In this chapter, we learned about Apache Storm architecture in brief and we also went through the limitations of Storm which motivated Twitter to develop Heron. We also discussed Heron architecture and its components. Later, we went through the API and an example of Storm Kafka integration. We also covered IP Fraud detection use cases and learned how to create a topology.
In the next chapter, we will learn about the Confluent Platform for Apache Kafka, which provides lots of advanced tools and features which we can use with Kafka.
Building Data Streaming Applications with Apache Kafka
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Building Data Streaming Applications with Apache Kafka
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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.
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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
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