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

Guide to High Performance Distributed Computing Case Studies with Hadoop, Scalding and Spark / by K.G. Srinivasa, Anil Kumar Muppalla.

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), Muppalla, Anil Kumar (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2015.
Edition:1st ed. 2015.
Series:Computer Communications and Networks,
Springer eBook Collection.
Subjects:
Computer communication systems.
Computer programming.
Data mining.
Artificial intelligence.
Optical data processing.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
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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