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This script is best run interactively to review its operation and to
ensure that the interaction with Azure completes.
A common use case is for a Data Scientist to create their R programs
to analyse a dataset on their local compute platform (e.g., a laptop
with 6GB RAM running Ubuntu with R installed). Development is
performed with a subset of the full dataset (a random sample) that
will not exceed the available memory and will return results
quickly. When the experimental setup is complete the script can be
sent across to a considerably more capable compute engine on Azure,
possibly a cluster of servers to build models in parallel.
This tutorial will deploy several Linux Data Science Virtual Machines
(DSVMs), distribute a copmute task over those servers, colelct the
results and generate a report, and then delete the compute
resources.
# Setup
To get started load our Azure credentials as well as the user's ssh