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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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Author (1):
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GABRIELE MODENA GABRIELE MODENA
Author Profile Icon GABRIELE MODENA
GABRIELE MODENA
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Toc

Table of Contents (18) Chapters Close

Learning Hadoop 2
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Introduction FREE CHAPTER 2. Storage 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

I'm a developer – I don't care about operations!


Before going any further, we need to explain why we are putting a chapter about systems operations in a book squarely aimed at developers. For anyone who has developed for more traditional platforms (for example, web apps, database programming, and so on) then the norm might well have been for a very clear delineation between development and operations. The first group builds the code and packages it up, and the second group controls and operates the environment in which it runs.

In recent years, the DevOps movement has gained momentum with a belief that it is best for everyone if these silos are removed and that the teams work more closely together. When it comes to running systems and services based on Hadoop, we believe this is absolutely essential.

Hadoop and DevOps practices

Even though a developer can conceptually build an application ready to be dropped into YARN and forgotten about, the reality is often more nuanced. How many resources...

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