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Mastering Hadoop 3

You're reading from  Mastering Hadoop 3

Product type Book
Published in Feb 2019
Publisher Packt
ISBN-13 9781788620444
Pages 544 pages
Edition 1st Edition
Languages
Authors (2):
Chanchal Singh Chanchal Singh
Profile icon Chanchal Singh
Manish Kumar Manish Kumar
Profile icon Manish Kumar
View More author details
Toc

Table of Contents (23) Chapters close

Title Page
Dedication
About Packt
Foreword
Contributors
Preface
1. Journey to Hadoop 3 2. Deep Dive into the Hadoop Distributed File System 3. YARN Resource Management in Hadoop 4. Internals of MapReduce 5. SQL on Hadoop 6. Real-Time Processing Engines 7. Widely Used Hadoop Ecosystem Components 8. Designing Applications in Hadoop 9. Real-Time Stream Processing in Hadoop 10. Machine Learning in Hadoop 11. Hadoop in the Cloud 12. Hadoop Cluster Profiling 13. Who Can Do What in Hadoop 14. Network and Data Security 15. Monitoring Hadoop 1. Other Books You May Enjoy Index

HDFS reads and writes


HDFS is a Distributed File Storage system in which we write data and then read that same data. NameNode is a master node that contains metadata information about all the files and DataNode space. The DataNode is a worker node that stores real files. Every read and write request will go through NameNode. HDFS is known for the write once read many pattern, meaning that the file is written in HDFS only once and can be read many times. Files stored in HDFS are not editable but appending new data to a file is allowed. 

In this section, we will cover the internals of HDFS read and write operations, and will see how clients communicate with NameNode and DataNode for read/write operations.

Write workflows

HDFS provides us with the capability to write, read, and delete files from its storage system. You can write data using the command-line utility or by using the programming API interface. However, the write workflow remains the same in both cases. We will go through the internals...

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