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Mastering Hadoop 3

You're reading from  Mastering Hadoop 3

Product type Book
Published in Feb 2019
Publisher Packt
ISBN-13 9781788620444
Pages 544 pages
Edition 1st Edition
Languages
Authors (2):
Chanchal Singh Chanchal Singh
Profile icon Chanchal Singh
Manish Kumar Manish Kumar
Profile icon Manish Kumar
View More author details
Toc

Table of Contents (23) Chapters close

Title Page
Dedication
About Packt
Foreword
Contributors
Preface
1. Journey to Hadoop 3 2. Deep Dive into the Hadoop Distributed File System 3. YARN Resource Management in Hadoop 4. Internals of MapReduce 5. SQL on Hadoop 6. Real-Time Processing Engines 7. Widely Used Hadoop Ecosystem Components 8. Designing Applications in Hadoop 9. Real-Time Stream Processing in Hadoop 10. Machine Learning in Hadoop 11. Hadoop in the Cloud 12. Hadoop Cluster Profiling 13. Who Can Do What in Hadoop 14. Network and Data Security 15. Monitoring Hadoop 1. Other Books You May Enjoy Index

Introduction to YARN job scheduling


In the previous sections, we talked about the YARN architecture and its components. The Resource Manager has two major components; namely, the application manager and the scheduler. The Resource Manager scheduler is responsible for allocating the required resources to an application based on schedule policies. Before YARN, Hadoop used to allocate slots for map and reduce tasks from available memory, which restricts reduce tasks to run on slots allocated for map tasks and the other way around. YARN does not define map and reduce slots initially. Based on a request, it launches containers for tasks. This means that if any free container is available, it will be used for map or reduce tasks. As previously discussed in this chapter, the scheduler will not perform monitoring or status tracking for the any application. The scheduler receives requests from per application application masters with the resources requirement detail and executes its scheduling function...

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