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)

Out-of-order events

This is one of the key problems with any unbound data stream. Sometimes an event arrives so late that events that should have been processed after that out of order event are processed first. Events from varied remote discrete sources may be produced at the same time and, due to network latency or some other problem, some of them are delayed. The challenge with out-of-order events is that as they come very late, processing them involves data lookups on relevant datasets.

Moreover, it is very difficult to determine the conditions that help you decide if an event is an out-of-order event. In other words, it is difficult to determine if all events in each window have been received or not. Moreover, processing these out-of-order events poses risks of resource contentions. Other impacts could be increase in latency and overall system performance degradation.

Keeping...