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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

Data Processing

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

Clusters, nodes and daemons

Cluster, node, and daemon is the terminology that we will use throughout this chapter. It is important to build a common understanding of the context around which these terms are used during this chapter.

Cluster: A cluster is a group of computers (nodes) that work together in many aspects, and are often viewed as a single system.
Node: A node is an individual component in the cluster.
Daemon: In multitasking computer operating systems, a daemon is a computer program that runs as a background process, rather than being under control of an interactive user.

So now that we have terminology out of the way, what exactly does Spark need to run on a cluster? How is it managed? Is it a master/slave architecture? All these are key questions and need to be answered to fully understand the way how Spark works on a set of machines that comprise a cluster. Let's refer to the classical Spark architecture diagram (reference spark.apache.org/docs/latest) to understand this in a...

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