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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

Fair scheduler


In fair scheduling, all applications get almost an equal amount of the available resources. In fair scheduler, when the first application is submitted to YARN, it will assign all the available resources to the application. Now in any scenario, if the new application is submitted to the scheduler, the scheduler will start allocating resources to the new application until both the applications have almost an equal amount of resources for their execution. Unlike the two schedulers discussed before, the fair scheduler prevents applications from resource starvation and assures that the applications in the queue get the required memory for execution. The distribution of the minimum and maximum share resources are calculated by the scheduling queue by using the configuration provided in the fair scheduler. The application will get the amount of resources configured for the queue where the application is submitted and if a new application is submitted to the same queue, the total...

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