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Building Data Streaming Applications with Apache Kafka

You're reading from   Building Data Streaming Applications with Apache Kafka Design, develop and streamline applications using Apache Kafka, Storm, Heron and Spark

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Product type Paperback
Published in Aug 2017
Publisher Packt
ISBN-13 9781787283985
Length 278 pages
Edition 1st Edition
Tools
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Authors (2):
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Chanchal Singh Chanchal Singh
Author Profile Icon Chanchal Singh
Chanchal Singh
Manish Kumar Manish Kumar
Author Profile Icon Manish Kumar
Manish Kumar
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Messaging Systems FREE CHAPTER 2. Introducing Kafka the Distributed Messaging Platform 3. Deep Dive into Kafka Producers 4. Deep Dive into Kafka Consumers 5. Building Spark Streaming Applications with Kafka 6. Building Storm Applications with Kafka 7. Using Kafka with Confluent Platform 8. Building ETL Pipelines Using Kafka 9. Building Streaming Applications Using Kafka Streams 10. Kafka Cluster Deployment 11. Using Kafka in Big Data Applications 12. Securing Kafka 13. Streaming Application Design Considerations

Building Streaming Applications Using Kafka Streams

In the previous chapter, you learned about Kafka Connect and how it makes a user's job simple when it comes to importing and exporting data from Kafka. You also learned how Kafka Connect can be used as an extract and load processor in the ETL pipeline. In this chapter, we will focus on Kafka Stream, which is a lightweight streaming library used to develop a streaming application that works with Kafka. Kafka Stream can act as a transformer in the ETL phase.

We will cover the following topics in this chapter:

  • Introduction to Kafka Stream
  • Kafka Stream architecture
  • Advantages of using Kafka Stream
  • Introduction to KStream and KTable
  • Use case example
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