New Course: Introduction to Spark in R using sparklyr

[This article was first published on DataCamp Community - r programming, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Hello R users! We have a big announcement this week as well, DataCamp just released our first Spark in R course: Introduction to Spark in R using sparklyr! This course is taught by Richie Cotton.

R is mostly optimized to help you write data analysis code quickly and readably. Apache Spark is designed to analyze huge datasets quickly. The sparklyr package lets you write dplyr R code that runs on a Spark cluster, giving you the best of both worlds. This course teaches you how to manipulate Spark DataFrames using both the dplyr interface and the native interface to Spark, as well as trying machine learning techniques. Throughout the course, you’ll explore the Million Song Dataset.


Take me to the first chapter! 


Introduction to Spark in R using sparklyr features interactive exercises that combine high-quality video, in-browser coding, and gamification for an engaging learning experience that will teach you how to work with Spark in R!


What you’ll learn:

Chapter 1 – Light My Fire: Starting To Use Spark With dplyr Syntax

Starting off you will learn how Spark and R complement each other, how to get data to and from Spark, and how to manipulate Spark data frames using dplyr syntax.

Chapter 2 – Tools of the Trade: Advanced dplyr Usage

In the second chapter, you will learn more about using the dplyr interface to Spark, including advanced field selection, calculating groupwise statistics, and joining data frames.

Chapter 3 – Going Native: Use The Native Interface to Manipulate Spark DataFrames

In chapter 3, you’ll learn about Spark’s machine learning data transformation features and functionality for manipulating native DataFrames.

Chapter 4 – Case Study: Learning to be a Machine: Running Machine Learning Models on Spark

The final chapter is a case study in which you learn to use sparklyr‘s machine learning routines, by predicting the year in which a song was released.


Start Learning Spark in R Today!

To leave a comment for the author, please follow the link and comment on their blog: DataCamp Community - r programming. offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)