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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

Logical view of Hadoop in the cloud


The usability of infrastructure in the cloud has been increasing at a rapid speed. The companies who were worrying about adopting the cloud for its computing and storage needs due to security and availability now have enough confidence as there have been lots of improvements on the architecture and features being made by different cloud service providers. Apache Hadoop started with on premises deployment and during the initial years of the Hadoop foundation, the Hadoop infrastructure was mainly set up using self-managed infrastructure. But over the last few years, cloud service providers have given focus to the Hadoop infrastructure and now we have everything that's needed for a big data/Hadoop setup. Today, almost every company moving to big data adaptability is using the cloud for their data storage and infrastructure needs. In this section, we will talk about how the logical architecture for Hadoop looks over the cloud:

  • Ingestion layer: Data ingestion...
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