This article was written by John Mount. Introduction In this note we will show how to speed up work in R by partitioning data and process-level parallelization. We will show the technique with three different R packages: rqdatatable, data.table, and dplyr. The methods shown will also work with base-R and other packages. For each of the above packages we speed up work by using wrapr::execute_par…
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