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Practical Big Data Analytics

You're reading from   Practical Big Data Analytics Hands-on techniques to implement enterprise analytics and machine learning using Hadoop, Spark, NoSQL and R

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781783554393
Length 412 pages
Edition 1st Edition
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Author (1):
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Nataraj Dasgupta Nataraj Dasgupta
Author Profile Icon Nataraj Dasgupta
Nataraj Dasgupta
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Table of Contents (13) Chapters Close

Preface 1. Too Big or Not Too Big FREE CHAPTER 2. Big Data Mining for the Masses 3. The Analytics Toolkit 4. Big Data With Hadoop 5. Big Data Mining with NoSQL 6. Spark for Big Data Analytics 7. An Introduction to Machine Learning Concepts 8. Machine Learning Deep Dive 9. Enterprise Data Science 10. Closing Thoughts on Big Data 11. External Data Science Resources 12. Other Books You May Enjoy

The Hadoop ecosystem

This chapter should be titled as the Apache ecosystem. Hadoop, like all the other projects that will be discussed in this section, is an Apache project. Apache is used loosely as a short form for the open source projects that are supported by the Apache Software Foundation. It originally has its roots in the development of the Apache HTTP server in the early 90s, and today is a collaborative global initiative that comprises entirely of volunteers who participate in releasing open source software to the global technical community.

Hadoop started out as, and still is, one of the projects in the Apache ecosystem. Due to its popularity, many other projects that are also part of Apache have been linked directly or indirectly to Hadoop as they support key functionalities in the Hadoop environment. That said, it is important to bear in mind that these projects can...

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