Book Image

Real-Time Big Data Analytics

By : Sumit Gupta, Shilpi Saxena
Book Image

Real-Time Big Data Analytics

By: Sumit Gupta, Shilpi Saxena

Overview of this book

Enterprise has been striving hard to deal with the challenges of data arriving in real time or near real time. Although there are technologies such as Storm and Spark (and many more) that solve the challenges of real-time data, using the appropriate technology/framework for the right business use case is the key to success. This book provides you with the skills required to quickly design, implement and deploy your real-time analytics using real-world examples of big data use cases. From the beginning of the book, we will cover the basics of varied real-time data processing frameworks and technologies. We will discuss and explain the differences between batch and real-time processing in detail, and will also explore the techniques and programming concepts using Apache Storm. Moving on, we’ll familiarize you with “Amazon Kinesis” for real-time data processing on cloud. We will further develop your understanding of real-time analytics through a comprehensive review of Apache Spark along with the high-level architecture and the building blocks of a Spark program. You will learn how to transform your data, get an output from transformations, and persist your results using Spark RDDs, using an interface called Spark SQL to work with Spark. At the end of this book, we will introduce Spark Streaming, the streaming library of Spark, and will walk you through the emerging Lambda Architecture (LA), which provides a hybrid platform for big data processing by combining real-time and precomputed batch data to provide a near real-time view of incoming data.
Table of Contents (17 chapters)
Real-Time Big Data Analytics
About the Authors
About the Reviewer

How and when to use Storm

I am a believer of the fact that the quickest way to get acquainted to a tool or technology is to do it, and we have been doing a lot of theoretical talking so far rather than actually doing it, so let's actually begin the fun. We would start with the basic word count topology, I have lot of experience of using Storm on Linux, and there is a lot of online material available for the same. I have used a Windows VM for execution of the word count topology. Here are a couple of prerequisites:

  • apache-storm-0.9.5-src.

  • JDK 1.6+.

  • Python 2.x. (I figured this out by a little trial and error. My Ubuntu always had Python and it never gave any trouble; for example, the word count uses a Python script for splitting sentences, so I set up Python 3 (the latest version), but later figured out that the compatible one is 2.x.)

  • Maven.

  • Eclipse.

Here we go.

Set up the following environment variables accurately:



  • PATH

The PATH variable should have the path to Python installation...