Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Apache Spark 2: Data Processing and Real-Time Analytics

You're reading from   Apache Spark 2: Data Processing and Real-Time Analytics Master complex big data processing, stream analytics, and machine learning with Apache Spark

Arrow left icon
Product type Course
Published in Dec 2018
Publisher Packt
ISBN-13 9781789959208
Length 616 pages
Edition 1st Edition
Languages
Concepts
Arrow right icon
Authors (7):
Arrow left icon
Sridhar Alla Sridhar Alla
Author Profile Icon Sridhar Alla
Sridhar Alla
Romeo Kienzler Romeo Kienzler
Author Profile Icon Romeo Kienzler
Romeo Kienzler
Siamak Amirghodsi Siamak Amirghodsi
Author Profile Icon Siamak Amirghodsi
Siamak Amirghodsi
Broderick Hall Broderick Hall
Author Profile Icon Broderick Hall
Broderick Hall
Md. Rezaul Karim Md. Rezaul Karim
Author Profile Icon Md. Rezaul Karim
Md. Rezaul Karim
Meenakshi Rajendran Meenakshi Rajendran
Author Profile Icon Meenakshi Rajendran
Meenakshi Rajendran
Shuen Mei Shuen Mei
Author Profile Icon Shuen Mei
Shuen Mei
+3 more Show less
Arrow right icon
View More author details
Toc

Table of Contents (23) Chapters Close

Title Page
Copyright
About Packt
Contributors
Preface
1. A First Taste and What's New in Apache Spark V2 FREE CHAPTER 2. Apache Spark Streaming 3. Structured Streaming 4. Apache Spark MLlib 5. Apache SparkML 6. Apache SystemML 7. Apache Spark GraphX 8. Spark Tuning 9. Testing and Debugging Spark 10. Practical Machine Learning with Spark Using Scala 11. Spark's Three Data Musketeers for Machine Learning - Perfect Together 12. Common Recipes for Implementing a Robust Machine Learning System 13. Recommendation Engine that Scales with Spark 14. Unsupervised Clustering with Apache Spark 2.0 15. Implementing Text Analytics with Spark 2.0 ML Library 16. Spark Streaming and Machine Learning Library 1. Other Books You May Enjoy Index

Configuring IntelliJ to work with Spark and run Spark ML sample codes


We need to run some configurations to ensure that the project settings are correct before being able to run the samples that are provided by Spark or any of the programs listed this book.

Getting ready

We need to be particularly careful when configuring the project structure and global libraries. After we set everything up, we proceed to run the sample ML code provided by the Spark team to verify the setup. Sample code can be found under the Spark directory or can be obtained by downloading the Spark source code with samples.

How to do it...

The following are the steps for configuring IntelliJ to work with Spark MLlib and for running the sample ML code provided by Spark in the examples directory. The examples directory can be found in your home directory for Spark. Use the Scala samples to proceed:

  1. Click on the Project Structure... option, as shown in the following screenshot, to configure project settings:
  1. Verify the settings...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime