Hadoop is an open source project available under the Apache License 2.0. It has the ability to manage and store very large data sets across a distributed cluster of servers. One of the most beneficial features is its fault tolerance, which enables big data applications to continue to operate properly in the event of a failure. Another benefit of using Hadoop is its scalability. This programming logic has the potential to expand from a single server to numerous servers, each with the ability to have local computation and storage options.
This book is for anyone using Hadoop to perform a job that is data related, or if you have an interest in redefining how you can obtain meaningful information about any of your data stores. This includes big data solution architects, Linux system and big data engineers, big data platform engineers, Java programmers, and database administrators.
If you have an interest in learning more about Hadoop and how to extract specific elements for further analysis or review, then this book is for you.
You should have development experience and understand the basics of Hadoop, and should now be interested in employing it in real-world settings.
The source code for the samples is available for download at www.wrox.com/go/professionalhadoop or https://github.com/backstopmedia/hadoopbook.
This book was written in eight chapters as follows:
To help you get the most from the text and keep track of what's happening, we've used a number of conventions throughout the book.
As for styles in the text:
persistence.properties FileSystem fs = FileSystem.get(URI.create(uri), conf);
InputStream in = null;
try { http://<Slave Hostname>:50075As you work through the examples in this book, you may choose either to type in all the code manually, or to use the source code files that accompany the book. All the source code used in this book is available for download at www.wrox.com. Specifically for this book, the code download is on the Download Code tab at:
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