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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

Product type Paperback

Published in Jul 2017

Publisher Packt

ISBN-13 9781787126497

Length 350 pages

Edition 1st Edition

Languages

Java

Tools

Apache Spark

Concepts

Big Data

Authors (2):

Kumar

Gulati

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 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 job configuration and submission

When a Spark job is launched, it creates a SparkConf object and passes it to the constructor of SparkContext. The SparkConf() object contains a near exhaustive list of customizable parameters that can tune a Spark job as per cluster resources. The SparkConf object becomes immutable once it is passed to invoke a SparkContext() constructor, hence it becomes important to not only identify, but also modify all the SparkConf parameters before creating a SparkContext object.

There are different ways in which Spark job can be configured.

Spark's conf directory provides the default configurations to execute a Spark job. The SPARK_CONF_DIR parameter can be used to override the default location of the conf directory, which usually is SPARK_HOME/conf and some of the configuration files that are expected in this folder are spark-defaults.conf, spark-env.sh, and log4j.properties. Log4j is used by Spark for logging mechanism and can be configured by modifying the log4j...

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Authors (2)

Kumar

Kumar

Sumit Kumar is a developer with industry insights in telecom and banking. At different junctures, he has worked as a Java and SQL developer, but it is shell scripting that he finds both challenging and satisfying at the same time. Currently, he delivers big data projects focused on batch/near-real-time analytics and the distributed indexed querying system. Besides IT, he takes a keen interest in human and ecological issues.

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Gulati

Gulati

Sourav Gulati is associated with software industry for more than 7 years. He started his career with Unix/Linux and Java and then moved towards big data and NoSQL World. He has worked on various big data projects. He has recently started a technical blog called Technical Learning as well. Apart from IT world, he loves to read about mythology.

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