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Apache Spark 2.x for Java Developers

You're reading from  Apache Spark 2.x for Java Developers

Product type Book
Published in Jul 2017
Publisher Packt
ISBN-13 9781787126497
Pages 350 pages
Edition 1st Edition
Languages
Authors (2):
Sourav Gulati Sourav Gulati
Profile icon Sourav Gulati
Sumit Kumar Sumit Kumar
Profile icon Sumit Kumar
View More author details

Table of Contents (19) Chapters

Title Page
Credits
Foreword
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Introduction to Spark 2. Revisiting Java 3. Let Us Spark 4. Understanding the Spark Programming Model 5. Working with Data and Storage 6. Spark on Cluster 7. Spark Programming Model - Advanced 8. Working with Spark SQL 9. Near Real-Time Processing with Spark Streaming 10. Machine Learning Analytics with Spark MLlib 11. Learning Spark GraphX

Streams


A stream represents a collection of elements on which a chain of aggregate operations can be performed lazily. Streams have been optimized to cater to both sequential as well as parallel computation, keeping in mind the hardware capabilities of CPU cores. The Steams API was introduced in Java 8 to cater to functional programming needs of the developer. Streams are not Java based collections; however, they are capable enough to operate over collections by first converting them into streams. Some of the characteristics of streams that make them uniquely different from Java collection APIs are:

  • Streams do not store elements. It only transfer values received from sources such as I/O channels, generating functions, data structures (Collections API), and perform a set of pipelined computation on them.
  • Streams do not change the underlying data, they only process them and produce a new set of resultant data. When a distinct() or sorted() method is called on a stream, the source data does not...
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