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

Chapter 11. Apache Log Processing with Storm

In the previous chapter, we covered how we can integrate Storm with Redis, HBase, Esper and Elasticsearch.

In this chapter, we are covering the most popular use case of Storm, which is log processing.

This chapter covers the following major sections:

  • Apache log processing elements
  • Installation of Logstash
  • Configuring Logstash to produce the Apache log into Kafka
  • Splitting the Apache log file
  • Calculating the country name, operating system type, and browser type
  • Identifying the search key words of your website
  • Persisting the process data
  • Kafka spout and defining the topology
  • Deploying the topology
  • Storing the data into Elasticsearch and reporting