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Mastering Hadoop 3

You're reading from   Mastering Hadoop 3 Big data processing at scale to unlock unique business insights

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781788620444
Length 544 pages
Edition 1st Edition
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Authors (3):
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Timothy Wong Timothy Wong
Author Profile Icon Timothy Wong
Timothy Wong
Manish Kumar Manish Kumar
Author Profile Icon Manish Kumar
Manish Kumar
Chanchal Singh Chanchal Singh
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Chanchal Singh
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Table of Contents (21) Chapters Close

Preface 1. Section 1: Introduction to Hadoop 3 FREE CHAPTER
2. Journey to Hadoop 3 3. Deep Dive into the Hadoop Distributed File System 4. YARN Resource Management in Hadoop 5. Internals of MapReduce 6. Section 2: Hadoop Ecosystem
7. SQL on Hadoop 8. Real-Time Processing Engines 9. Widely Used Hadoop Ecosystem Components 10. Section 3: Hadoop in the Real World
11. Designing Applications in Hadoop 12. Real-Time Stream Processing in Hadoop 13. Machine Learning in Hadoop 14. Hadoop in the Cloud 15. Hadoop Cluster Profiling 16. Section 4: Securing Hadoop
17. Who Can Do What in Hadoop 18. Network and Data Security 19. Monitoring Hadoop 20. Other Books You May Enjoy

YARN Resource Management in Hadoop

From the very beginning of Hadoop's existence, it has consisted of two major parts, the storage part, which is known as the Hadoop Distributed File System (HDFS), and the processing part, which is known as MapReduce. In the previous chapter, we discussed the Hadoop Distributed File System, its architecture, and its internals. In Hadoop version 1, the only job that can be submitted and executed to Hadoop is MapReduce. In the present era of data processing, real-time and near real-time processing are favored over batch processing. Thus, there is a need for a generic application executor and Resource Manager that can schedule and execute all types of applications, including MapReduce, in real time or near real time. In this chapter, we will learn about YARN and will cover the following topics:

  • YARN architecture 
  • YARN job...
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