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You're reading from Mastering Hadoop 3 Big data processing at scale to unlock unique business insights

Product type Paperback

Published in Feb 2019

Publisher Packt

ISBN-13 9781788620444

Length 544 pages

Edition 1st Edition

Languages

Java

Tools

Hadoop

Concepts

Big Data

Authors (3):

Timothy Wong

Manish Kumar

Chanchal Singh

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Table of Contents (21) Chapters

Preface

1. Section 1: Introduction to Hadoop 3 FREE CHAPTER

2. Journey to Hadoop 3

3. Deep Dive into the Hadoop Distributed File System

4. YARN Resource Management in Hadoop

5. Internals of MapReduce

6. Section 2: Hadoop Ecosystem

7. SQL on Hadoop

8. Real-Time Processing Engines

9. Widely Used Hadoop Ecosystem Components

10. Section 3: Hadoop in the Real World

11. Designing Applications in Hadoop

12. Real-Time Stream Processing in Hadoop

13. Machine Learning in Hadoop

14. Hadoop in the Cloud

15. Hadoop Cluster Profiling

16. Section 4: Securing Hadoop

17. Who Can Do What in Hadoop

18. Network and Data Security

19. Monitoring Hadoop

20. Other Books You May Enjoy

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Journey to Hadoop 3

Hadoop has come a long way since its inception. Powered by a community of open source enthusiasts, it has seen three major version releases. The version 1 release saw the light of day six years after the first release of Hadoop. With this release, the Hadoop platform had full capabilities that can run MapReduce-distributed computing on Hadoop Distributed File System (HDFS) distributed storage. It had some of the most major performance improvements ever done, along with full support for security. This release also enjoyed a lot of improvements with respect to HBASE.

The version 2 release made significant leaps compared to version 1 of Hadoop. It introduced YARN, a sophisticated general-purpose resource manager and job scheduling component. HDFS high availability, HDFS federations, and HDFS snapshots were some other prominent features introduced in version 2...

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Authors (3)

Singh

Contacted on 12/01/18 by Davis Anto

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Wong

Dr. Timothy Wong is a 30 years IT veteran. He holds a PhD in networking from University of Manchester Institute of Science and Technology, UK. He has deep experience in wireless and wireline networking, digital a/v, software development, sales and consulting. He frequently works with telcos, banks, governments and enterprises. He is also a professor on Big Data, Wireless and IoT at Humber College, Toronto, Canada. As an entrepreneur, he co-founded a number of companies in the past 20 years. He infuses business and technical knowledge to pursue successes.

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Kumar

Ashish Kumar is a seasoned data science professional, a publisher author and a thought leader in the field of data science and machine learning. An IIT Madras graduate and a Young India Fellow, he has around 7 years of experience in implementing and deploying data science and machine learning solutions for challenging industry problems in both hands-on and leadership roles. Natural Language Procession, IoT Analytics, R Shiny product development, Ensemble ML methods etc. are his core areas of expertise. He is fluent in Python and R and teaches a popular ML course at Simplilearn. When not crunching data, Ashish sneaks off to the next hip beach around and enjoys the company of his Kindle. He also trains and mentors data science aspirants and fledgling start-ups.

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