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Big Data Architect???s Handbook

You're reading from   Big Data Architect???s Handbook A guide to building proficiency in tools and systems used by leading big data experts

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781788835824
Length 486 pages
Edition 1st Edition
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Author (1):
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Syed Muhammad Fahad Akhtar Syed Muhammad Fahad Akhtar
Author Profile Icon Syed Muhammad Fahad Akhtar
Syed Muhammad Fahad Akhtar
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Table of Contents (21) Chapters Close

Preface 1. Why Big Data? FREE CHAPTER 2. Big Data Environment Setup 3. Hadoop Ecosystem 4. NoSQL Database 5. Off-the-Shelf Commercial Tools 6. Containerization 7. Network Infrastructure 8. Cloud Infrastructure 9. Security and Monitoring 10. Frontend Architecture 11. Backend Architecture 12. Machine Learning 13. Artificial Intelligence 14. Elasticsearch 15. Structured Data 16. Unstructured Data 17. Data Visualization 18. Financial Trading System 19. Retail Recommendation System 20. Other Books You May Enjoy

Hadoop MapReduce

Now that we have an understanding of how HDFS works, it's time to move forward and seek to understand what the benefit of HDFS and a clustered computing environment is. Hadoop introduces the MapReduce framework to facilitate the execution of programs and parallel processing. The following figure illustrates where the MapReduce framework fits into Hadoop's architecture:

Figure-3.2.5

This framework mainly consists of two parts: Map and Reduce. The Map process mainly comprises of getting information from the data stored, applying the required algorithm, and generating a result in the form of key-value pairs. The Reduce process is used to summarize the information that was collected and paired during the Map process. We will look at these processes in more detail as we proceed with this chapter, but let's first understand how a program is executed...

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