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Apache Spark 2.x for Java Developers

You're reading from   Apache Spark 2.x for Java Developers Explore big data at scale using Apache Spark 2.x Java APIs

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787126497
Length 350 pages
Edition 1st Edition
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Concepts
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Authors (2):
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Sourav Gulati Sourav Gulati
Author Profile Icon Sourav Gulati
Sourav Gulati
Sumit Kumar Sumit Kumar
Author Profile Icon Sumit Kumar
Sumit Kumar
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Toc

Table of Contents (12) Chapters Close

Preface 1. Introduction to Spark FREE CHAPTER 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

Summary


In this chapter, we discussed machine learning as a field of study and its various sub classifications. We then progressed ahead to discuss various parlance associated with machine learning and how machine learning has been implemented in Apache Spark. We also covered the datatypes that are used in the spark.mllib package and then discussed job chaining using pipeline. Terminologies around pipeline were also discussed in detail along with use cases. Finally, operations on features what a feeling discussed.

In the following chapter, we will look into another module of Spark, that is, GraphX, and we will discover types of GraphX RDD and various operations associated with them. We will also discuss use cases around GraphX implementation.

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