Introduction to Spark with sparklyr in R

Learn how to analyze huge datasets using Apache Spark and R using the sparklyr package.

Start Course for Free
4 Hours4 Videos50 Exercises16,631 Learners
4600 XP

Create Your Free Account

GoogleLinkedInFacebook

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA. You confirm you are at least 16 years old (13 if you are an authorized Classrooms user).

Loved by learners at thousands of companies


Course Description

R is mostly optimized to help you write data analysis code quickly and readably. Apache Spark is designed to analyze huge datasets quickly. The <code>sparklyr</code> package lets you write <code>dplyr</code> 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 <code>dplyr</code> interface and the native interface to Spark, as well as trying machine learning techniques. Throughout the course, you'll explore the Million Song Dataset.

  1. 1

    Light My Fire: Starting To Use Spark With dplyr Syntax

    Free

    In which you 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.

    Play Chapter Now
    Getting started
    50 xp
    Made for each other
    50 xp
    Here be dragons
    50 xp
    The connect-work-disconnect pattern
    100 xp
    Copying data into Spark
    100 xp
    Big data, tiny tibble
    100 xp
    Exploring the structure of tibbles
    100 xp
    Selecting columns
    100 xp
    Filtering rows
    100 xp
    Arranging rows
    100 xp
    Mutating columns
    100 xp
    Summarizing columns
    100 xp

In the following tracks

Big DataMachine Learning Scientist

Collaborators

Tom Jeon

Prerequisites

Intermediate R
Richie Cotton Headshot

Richie Cotton

Curriculum Architect at DataCamp

Richie is a Learning Solutions Architect at DataCamp. He has been using R since 2004, in the fields of proteomics, debt collection, and chemical health and safety. He has released almost 30 R packages on CRAN and Bioconductor – most famously the assertive suite of packages – as well as creating and contributing to many others. He also has written two books on R programming, Learning R and Testing R Code.
See More

What do other learners have to say?

I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

Devon Edwards Joseph
Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

Louis Maiden
Harvard Business School

DataCamp is by far my favorite website to learn from.

Ronald Bowers
Decision Science Analytics, USAA