Hadoop Ebook

Topics: Hadoop, MapReduce, Business intelligence Pages: 72 (16944 words) Published: November 21, 2014
Hadoop Illuminated

Mark Kerzner
Sujee Maniyam

Hadoop Illuminated
by Mark Kerzner and Sujee Maniyam

Dedication
To the open source community
This book on GitHub [https://github.com/hadoop-illuminated/hadoop-book] Companion project on GitHub [https://github.com/hadoop-illuminated/HI-labs]

i

Acknowledgements
From Mark
I would like to express gratitude to my editors, co-authors, colleagues, and bosses who shared the thorny path to working clusters - with the hope to make it less thorny for those who follow. Seriously, folks, Hadoop is hard, and Big Data is tough, and there are many related products and skills that you need to master. Therefore, have fun, provide your feedback [http://groups.google.com/group/hadoop-illuminated], and I hope you will find the book entertaining.

"The author's opinions do not necessarily coincide with his point of view." - Victor Pelevin, "Generation P" [http://lib.udm.ru/lib/PELEWIN/pokolenie_engl.txt]
From Sujee
To the kind souls who helped me along the way
Copyright © 2013 Hadoop illuminated LLC. All Rights Reserved.

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Table of Contents
1. Who is this book for? ...................................................................................................... 1 1.1. About "Hadoop illuminated" ................................................................................... 1 2. About Authors ................................................................................................................ 2 3. Why do I Need Hadoop ? ................................................................................................. 5 3.1. Hadoop provides storage for Big Data at reasonable cost ............................................. 5 3.2. Hadoop allows to capture new or more data .............................................................. 6 3.3. With Hadoop, you can store data longer ................................................................... 6 3.4. Hadoop provides scalable analytics .......................................................................... 6 3.5. Hadoop provides rich analytics ............................................................................... 6 4. Big Data ....................................................................................................................... 7 4.1. What is Big Data? ................................................................................................ 7 4.2. Human Generated Data and Machine Generated Data .................................................. 7 4.3. Where does Big Data come from ............................................................................ 8 4.4. Examples of Big Data in the Real world ................................................................... 8 4.5. Challenges of Big Data ......................................................................................... 9 4.6. How Hadoop solves the Big Data problem .............................................................. 10 5. Soft Introduction to Hadoop ............................................................................................ 11 5.1. MapReduce or Hadoop? ....................................................................................... 11 5.2. Why Hadoop? .................................................................................................... 11 5.3. Meet the Hadoop Zoo .......................................................................................... 13 5.4. Hadoop alternatives ............................................................................................. 14 5.5. Alternatives for distributed massive computations ..................................................... 16 5.6. Arguments for Hadoop ........................................................................................ 17 5.7. Say "Hi!" to Hadoop...
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