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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

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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