Mastering Apache Storm

Key Features

• Exploit the various real-time processing functionalities offered by Apache Storm such as parallelism, data partitioning, and more
• Integrate Storm with other Big Data technologies like Hadoop, HBase, and Apache Kafka
• An easy-to-understand guide to effortlessly create distributed applications with Storm

Book Description

Apache Storm is a real-time Big Data processing framework that processes large amounts of data reliably, guaranteeing that every message will be processed. Storm allows you to scale your data as it grows, making it an excellent platform to solve your big data problems. This extensive guide will help you understand right from the basics to the advanced topics of Storm.

The book begins with a detailed introduction to real-time processing and where Storm fits in to solve these problems. You’ll get an understanding of deploying Storm on clusters by writing a basic Storm Hello World example. Next we’ll introduce you to Trident and you’ll get a clear understanding of how you can develop and deploy a trident topology. We cover topics such as monitoring, Storm Parallelism, scheduler and log processing, in a very easy to understand manner. You will also learn how to integrate Storm with other well-known Big Data technologies such as HBase, Redis, Kafka, and Hadoop to realize the full potential of Storm.

With real-world examples and clear explanations, this book will ensure you will have a thorough mastery of Apache Storm. You will be able to use this knowledge to develop efficient, distributed real-time applications to cater to your business needs.

What you will learn

• Understand the core concepts of Apache Storm and real-time processing
• Follow the steps to deploy multiple nodes of Storm Cluster
• Create Trident topologies to support various message-processing semantics
• Make your cluster sharing effective using Storm scheduling
• Integrate Apache Storm with other Big Data technologies such as Hadoop, HBase, Kafka, and more
• Monitor the health of your Storm cluster

Table of Contents

Chapter 1. Real-Time Processing And Storm Introduction
Chapter 2. Storm Deployment, Topology Development, And Topology Options
Chapter 3. Storm Parallelism And Data Partitioning
Chapter 4. Trident Introduction
Chapter 5. Trident Topology And Uses
Chapter 6. Storm Scheduler
Chapter 7. Monitoring Of Storm Cluster
Chapter 8. Integration Of Storm And Kafka
Chapter 9. Storm And Hadoop Integration
Chapter 10. Storm Integration With Redis, Elasticsearch, And Hbase
Chapter 11. Apache Log Processing With Storm
Chapter 12. Twitter Tweet Collection And Machine Learning