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

Architectural overview of Kinesis

In this section, we will talk about the overall architecture and various components of Kinesis. This section will help us to understand the terminology and various components of Amazon Kinesis.

Benefits and use cases of Amazon Kinesis

Amazon Kinesis is a service provided by Amazon in the cloud that allows developers to consume data from multiple data sources, such as streaming news feeds, financial data, social media applications, logs, or sensor data, and subsequently write applications that respond to these real-time data feeds. The data received from Kinesis can be further consumed, transformed, and finally persisted in various data stores such as Amazon S3, Amazon DynamoDB, Amazon Redshift, or any other NoSQL database either in its raw form or filtered according to predefined business rules.

Kinesis can be integrated with real-time dashboards and business intelligence software, which thereby enables the scripting of alerts and decision making protocols...