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Real-Time Big Data Analytics

You're reading from   Real-Time Big Data Analytics Design, process, and analyze large sets of complex data in real time

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Product type Paperback
Published in Feb 2016
Publisher
ISBN-13 9781784391409
Length 326 pages
Edition 1st Edition
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Author (1):
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Shilpi Saxena Shilpi Saxena
Author Profile Icon Shilpi Saxena
Shilpi Saxena
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Table of Contents (12) Chapters Close

Preface 1. Introducing the Big Data Technology Landscape and Analytics Platform FREE CHAPTER 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 Index

An overview of Storm

If someone would ask me to describe Storm in a line, I would use the well-known statement, "Storm is actually Hadoop of real time." Hadoop provides the solution to the volume dimension of Big Data, but it's essentially a batch processing platform. It doesn't come with speed and immediate results/analysis. Though Hadoop has been a turning point for the data storage and computation regime, it cannot be a solution to a problem requiring real-time analysis and results.

Storm addresses the velocity aspect of Big Data. This framework provides the capability to execute distributed computations at lightning fast speed in real-time streaming data. It's a widely used solution to provide real-time alerts and analytics over high velocity streaming data. Storm is a project that's now adopted by Apache. It is proven and known for its capabilities; being under the Apache canopy, it is free and open source. It is a distributed compute engine, which is...

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