
Guide to High Performance Distributed Computing
Case Studies with Hadoop, Scalding and Spark
Springer (Publisher)
Published on 6. October 2016
Book
Paperback/Softback
XVII, 304 pages
978-3-319-38347-7 (ISBN)
Description
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.
More details
Series
Edition
Softcover reprint of the original 1st ed. 2015
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Primary & secondary/elementary & high school
Illustrations
43 s/w Abbildungen
XVII, 304 p. 43 illus.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 18 mm
Weight
493 gr
ISBN-13
978-3-319-38347-7 (9783319383477)
DOI
10.1007/978-3-319-13497-0
Schweitzer Classification
Other editions
Additional editions

K.G. Srinivasa | Anil Kumar Muppalla
Guide to High Performance Distributed Computing
Case Studies with Hadoop, Scalding and Spark
Book
03/2015
Springer
€53.49
Shipment within 10-15 days
Content
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.