The Community for Technology Leaders
2013 IEEE 29th International Conference on Data Engineering (ICDE) (2013)
Brisbane, Australia Australia
Apr. 8, 2013 to Apr. 12, 2013
ISSN: 1063-6382
ISBN: 978-1-4673-4909-3
pp: 1249
A. Aboulnaga , Cheriton Sch. of Comput. Sci., Univ. of Waterloo, Waterloo, ON, Canada
S. Babu , Dept. of Comput. Sci., Duke Univ., Durham, NC, USA
ABSTRACT
Parallel database systems and MapReduce systems are essential components of today's infrastructure for Big Data analytics. These systems process multiple concurrent workloads consisting of complex user requests, where each request is associated with an (explicit or implicit) service level objective.
INDEX TERMS
Resource management, Tutorials, Databases, Educational institutions, Admission control, Processor scheduling, Big data
CITATION

A. Aboulnaga and S. Babu, "Workload management for Big Data analytics," 2013 29th IEEE International Conference on Data Engineering (ICDE 2013)(ICDE), Brisbane, QLD, 2013, pp. 1249.
doi:10.1109/ICDE.2013.6544915
97 ms
(Ver 3.3 (11022016))