Run SparkR in local and cluster mode from an R project, setting environment variables and the library path, then reading JSON and CSV files.

Set up a two node Spark standalone cluster on VirtualBox Ubuntu guests, covering machine preparation, copying the VDI image and password-less SSH.

Wrap Python boto calls for Amazon S3 in an R package, rs3helper, where the Python scripts return JSON so R parses it as vectors and data frames.

Call a SOAP web service from Python with the suds library, a job R has no comprehensive client package for, demonstrated on the Sizmek MDX API.

Write Python in an object-oriented style, shown with SOAP API client classes, and a reading order for the Introducing Python book by chapter group.

Make caret results reproducible when a model trains in parallel on Windows or Linux, by setting the random seeds caret uses.

Turn an analysis into an R package, with the treebgg bagging package as the worked example, covering roxygen2 documents, testthat tests and vignettes.

Compare the snow and foreach approaches to parallel processing in R on three practical examples, starting with k-means clustering on the Boston data.

Loop in parallel on one machine in R with the foreach and doParallel packages, with the iterators package covered for writing the loop itself.

Run parallel tasks on one machine in R with the snow and parallel packages, comparing clusterApply, clusterApplyLB, parLapply and parLapplyLB.