R and Hadoop Integrated Programming Environment. In Divide and Recombine (D&R), big data are divided into subsets in one or more ways, forming divisions. Analytic methods, numeric-categorical methods of machine learning and statistics plus visualization methods, are applied to each of the subsets of a division. Then the subset outputs for each method are recombined. D&R methods of division and recombination seek to make the statistical accuracy of recombinations as large as possible, ideally close to that of the hypothetical direct, all-data application of the methods. The D&R computational environment starts with RHIPE, a merger of R and Hadoop. RHIPE allows an analyst to carry out D&R analysis of big data wholly from within R, and use any of the thousands of methods available in R.
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