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Guide to High Performance Distributed Computing Case Studies with Hadoop, Scalding and Spark /

This timely text/reference describes the development and implementation of large-scale distributed processing systems using open source tools and technologies such as Hadoop, Scalding and Spark. Comprehensive in scope, the book presents state-of-the-art material on building high performance distribu...

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Bibliographic Details
Main Authors: Srinivasa, K.G. (Author, http://id.loc.gov/vocabulary/relators/aut), Muppalla, Anil Kumar. (http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2015.
Edition:1st ed. 2015.
Series:Computer Communications and Networks,
Subjects:
Computer communication systems.
Computer programming.
Data mining.
Artificial intelligence.
Optical data processing.
Computer Communication Networks.
Programming Techniques.
Data Mining and Knowledge Discovery.
Artificial Intelligence.
Image Processing and Computer Vision.
Online Access:https://doi.org/10.1007/978-3-319-13497-0
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Table of Contents:
  • Part I: Programming Fundamentals of High Performance Distributed Computing
  • Introduction
  • Getting Started with Hadoop
  • Getting Started with Spark
  • Programming Internals of Scalding and Spark
  • Part II: Case studies using Hadoop, Scalding and Spark
  • Case Study I: Data Clustering using Scalding and Spark
  • Case Study II: Data Classification using Scalding and Spark
  • Case Study III: Regression Analysis using Scalding and Spark
  • Case Study IV: Recommender System using Scalding and Spark.

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