Apache Kafka Quick Start Guide: Leverage Apache Kafka 2.0 to simplify real-time data processing for distributed applications

Apache Kafka Quick Start Guide: Leverage Apache Kafka 2.0 to simplify real-time data processing for distributed applicationsReviews
Author: Raúl Estrada
Pub Date: 2018
ISBN: 978-1788997829
Pages: 186
Language: English
Format: PDF/EPUB
Size: 20 Mb

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Process large volumes of data in real-time while building high performance and robust data stream processing pipeline using the latest Apache Kafka 2.0
Apache Kafka is a great open source platform for handling your real-time data pipeline to ensure high-speed filtering and pattern matching on the ?y. In this book, you will learn how to use Apache Kafka for efficient processing of distributed applications and will get familiar with solving everyday problems in fast data and processing pipelines.
This book focuses on programming rather than the configuration management of Kafka clusters or DevOps. It starts off with the installation and setting up the development environment, before quickly moving on to performing fundamental messaging operations such as validation and enrichment.
Here you will learn about message composition with pure Kafka API and Kafka Streams. You will look into the transformation of messages in different formats, such asext, binary, XML, JSON, and AVRO. Next, you will learn how to expose the schemas contained in Kafka with the Schema Registry. You will then learn how to work with all relevant connectors with Kafka Connect. While working with Kafka Streams, you will perform various interesting operations on streams, such as windowing, joins, and aggregations. Finally, through KSQL, you will learn how to retrieve, insert, modify, and delete data streams, and how to manipulate watermarks and windows.
What you will learn

  • How to validate data with Kafka
  • Add information to existing data ?ows
  • Generate new information through message composition
  • Perform data validation and versioning with the Schema Registry
  • How to perform message Serialization and Deserialization
  • How to perform message Serialization and Deserialization
  • Process data streams with Kafka Streams
  • Understand the duality between tables and streams with KSQL