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Dylan Scott

Kafka in Action

Edition 1

Kafka in Action

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Best.Nr.
978-1-6172-9523-2
Erscheint im
Januar 2021
Sprache
Englisch
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nach Erscheinungstermin
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€ 41,72
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Kafka in Action is a practical, hands-on guide to building Kafka-based data pipelines. Filled with real-world use cases and scenarios, this book probes Kafka's most common use cases, ranging from simple logging through managing streaming data systems for message routing, analytics, and more.

 

In systems that handle big data, streaming data, or fast data, it's important to get your data pipelines right. Apache Kafka is a wicked-fast distributed streaming platform that operates as more than just a persistent log or a flexible message queue.

 

Key Features

·   Understanding Kafka's concepts

·   Implementing Kafka as a message queue

·   Setting up and executing basic ETL tasks

·   Recording and consuming streaming data

·   Working with Kafka producers and consumers from Java applications

·   Using Kafka as part of a large data project team

·   Performing Kafka developer and admin tasks

 

Written for intermediate Java developers or data engineers. No prior knowledge of Kafka is required.

 

About the technology

Apache Kafka is a distributed streaming platform for logging and streaming data between services or applications. With Kafka, it's easy to build applications that can act on or react to data streams as they flow through your system. Operational data monitoring, large scale message processing, website activity tracking, log aggregation, and more are all possible with Kafka.

 

Dylan Scott is a software developer with over ten years of experience in Java and Perl. His experience includes implementing Kafka as a messaging system for a large data migration, and he uses Kafka in his work in the insurance industry.



Kafka in Action is a practical, hands-on guide to building Kafka-based data pipelines. Filled with real-world use cases and scenarios, this book probes Kafka's most common use cases, ranging from simple logging through managing streaming data systems for message routing, analytics, and more.

 

In systems that handle big data, streaming data, or fast data, it's important to get your data pipelines right. Apache Kafka is a wicked-fast distributed streaming platform that operates as more than just a persistent log or a flexible message queue.

 

Key Features

·   Understanding Kafka's concepts

·   Implementing Kafka as a message queue

·   Setting up and executing basic ETL tasks

·   Recording and consuming streaming data

·   Working with Kafka producers and consumers from Java applications

·   Using Kafka as part of a large data project team

·   Performing Kafka developer and admin tasks

 

Written for intermediate Java developers or data engineers. No prior knowledge of Kafka is required.

 

About the technology

Apache Kafka is a distributed streaming platform for logging and streaming data between services or applications. With Kafka, it's easy to build applications that can act on or react to data streams as they flow through your system. Operational data monitoring, large scale message processing, website activity tracking, log aggregation, and more are all possible with Kafka.

 

Dylan Scott is a software developer with over ten years of experience in Java and Perl. His experience includes implementing Kafka as a messaging system for a large data migration, and he uses Kafka in his work in the insurance industry.

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