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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

Building ETL Pipelines Using Kafka

In the previous chapter, we learned about Confluent Platform. We covered its architecture in detail and discussed its components. You also learned how to export data from Kafka to HDFS using different tools. We went through Camus, Goblin, Flume, and Kafka Connect to cover different ways of bringing data to HDFS. We also recommend you try all the tools discussed in the last chapter to understand how they work. Now we will look into creating an ETL pipeline using these tools and look more closely at Kafka Connect use cases and examples.

In this chapter, we will cover Kafka Connect in detail. The following are the topics we will cover:

  • Use of Kafka in the ETL pipeline
  • Introduction to Kafka Connect
  • Kafka Connect architecture
  • Deep dive into Kafka Connect
  • Introductory example of Kafka Connect
  • Common use cases
...
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