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Learning Real-time Processing with Spark Streaming

Posted By: AlenMiler
Learning Real-time Processing with Spark Streaming

Learning Real-time Processing with Spark Streaming by Sumit Gupta
English | 28 Sept. 2015 | ISBN: 1783987669 | 202 Pages | True AZW3 (Kindle)/(EPUB/PDF conv) | 12.28 MB

This book is intended for big data developers with basic knowledge of Scala but no knowledge of Spark. It will help you grasp the basics of developing real-time applications with Spark and understand efficient programming of core elements and applications.

Building scalable and fault-tolerant streaming applications made easy with Spark streaming

About This Book

Process live data streams more efficiently with better fault recovery using Spark Streaming
Implement and deploy real-time log file analysis
Learn about integration with Advance Spark Libraries – GraphX, Spark SQL, and MLib.

What You Will Learn

Install and configure Spark and Spark Streaming to execute applications
Explore the architecture and components of Spark and Spark Streaming to use it as a base for other libraries
Process distributed log files in real-time to load data from distributed sources
Apply transformations on streaming data to use its functions
Integrate Apache Spark with the various advance libraries like MLib and GraphX
Apply production deployment scenarios to deploy your application

In Detail

Using practical examples with easy-to-follow steps, this book will teach you how to build real-time applications with Spark Streaming.

Starting with installing and setting the required environment, you will write and execute your first program for Spark Streaming. This will be followed by exploring the architecture and components of Spark Streaming along with an overview of libraries/functions exposed by Spark. Next you will be taught about various client APIs for coding in Spark by using the use-case of distributed log file processing. You will then apply various functions to transform and enrich streaming data. Next you will learn how to cache and persist datasets. Moving on you will integrate Apache Spark with various other libraries/components of Spark like Mlib, GraphX, and Spark SQL. Finally, you will learn about deploying your application and cover the different scenarios ranging from standalone mode to distributed mode using Mesos, Yarn, and private data centers or on cloud infrastructure.

Style and approach

A Step-by-Step approach to learn Spark Streaming in a structured manner, with detailed explanation of basic and advance features in an easy-to-follow Style. Each topic is explained sequentially and supported with real world examples and executable code snippets that appeal to the needs of readers with the wide range of experiences.

Books in these formats look like real PDF, with good pictures and tables!
You can download on your any Kindle devices (Kindle Paperwhite, Kindle Fire HDX, Kindle Voyage, Kindle Keyboard, Kindle Wireless) and then open the eBook to read.
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