Observatorio de I+D+i UPM

Memorias de investigación
Book chapters:
On the Dynamic Shifting of the MapReduce Timeout
Year:2015
Research Areas
  • Information technology and adata processing
Information
Abstract
MapReduce has become a relevant framework for Big Data processing in the cloud. At large-scale clouds, failures do occur and may incur unwanted performance degradation to Big Data applications. As the reliability of MapReduce depends on how well they detect and handle failures, this book chapter investigates the problem of failure detection in the MapReduce frame­work. The case studies of this contribution reveal that the current static timeout value is not adequate and demonstrate significant variations in the application?s response time with different timeout values. While arguing that comparatively little attention has been devoted to the failure detection in the framework, the chapter presents design ideas for a new adaptive timeout.
International
Si
10.4018/978-1-4666-9767-6
Book Edition
Book Publishing
ISBN
9781466697676
Series
Advances in Data Mining and Database Management (ADMDM)
Book title
Handbook of Research on Managing and Processing Big Data in Cloud Computing
From page
1
To page
22
Participants
  • Autor: Bunjamin Memishi (UPM)
  • Autor: Shadi Ibrahim (INRIA)
  • Autor: Maria de los Santos Perez Hernandez (UPM)
  • Autor: Gabriel Antoniu (INRIA)
Research Group, Departaments and Institutes related
  • Creador: Departamento: Arquitectura y Tecnología de Sistemas Informáticos
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