We walked you through some of the aspects of using Kafka in big data applications. By the end of this chapter, you should have clear understanding of how to use Kafka in big data Applications. Volume is one of the important aspects of any big data application. Therefore, we have a dedicated section for it in this chapter, because you are required to pay attention to granular details while managing high volumes in Kafka. Delivery semantics is another aspect you should keep in mind. Based on your choice of delivery semantics, your processing logic would differ. Additionally, we covered some of the best ways of handling failures without any data loss and some of the governance principles that can be applied while using Kafka in big data pipeline. We gave you an understanding of how to monitor Kafka and what some of the useful Kafka matrices are. You learned a good detail...
Building Data Streaming Applications with Apache Kafka
By :
Building Data Streaming Applications with Apache Kafka
By:
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.
Related Content you might be interested in
Current Title:
Building Data Streaming Applications with Apache Kafka
Table of Contents (14 chapters)
Preface
Free Chapter
Introduction to Messaging Systems
Introducing Kafka the Distributed Messaging Platform
Deep Dive into Kafka Producers
Deep Dive into Kafka Consumers
Building Spark Streaming Applications with Kafka
Building Storm Applications with Kafka
Using Kafka with Confluent Platform
Building ETL Pipelines Using Kafka
Building Streaming Applications Using Kafka Streams
Kafka Cluster Deployment
Using Kafka in Big Data Applications
Securing Kafka
Customer Reviews