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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

Using Kafka in Big Data Applications

In the earlier chapters, we covered how Kafka works, what kind of different components Kafka has, and what some of the Kafka tools that we can utilize for some specific use cases are. In this chapter, our focus is on understanding the importance of Kafka in big data applications. Our intention is for you to understand how Kafka can be used in any big data use cases and what are different types of design aspects you should keep in mind while using Kafka in this manner.

Kafka is becoming the standard tool for messaging in big data applications. There are some specific reasons for it. One of the reasons for it is that we can not use databases as the one-stop destination for all. Earlier, due to lack of elegant storage systems, databases tend to be the only solution for any type of data store. If you use a database, over a period of time, the system...

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