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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

Common messaging publishing patterns

Applications may have different requirements of producer--a producer that does not care about acknowledgement for the message they have sent or a producer that cares about acknowledgement but the order of messages does not matter. We have different producer patterns that can be used for application requirement. Let's discuss them one by one:

  • Fire-and-forget: In this pattern, producers only care about sending messages to Kafka queues. They really do not wait for any success or failure response from Kafka. Kafka is a highly available system and most of the time, messages would be delivered successfully. However, there is some risk of message loss in this pattern. This kind of pattern is useful when latency has to be minimized to the lowest level possible and one or two lost messages does not affect the overall system functionality. To use...
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