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)

Role of Zookeeper

We have already talked a lot about Zookeeper in the previous sections. Zookeeper plays a very important role in Kafka architecture and it is very important for you to understand how it records the Kafka cluster state. Therefore, we are dedicating a separate section to the role of Zookeeper in the Kafka cluster. Kafka cannot work without Zookeeper. Kafka uses Zookeeper for the following functions:

  • Choosing a controller: The controller is one of the brokers responsible for partition management with respect to leader election, topic creation, partition creation, and replica management. When a node or server shuts down, Kafka controllers elect partition leaders from followers. Kafka uses Zookeeper's metadata information to elect a controller. Zookeeper ensures that a new controller is elected in case the current controller crashes.
  • Brokers metadata: Zookeeper...