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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

Summary

This concludes our section on Kafka producers. This chapter addresses one of the key functionalities of Kafka message flows. The major emphasis in this chapter was for you to understand how Kafka producers work at the logical level and how messages are passed from Kafka producers to Kafka queues. This was covered in the Kafka Internals section. This is an important section for you to understand before you learn how to code with Kafka APIs. Unless you understand the logical working of Kafka producers, you will not be able to do justice to producer application technical designing.

We discussed Kafka Producer APIs and different components around it such as custom practitioners. We gave both Java and Scala examples as both languages are heavily used in enterprise applications. We would suggest you try all those examples on your consoles and get a better grasp of how Kafka...

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