An Adaptive and Memory Efficient Sampling Mechanism for Partitioning in MapReduce-Reference-Cited by-同舟云学术

An Adaptive and Memory Efficient Sampling Mechanism for Partitioning in MapReduce

Published:2013-11-08 Issue:3 Volume:43 Page:489-507
ISSN:0885-7458
Container-title:International Journal of Parallel Programming
language:en
Short-container-title:Int J Parallel Prog

Author:

Slagter Kenn,Hsu Ching-Hsien,Chung Yeh-Ching

Publisher

Springer Science and Business Media LLC

Subject

Information Systems,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s10766-013-0288-z.pdf

Reference28 articles.

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3. Chang, F., Dean, J., Ghemawat, S., Hsieh, W.C., Wallach, D.A., Burrows, M., Chandra, T., Fikes, A., Gruber, R.E.: Bigtable: a distributed storage system for structured data. In: 7th USENIX Symposium on Operating Systems Design and Implementation, pp. 205–218 (2006)

4. Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters. Commun. ACM 51, 107–113 (2008)

5. Fadika, Z., Govindaraju, M.: Delma: dynamically elastic mapreduce framework for cpu-intensive applications. In: IEEE/ACM International Symposium on Cluster, Cloud and Grid, Computing, pp.454–463 (2011)

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