From Gilles Fedak

Main: MarpReduceClass

Mini Course on MapReduce Runtime Environment

I propose a course on MapReduce Environments: Design, Performance, Optimizations. It covers the basic design of the runtime environments, which implements the MapReduce programming model; Hadoop being the most famous one. Then, several research challenges and results are presented (task management, outliers, greener mapreduce). Finally, we introduce some of the results we obtained based on our research around MapReduce for Internet Computing.

This mini course has been presented at the following venue :

Additional Material

MapReduce: Simplified Data Processing on Large Clusters Jeffrey Dean and Sanjay Ghemawat, in OSDI’04: Sixth Symposium on Operating System Design and Implementation, San Francisco, CA, December, 2004.

Improving MapReduce Performance in Heterogeneous Environments. Zaharia, M., Konwinski, A., Joseph, A. D., Katz, R. and Stoica, I. in OSDI’08: Sixth Symposium on Operating System Design and Implementation, San Diego, CA, December, 2008.

Reining in the Outliers in Map-Reduce Clusters using Mantri Ananthanarayanan, G., Kandula, S., Greenberg, A. G., Stoica, I., Lu, Y., Saha, B., & Harris, E. (2010, October). . In OSDI (Vol. 10, No. 1, p. 24).

Moon: Mapreduce on opportunistic environments Lin, H., Ma, X., Archuleta, J., Feng, W. C., Gardner, M., & Zhang, Z. (2010, June). . In Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing (pp. 95-106). ACM.

Towards MapReduce for Desktop Grids B. Tang, M. Moca, S. Chevalier, H. He, G. Fedak, in Proceedings of the Fifth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing 3GPCIC, Fukuoka, Japan, Novembre 2010

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