Course
Introduction to Spark with sparklyr in R
Create Your Free Account
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.Loved by learners at thousands of companies
Training 2 or more people?
Try DataCamp for BusinessCourse Description
Explore the Advantages of R, Spark, and sparklyr
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 4-hour 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.Load Data into Spark and Manipulate Spark DataFrames
You’ll start this Spark course by investigating how Spark and R work well together and practicing loading data, ready for cleaning, transformation, and analysis. You’ll use Spark frames and dplyr syntax to manipulate your data by filtering and arranging rows, and mutating and summarizing columns.Delve into Big Data Analysis with Spark MLib
This course focuses on building your skills and confidence in analyzing huge datasets. The final chapters take you through Spark’s machine learning data transformation features and offer you the chance to practice sparklyr’s machine learning routines by using it to make predictions using gradient boosted trees and random forests. "Prerequisites
Supervised Learning in R: RegressionLight My Fire: Starting To Use Spark With dplyr Syntax
Tools of the Trade: Advanced dplyr Usage
dplyr interface to Spark, including advanced field selection, calculating groupwise statistics, and joining data frames.Going Native: Use The Native Interface to Manipulate Spark DataFrames
Case Study: Learning to be a Machine: Running Machine Learning Models on Spark
sparklyr's machine learning routines, by predicting the year in which a song was released.Complete
Earn Statement of Accomplishment
Add this credential to your LinkedIn profile, resume, or CVShare it on social media and in your performance reviewEnroll Now
FAQs
What is MLib in Apache Spark used for?
MLib is Spark’s machine learning library. It’s used to simplify the process of machine learning and provides a set of algorithms to help with clarifying, regressing, clustering, and filtering data. This course teaches you how to use Spark MLib and lets you practice using real datasets.
What is the difference between Spark and Sparklyr?
Sparklyr is an interface to Spark, specifically in the R programming language. Sparklyr allows you to access Spark tools to transform data. This course uses both Spark and Sparklyr to analyze datasets.
Is R useful in big data?
Yes - R is a very useful language in big data analysis. R with Apache Spark is a particularly good combination for analyzing big data sets.
Is this course suitable for beginners?
Yes, even though no prior knowledge of Apache Spark is required, this course introduces learners to the basics of Apache Spark and how to use Spark with the sparklyr package in R.
What topics does this course cover?
This course covers topics such as manipulating Spark DataFrames using the dplyr interface and native interface to Spark, exploring the Million Song Dataset, learning more about utilizing the dplyr interface to Spark, learning to use Spark's machine learning data transformation features, and running machine learning models on Spark.
Will I receive a certificate at the end of the course?
Yes! Upon the successful completion of this course, learners will be awarded a certificate of completion verified by DataCamp.
Would I need to complete any programming projects?
Yes, throughout the course learners will be given the opportunity to practice their learned skills by programming projects in R.
Who will benefit from this course?
This course can be beneficial for anyone interested in learning how to manipulate large datasets quickly using Apache Spark and the sparklyr package in R. From data engineers to data scientists to analytics professionals and software developers, anyone working with large datasets would benefit from this course.
What will I learn when manipulating Spark DataFrames using the dplyr interface?
When manipulating Spark DataFrames using the dplyr interface, learners will learn advanced field selection, calculate groupwise statistics, and join data frames.
Would I need to have prior knowledge of Apache Spark in order to complete this course?
No prior knowledge of Apache Spark is required, however learners should have a basic understanding of R. We recommend taking the Intermediate R course.
Join over 19 million learners and start Introduction to Spark with sparklyr in R today!
Create Your Free Account
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.Grow your data skills with DataCamp for Mobile
Make progress on the go with our mobile courses and daily 5-minute coding challenges.