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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. Big Data 5 3.1. What is Big Data? 5 3.2. Human Generated Data and Machine Generated Data 5 3.3. Where does Big Data come from 5 3.4. Examples of Big Data in the Real world 6 3.5. Challenges of Big Data 7 3.1. Taming Big Data 8 4. Hadoop and Big Data 9 4.1. How Hadoop solves the Big Data problem 9 4.2. Business Case for Hadoop 10 5. Hadoop for Executives 12 6. Hadoop for Developers 14
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Hadoop Illuminated
Mark Kerzner <mark@elephantscale.com>
Sujee Maniyam <sujee@elephantscale.com>
![](https://csdnimg.cn/release/download_crawler_static/89463853/bg2.jpg)
Hadoop Illuminated
by Mark Kerzner and Sujee Maniyam
![](https://csdnimg.cn/release/download_crawler_static/89463853/bg4.jpg)
ii
Acknowledgements
To Hadoop community
• Apache Hadoop [http://wiki.apache.org/hadoop/PoweredBy] is an open source software from Apache
Software Foundation [http://wiki.apache.org/hadoop/PoweredBy].
• Apache, Apache Hadoop, and Hadoop are trademarks of The Apache Software Foundation. Used with
permission. No endorsement by The Apache Software Foundation is implied by the use of these marks
• For brevity we will refer Apache Hadoop as Hadoop
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://en.wikipedia.org/wiki/Generation_%22%D0%9F%22]
From Sujee
To the kind souls who helped me along the way.
Copyright 2013-2016 Elephant Scale LLC
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in
compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is dis-
tributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
express or implied. See the License for the specific language governing permissions and limitations under
the License.
![](https://csdnimg.cn/release/download_crawler_static/89463853/bg5.jpg)
iii
Table of Contents
1. Who is this book for? ...................................................................................................... 1
1.1. About "Hadoop illuminated" ................................................................................... 1
2. About Authors ................................................................................................................ 2
3. Big Data ....................................................................................................................... 5
3.1. What is Big Data? ................................................................................................ 5
3.2. Human Generated Data and Machine Generated Data .................................................. 5
3.3. Where does Big Data come from ............................................................................ 5
3.4. Examples of Big Data in the Real world ................................................................... 6
3.5. Challenges of Big Data ......................................................................................... 7
3.1. Taming Big Data .................................................................................................. 8
4. Hadoop and Big Data ...................................................................................................... 9
4.1. How Hadoop solves the Big Data problem ................................................................ 9
4.2. Business Case for Hadoop .................................................................................... 10
5. Hadoop for Executives ................................................................................................... 12
6. Hadoop for Developers .................................................................................................. 14
7. Soft Introduction to Hadoop ............................................................................................ 16
7.1. Hadoop = HDFS + MapReduce ............................................................................. 16
7.2. Why Hadoop? .................................................................................................... 16
7.3. Meet the Hadoop Zoo .......................................................................................... 18
7.4. Hadoop alternatives ............................................................................................. 21
7.5. Alternatives for distributed massive computations ..................................................... 22
7.6. Arguments for Hadoop ........................................................................................ 23
8. Hadoop Distributed File System (HDFS) -- Introduction ....................................................... 24
8.1. HDFS Concepts .................................................................................................. 24
8.1. HDFS Architecture ............................................................................................. 27
9. Introduction To MapReduce ............................................................................................ 30
9.1. How I failed at designing distributed processing ....................................................... 30
9.2. How MapReduce does it ...................................................................................... 31
9.3. How MapReduce really does it ............................................................................. 31
9.1. Understanding Mappers and Reducers .................................................................... 32
9.4. Who invented this? ............................................................................................. 34
9.5. The benefits of MapReduce programming ............................................................... 34
10. Hadoop Use Cases and Case Studies ............................................................................... 35
10.1. Politics ............................................................................................................ 35
10.2. Data Storage .................................................................................................... 35
10.3. Financial Services ............................................................................................. 35
10.4. Health Care ...................................................................................................... 36
10.5. Human Sciences ............................................................................................... 37
10.6. Telecoms ......................................................................................................... 37
10.7. Travel ............................................................................................................. 38
10.8. Energy ............................................................................................................ 38
10.9. Logistics .......................................................................................................... 39
10.10. Retail ............................................................................................................ 40
10.11. Software / Software As Service (SAS) / Platforms / Cloud ....................................... 40
10.12. Imaging / Videos ............................................................................................. 41
10.13. Online Publishing , Personalized Content ............................................................. 42
11. Hadoop Distributions ................................................................................................... 44
11.1. The Case for Distributions .................................................................................. 44
11.2. Overview of Hadoop Distributions ....................................................................... 44
11.3. Hadoop in the Cloud ......................................................................................... 45
12. Big Data Ecosystem ..................................................................................................... 47
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