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Muppalla / Srinivasa

Guide to High Performance Distributed Computing

Case Studies with Hadoop, Scalding and Spark

Medium: Buch
ISBN: 978-3-319-38347-7
Verlag: Springer International Publishing
Erscheinungstermin: 06.10.2016
Lieferfrist: bis zu 10 Tage

This timely text/reference describes the development and implementation of large-scale distributed processing systems using open source tools and technologies. Comprehensive in scope, the book presents state-of-the-art material on building high performance distributed computing systems, providing practical guidance and best practices as well as describing theoretical software frameworks. Features: describes the fundamentals of building scalable software systems for large-scale data processing in the new paradigm of high performance distributed computing; presents an overview of the Hadoop ecosystem, followed by step-by-step instruction on its installation, programming and execution; Reviews the basics of Spark, including resilient distributed datasets, and examines Hadoop streaming and working with Scalding; Provides detailed case studies on approaches to clustering, data classification and regression analysis; Explains the process of creating a working recommender system using Scalding and Spark.


Produkteigenschaften


  • Artikelnummer: 9783319383477
  • Medium: Buch
  • ISBN: 978-3-319-38347-7
  • Verlag: Springer International Publishing
  • Erscheinungstermin: 06.10.2016
  • Sprache(n): Englisch
  • Auflage: Softcover Nachdruck of the original 1. Auflage 2015
  • Serie: Computer Communications and Networks
  • Produktform: Kartoniert, Previously published in hardcover
  • Gewicht: 493 g
  • Seiten: 304
  • Format (B x H x T): 155 x 235 x 18 mm
  • Ausgabetyp: Kein, Unbekannt
Autoren/Hrsg.

Autoren

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.