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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

Introducing Kafka Connect

Kafka Connect is used to copy data into and out of Kafka. There are already a lot of tools available to move data from one system to another system. You would find many use cases where you want to do real-time analytics and batch analytics on the same data. Data can come from different sources but finally may land into the same category or type.

We may want to bring this data to Kafka topics and then pass it to a real-time processing engine or store it for batch processing. If you closely look at the following figure, there are different processes involved:

Kafka Connect

Let's look into each component in detail:

  • Ingestion in Kafka: Data is inserted into Kafka topic from different sources, and most of the time, the type of sources are common. For example you may want to insert server logs into Kafka topics, or insert all records from the database...
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