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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

Multicluster deployment

Generally, multicluster deployment is used to mitigate some of the risks associated with single cluster deployment. We have mentioned to you, some of those risks in the preceding section. Multicluster deployment can come in two flavors - distributive models and aggregate models.

The distributive model diagram is shown in the following figure. In this model, based on the topics, messages are sent to different Kafka clusters deployed in different data centers. Here, we have chosen to deploy Kafka cluster on Data Center 1 and Data Center 3.

Applications deployed in Data Center 2 can choose to send data to any of the Kafka clusters deployed in Data Center 1 and Data Center 3. They will use different a data center-deployed Kafka cluster depending on the Kafka topic associated with the messages. This kind of message routing can also be done using some intermediate...

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