Book Image

Mastering Apache Storm

By : Ankit Jain
Book Image

Mastering Apache Storm

By: Ankit Jain

Overview of this book

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.
Table of Contents (19 chapters)
Title Page
About the Author
About the Reviewers
Customer Feedback

Deploy the Kafka topology on Storm cluster

The deployment of Kafka and Storm integration topology on the Storm cluster is similar to the deployment of other topologies. We need to set the number of workers and the maximum spout pending Storm config and we need to use the submitTopology method of StormSubmitter to submit the topology on the Storm cluster.

Now, we need to build the topology code as mentioned in the following steps to create a JAR of the Kafka Storm integration topology:

  1. Go to project home.
  2. Execute the command:
mvn clean install

The output of the preceding command is as follows:

------------------------------------------------------------------ -----
[INFO] ----------------------------------------------------------- -----
[INFO] ----------------------------------------------------------- -----
[INFO] Total time: 58.326s
[INFO] Finished at:
[INFO] Final Memory: 14M/116M
[INFO] ----------------------------------------------------------- -----
  1. Now, copy the Kafka...