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Course Details

Course Outline
Learning Outcomes
Materials
Prior Knowledge

Course Outline

Hardware: a brief overview of CPU, memory sizes and RAM. The benefit of switching to the cloud.
Rcpp: leveraging C++ for slow operations.
Tips and tricks for visualising big data sets.
The remainder of the course will consider three classes of data sets:
- Large in-memory data sets: the {dplyr} package.
- Out of memory: ff and the big memory suite of packages.
- Distributed datasets: using Spark and sparklyr.

Participants are encouraged to bring their own datasets and associated problems to this event.

Learning Outcomes

By the end of the day participants will be able to…

understand the different methods of dealing with big data
understand which method(s) apply to their problem
be able to apply said method to their own data using R’s interface to C coding, spark and other tools

Materials

Prior Knowledge

It is expected that participants have previous R experience, in particular, they are familiar with the topics in the Introduction to R and Programming with R courses.

Training Course Details

R for Big Data

Course Level: Advanced