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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 consumers. This chapter addresses one of the key functionalities of Kafka message flows. The major focus was on understanding consumer internal working and how the number of consumers in the same group and number of topic partitions can be utilized to increase throughput and latency. We have also covered how to create consumers using consumer APIs and how to handle message offsets in case consumer fails.
We started with Kafka consumer APIs and also covered synchronous and asynchronous consumers and their advantages and disadvantages. We explained how to increase the throughput of a consumer application. We then went through the consumer rebalancer concept and when it gets triggered and how we can create our own rebalancer. We also focused on different consumer patterns that are used in different consumer applications. We focused on...

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