Real-time big data analytics: design, process, and analyze large sets of complex data in real time

By:

Gupta, Sumit

Contributor(s):

Saxena, Shilpi [Co author]

Material type: Text

TextSeries: Community experience distilledPublication details: Packt Publishing 2016 United KingdomDescription: xiii, 299p. With indexISBN:

9781784391409

Subject(s):

DDC classification:

005.74 G8R3

Summary: 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. https://prod.packtpub.com/in/big-data-and-business-intelligence/real-time-big-data-analytics

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds
Book	Ahmedabad General Stacks	Non-fiction	005.74 G8R3 (Browse shelf(Opens below))	Available		199265

Total holds: 0

Table of Content

1 Introducing the Big Data Technology Landscape and Analytics Platform
2 Getting Acquainted with Storm
3 Processing Data with Storm
4 Introduction to Trident and Optimizing Storm Performance
5 Getting Acquainted with Kinesis
6 Getting Acquainted with Spark
7 Programming with RDDs
8 SQL Query Engine for Spark – Spark SQL
9 Analysis of Streaming Data Using Spark Streaming
10 Introducing Lambda Architecture

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.

https://prod.packtpub.com/in/big-data-and-business-intelligence/real-time-big-data-analytics

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