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)

External data lookups

The first question that must be in your mind is why we need external data lookups in the stream processing pipeline. The answer is that sometimes you need to perform operations such as enrichment, data validation, or data filtering on incoming events based on some frequently changing external system data. However, in the streaming design context, these data lookups pose certain challenges. These data lookups may result in increased end-to-end latency as there will be frequent calls to external systems. You cannot hold all the external reference data in-memory as these external datasets are too big to fit in-memory. They also change too frequently, which makes refreshing memory difficult. If these external systems are down, then they will become a bottleneck for streaming solutions.

Keeping these challenges in mind, there are three important factors while...