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Learning Hadoop 2

You're reading from   Learning Hadoop 2 Design and implement data processing, lifecycle management, and analytic workflows with the cutting-edge toolbox of Hadoop 2

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Product type Paperback
Published in Feb 2015
Publisher Packt
ISBN-13 9781783285518
Length 382 pages
Edition 1st Edition
Tools
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Toc

Table of Contents (13) Chapters Close

Preface 1. Introduction 2. Storage FREE CHAPTER 3. Processing – MapReduce and Beyond 4. Real-time Computation with Samza 5. Iterative Computation with Spark 6. Data Analysis with Apache Pig 7. Hadoop and SQL 8. Data Lifecycle Management 9. Making Development Easier 10. Running a Hadoop Cluster 11. Where to Go Next Index

Summary


This has been quite a whistle-stop tour around the considerations of running an operational Hadoop cluster. We didn't try to turn developers into administrators, but hopefully, the broader perspective will help you to help your operations staff. In particular, we covered the following topics:

  • How Hadoop is a natural fit for DevOps approaches as its multilayered complexity means it's not possible or desirable to have substantial knowledge gaps between development and operations staff

  • Cloudera Manager, and how it can be a great management and monitoring tool; it might cause integration problems though, if you have other enterprise tools, and it comes with a vendor lock-in risk

  • Ambari, the Apache open source alternative to Cloudera Manager, and how it is used in the Hortonworks distribution

  • How to think about selecting hardware for a physical Hadoop cluster, and how this naturally fits into the considerations of how the multiple workloads possible in the world of Hadoop 2 can peacefully...

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