Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Mastering Apache Spark 2.x

You're reading from   Mastering Apache Spark 2.x Advanced techniques in complex Big Data processing, streaming analytics and machine learning

Arrow left icon
Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781786462749
Length 354 pages
Edition 2nd Edition
Languages
Concepts
Arrow right icon
Author (1):
Arrow left icon
Romeo Kienzler Romeo Kienzler
Author Profile Icon Romeo Kienzler
Romeo Kienzler
Arrow right icon
View More author details
Toc

Table of Contents (15) Chapters Close

Preface 1. A First Taste and What’s New in Apache Spark V2 FREE CHAPTER 2. Apache Spark SQL 3. The Catalyst Optimizer 4. Project Tungsten 5. Apache Spark Streaming 6. Structured Streaming 7. Apache Spark MLlib 8. Apache SparkML 9. Apache SystemML 10. Deep Learning on Apache Spark with DeepLearning4j and H2O 11. Apache Spark GraphX 12. Apache Spark GraphFrames 13. Apache Spark with Jupyter Notebooks on IBM DataScience Experience 14. Apache Spark on Kubernetes

Using Datasets

This API as been introduced since Apache Spark 1.6 as experimental and finally became a first-class citizen in Apache Spark 2.0. It is basically a strongly typed version of DataFrames.

DataFrames are kept for backward compatibility and are not going to be deprecated for two reasons. First, a DataFrame since Apache Spark 2.0 is nothing else but a Dataset where the type is set to Row. This means that you actually lose the strongly static typing and fall back to a dynamic typing. This is also the second reason why DataFrames are going to stay. Dynamically typed languages such as Python or R are not capable of using Datasets because there isn't a concept of strong, static types in the language.

So what are Datasets exactly? Let's create one:

import spark.implicits._
case class Person(id: Long, name: String)
val caseClassDS = Seq(Person(1,"Name1")...
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
Banner background image