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Hadoop 2.x Administration Cookbook

You're reading from   Hadoop 2.x Administration Cookbook Administer and maintain large Apache Hadoop clusters

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Product type Paperback
Published in May 2017
Publisher Packt
ISBN-13 9781787126732
Length 348 pages
Edition 1st Edition
Tools
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Author (1):
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Aman Singh Aman Singh
Author Profile Icon Aman Singh
Aman Singh
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Table of Contents (14) Chapters Close

Preface 1. Hadoop Architecture and Deployment FREE CHAPTER 2. Maintaining Hadoop Cluster HDFS 3. Maintaining Hadoop Cluster – YARN and MapReduce 4. High Availability 5. Schedulers 6. Backup and Recovery 7. Data Ingestion and Workflow 8. Performance Tuning 9. HBase Administration 10. Cluster Planning 11. Troubleshooting, Diagnostics, and Best Practices 12. Security Index

Introduction

In the previous chapters, we learned about the storage layer HDFS, how to configure it, and what are its different components. We mainly talked about Namenode, Datanode, and its concepts.

In this chapter, we will take a look at the processing layer which is MapReduce and the resource management framework YARN. Prior to Hadoop 2.x, MapReduce was the only processing layer for Hadoop, but the introduction of YARN as a framework, provided a pluggable processing layer, which could be MapReduce, Spark, and so on.

Note

While the recipes in this chapter will give you an overview of a typical configuration, we encourage you to adapt this proposal according to your needs. The deployment directory structure varies according to IT policies within an organization.

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