Book Image

Building Data Streaming Applications with Apache Kafka

By : Chanchal Singh, Manish Kumar
Book Image

Building Data Streaming Applications with Apache Kafka

By: Chanchal Singh, Manish Kumar

Overview of this book

Apache Kafka is a popular distributed streaming platform that acts as a messaging queue or an enterprise messaging system. It lets you publish and subscribe to a stream of records, and process them in a fault-tolerant way as they occur. This book is a comprehensive guide to designing and architecting enterprise-grade streaming applications using Apache Kafka and other big data tools. It includes best practices for building such applications, and tackles some common challenges such as how to use Kafka efficiently and handle high data volumes with ease. This book first takes you through understanding the type messaging system and then provides a thorough introduction to Apache Kafka and its internal details. The second part of the book takes you through designing streaming application using various frameworks and tools such as Apache Spark, Apache Storm, and more. Once you grasp the basics, we will take you through more advanced concepts in Apache Kafka such as capacity planning and security. By the end of this book, you will have all the information you need to be comfortable with using Apache Kafka, and to design efficient streaming data applications with it.
Table of Contents (14 chapters)

Common messaging publishing patterns

Applications may have different requirements of producer--a producer that does not care about acknowledgement for the message they have sent or a producer that cares about acknowledgement but the order of messages does not matter. We have different producer patterns that can be used for application requirement. Let's discuss them one by one:

  • Fire-and-forget: In this pattern, producers only care about sending messages to Kafka queues. They really do not wait for any success or failure response from Kafka. Kafka is a highly available system and most of the time, messages would be delivered successfully. However, there is some risk of message loss in this pattern. This kind of pattern is useful when latency has to be minimized to the lowest level possible and one or two lost messages does not affect the overall system functionality. To use...