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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

Kafka message delivery semantics

Semantic guarantees in Kafka need to be understood from the perspective of producers and consumers.

At a very high level, message flows in Kafka comprise the producer writing messages that are read by consumers to deliver it to the message processing component. In other words, producer message delivery semantics impact the way messages are received by the consumer.

For example, suppose the producer component does not receive successful acks from brokers because of network connectivity. In that case, the producer re-sends those messages even if the broker has received them. This results in duplicate messages sent to the consumer application. Therefore, it is important to understand that the way messages are delivered by the producer effects the manner in which the consumer would receive the messages. This would ultimately have impact on applications...

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