Do you have friends in Århus.. Tell them about Rhus.club
This is a useR group for people near or far from Copenhagen. Everybody is welcome no matter your level or specific interests in the R language. We hope to create a group where people can share knowledge, learn and hopefully inspire and get inspired using R. According to KDNuggets R is the most popular language for analytics, data mining and data science. There are several reasons for this! R has a package for just about everything, you can create beautiful graphics and its statistical capabilities are top of the line. This is just the tip of the iceberg... Want to learn more? Join this group if you want to meet and connect with other R useRs.
Two exciting talks:
Easy peasy massive parallel computing in R
by Mikkel Krogsholm
Wouldn’t it be nice to be able to write simple R-code that very simply scales to massive parallel computing?
The future and the furrr package in R provides a framework that makes it possible for you to write code, that works seamlessly on your laptop or on a supercomputer. With these, R expressions can be evaluated on the local machine, in parallel a set of local machines, or distributed on a mix of local and remote machines.
There is no need to modify any code in order switch from sequential on the local machine to distributed processing on a remote compute cluster. Global variables and functions are also automatically identified and exported as needed, making it straightforward to tweak existing code to make use of futures.
This R-talk shows you how. We will run through a concrete example that we first execute on a local machine and then on a much more powerful server.
R at scale on the Google Cloud Platform
by Mark Edmonson
This talk covers my current thinking on what I consider the optimal way to work with R on the Google Cloud Platform (GCP). It seems this has developed into my niche, and I get questions about it so would like to be able to point to a URL.
Both R and the GCP rapidly evolve, so this will have to be updated I guess at some point in the future, but even as things stand now you can do some wonderful things with R, and can multiply those out to potentially billions of users with GCP. The only limit is ambition.
The common scenarios I want to cover are: Scaling a standalone R script and
Scaling Shiny apps and R APIs