implemented inside a Map Reduce framework?  Or are there restrictions?I guess there may be some algorithms that is not possible to parallelize?
Can all statistical algorithms be parallelized using a Map Reduce framework
machine learning;apache hadoop;map reduce
Indeed there are:Gradient Boosting is by construction sequential, so parallelization is not really possibleGeneralized Linear Models need all data at the same time, although technically you can parallelize some of the inner linear algebra nuts and boltsSupport Vector Machines