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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

Summary


In this chapter, we learned about detailed architecture and uses of a few widely used Hadoop components, such as Apache Pig, Apache HBase, Apache Kafka, and Apache Flume. We have covered a few examples around writing custom UDF in Apache Pig, writing custom source, sink, and interceptor in Apache Flume, writing producer and consumer in Apache Kafka, and so on. Our focus was also to see how we can install and set up these componentS for practical use. 

In the next chapter, our focus will be to look into some advanced topics in Big Data and cover some useful fundamental techniques and concepts, such as compression, file format serialization techniques, and some important pillars of data governance. 

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