Bookbot

Guide to High Performance Distributed Computing

Case Studies with Hadoop, Scalding and Spark

Boekbeoordeling

Meer over het boek

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.

Een boek kopen

Guide to High Performance Distributed Computing, M. Srinivasa Sarma

Taal
Jaar van publicatie
2015
product-detail.submit-box.info.binding
(Hardcover)
Zodra we het ontdekt hebben, sturen we een e-mail.

Betaalmethoden

4,0
Zeer goed
1 Beoordelingen

We missen je recensie hier.

Titel
Guide to High Performance Distributed Computing
Ondertitel
Case Studies with Hadoop, Scalding and Spark
Taal
Engels
Uitgever
Springer
Jaar van publicatie
2015
Formaat
Hardcover
Aantal pagina's
321
ISBN10
3319134965
ISBN13
9783319134963
Reeks
Beoordeling
4 van 5
Aantekening
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.