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Learning Apache Spark 2

You're reading from  Learning Apache Spark 2

Product type Book
Published in Mar 2017
Publisher Packt
ISBN-13 9781785885136
Pages 356 pages
Edition 1st Edition
Languages
Concepts

Table of Contents (18) Chapters

Learning Apache Spark 2
Credits
About the Author
About the Reviewers
www.packtpub.com
Customer Feedback
Preface
1. Architecture and Installation 2. Transformations and Actions with Spark RDDs 3. ETL with Spark 4. Spark SQL 5. Spark Streaming 6. Machine Learning with Spark 7. GraphX 8. Operating in Clustered Mode 9. Building a Recommendation System 10. Customer Churn Prediction 1. Theres More with Spark

What's new in Spark 2.0?

For some of you who have stayed closed to the announcements of Spark 2.0, you might have heard of the fact that DataFrame API has now been merged with the Dataset API, which means developers now have to learn fewer concepts to learn and work with a single high-level, type-safe API called a Dataset.

The Dataset API takes on two distinct characteristics:

  • A strongly typed API
  • An untyped API

A DataFrame in Apache Spark 2.0 is just a dataset of generic row objects, which are especially useful in cases when you do not know the fields ahead of time; if you don't know the class that is eventually going to wrap this data, you will want to stay with a generic object that can later be cast into any other class (as soon as you figure out what that is). If you want to switch to a particular class, you can request Spark SQL to enforce types on the previously generated generic row objects using the as method of the DataFrame.

Let us consider a simple example of loading a Product available...

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