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)

Message consumers

The consumer is any one who subscribes for topics in Kafka. Each consumer belongs to a consumer group and some consumer groups contains multiple consumers. Consumers are an interesting part of Kafka and we will cover them in detail.

Two consumers from the same group cannot consume message from a similar partition because it will lead to the message being consumed out of order. However, consumers from the same group can consume message from a different partition of the same topic simultaneously. Similarly, consumers from a different group can consume messages from the same partition in parallel without affecting the order of consumption.

So, it's clear that groups play an important role; in Kafka's initial version, Zookeeper was used for group management, but in the latest version, Kafka has its own group protocol built in. One of the brokers will act...