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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
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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

Kafka Stream architecture 

Kafka Streams internally uses the Kafka producer and consumer libraries. It is tightly coupled with Apache Kafka and allows you to leverage the capabilities of Kafka to achieve data parallelism, fault tolerance, and many other powerful features.

In this section, we will discuss how Kafka Stream works internally and what the different components involved in building Stream applications using Kafka Streams are. The following figure is an internal representation of the working of Kafka Stream:

Kafka Stream architecture

Stream instance consists of multiple tasks, where each task processes non overlapping subsets of the record. If you want to increase parallelism, you can simply add more instances, and Kafka Stream will auto distribute work among different instances.

Let's discuss a few important components seen in the previous figure:

  • Stream...
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