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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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 Kumar Kumar
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Kumar
 Gulati Gulati
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Gulati
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Table of Contents (19) Chapters Close

Title Page
Credits
Foreword
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
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

Spark REST APIs


Representational state transfer (REST) architecture is used very often while developing web services. These days, a lot of frameworks such as Hadoop, Apache Storm, and so on, provide RESTful web services that help users to interact with or monitor the framework. Apache Spark, being in the same league, also provides REST web services that can be used to monitor the Spark applications. In this section, we will learn about the REST APIs provided by Apache Spark.

The response type of Spark REST APIs is JSON, which can be used to design custom monitoring over Spark applications. The REST endpoints are mounted at /api/v1, which means that for a SparkContext with UI running https://localhost:4040, the REST endpoints will be mounted at https://localhost:4040/api/v1.

It is time to explore some of the REST APIs provided by Apache Spark. For that, launch Spark shell and run any of the jobs mentioned in Spark REPL also known as CLI section:

Execute the following command to list the applications...

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