Book Image

Apache Kafka 1.0 Cookbook

By : Alexey Zinoviev, Raúl Estrada
Book Image

Apache Kafka 1.0 Cookbook

By: Alexey Zinoviev, Raúl Estrada

Overview of this book

Apache Kafka provides a unified, high-throughput, low-latency platform to handle real-time data feeds. This book will show you how to use Kafka efficiently, and contains practical solutions to the common problems that developers and administrators usually face while working with it. This practical guide contains easy-to-follow recipes to help you set up, configure, and use Apache Kafka in the best possible manner. You will use Apache Kafka Consumers and Producers to build effective real-time streaming applications. The book covers the recently released Kafka version 1.0, the Confluent Platform and Kafka Streams. The programming aspect covered in the book will teach you how to perform important tasks such as message validation, enrichment and composition.Recipes focusing on optimizing the performance of your Kafka cluster, and integrate Kafka with a variety of third-party tools such as Apache Hadoop, Apache Spark, and Elasticsearch will help ease your day to day collaboration with Kafka greatly. Finally, we cover tasks related to monitoring and securing your Apache Kafka cluster using tools such as Ganglia and Graphite. If you're looking to become the go-to person in your organization when it comes to working with Apache Kafka, this book is the only resource you need to have.
Table of Contents (18 chapters)
Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Dedication
Preface

Geolocation enricher


Let's remember the Doubloon project requirements for the stream processing app. The customer sees BTC price event happens in the customer's web browser and is dispatched to Kafka via an HTTP event collector. The second step is to enrich the messages with the geolocation information. Remember from the previous chapter that defective messages result in bad data, so they are filtered.

Getting ready

Putting it all together, the specification is to create a stream application that does the following:

  • Reads individual messages from a Kafka topic called raw-messages
  • Validates the message, sending any invalid message to a dedicated Kafka topic called invalid-messages
  • Enriches the message with the geolocation information
  • Writes the enriched messages in a Kafka topic called valid-messages

All this is detailed in the following diagram and is the second version of the stream processing application:

Figure 4.1: The processing application reads events from the raw-messages topic, validates...