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

Introduction to Hadoop

Apache Hadoop is an open source platform for developing and deploying big data applications. It was initially developed at Yahoo! based on the MapReduce and Google File System papers published by Google. Over the past few years, Hadoop has become the flagship big data platform.

In this section, we will discuss the key components of a Hadoop cluster.

Hadoop Common

This is the base library on which other Hadoop modules are based. It provides an abstraction for OS and filesystem operations so that Hadoop can be deployed on a variety of platforms.

Hadoop Distributed File System

Commonly known as HDFS, the Hadoop Distributed File System is a scalable, distributed, fault-tolerant filesystem. HDFS acts as the storage layer of the Hadoop ecosystem. It allows the sharing and storage of data and application code among the various nodes in a Hadoop cluster.

The following are the key assumptions taken while designing HDFS:

  • It should be deployable on a cluster of commodity hardware.
  • Hardware...