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Learning Hadoop 2

You're reading from  Learning Hadoop 2

Product type Book
Published in Feb 2015
Publisher Packt
ISBN-13 9781783285518
Pages 382 pages
Edition 1st Edition
Languages

Table of Contents (18) Chapters

Learning Hadoop 2
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Introduction 2. Storage 3. Processing – MapReduce and Beyond 4. Real-time Computation with Samza 5. Iterative Computation with Spark 6. Data Analysis with Apache Pig 7. Hadoop and SQL 8. Data Lifecycle Management 9. Making Development Easier 10. Running a Hadoop Cluster 11. Where to Go Next Index

Chapter 4. Real-time Computation with Samza

The previous chapter discussed YARN, and frequently mentioned the breadth of computational models and processing frameworks outside of traditional batch-based MapReduce that it enables on the Hadoop platform. In this chapter and the next, we will explore two such projects in some depth, namely Apache Samza and Apache Spark. We chose these frameworks as they demonstrate the usage of stream and iterative processing and also provide interesting mechanisms to combine processing paradigms. In this chapter we will explore Samza and cover the following topics:

  • What Samza is and how it integrates with YARN and other projects such as Apache Kafka

  • How Samza provides a simple callback-based interface for stream processing

  • How Samza composes multiple stream processing jobs into more complex workflows

  • How Samza supports persistent local state within tasks and how this greatly enriches what it can enable

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