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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 application in distributed-mode


A Spark application is made of up of Driver and Executor(s) processes. Each application in Spark contains one driver process and one or more executor processes. The driver is the central coordinator of the application that drives the application. Spark Driver communicates and divides work among one or more executors. In distributed mode, Spark driver and each executor runs in separate JVM.

Logical Representation of a Spark Application in Distributed Mode

Driver program

SparkContext is initialized in the Driver JVM. Spark driver can be considered as the master of Spark applications. The following are the responsibilities of Spark Driver program:

  • It creates the physical plan of execution of tasks based on the DAG of operations.
  • It schedules the tasks on the executors. It passes the task bundle to executors based. Data locality principle is used while passing the tasks to executors.
  • Spark driver tracks RDD partitions to executor mapping for executing future tasks...
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