Guest Editorial: The Parallel Storage, Processing and Analysis for Big Data
Author:
Publisher
Springer Science and Business Media LLC
Subject
Information Systems,Theoretical Computer Science,Software
Link
http://link.springer.com/article/10.1007/s10766-016-0475-9/fulltext.html
Reference17 articles.
1. Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters. Commun. ACM 51(1), 107–113 (2008)
2. Jiang, D., Ooi, B.C., Shi, L., Wu, S.: The performance of MapReduce: an in-depth study. Proc. VLDB Endow. 3(1), 472–483 (2010)
3. Panda, B., Herbach, J.S., Basu, S., Bayardo, R.J.: PLANET: massively parallel learning of tree ensembles with MapReduce. Proc. VLDB Endow. 2(2), 1426–1437 (2009)
4. Wang, Q., Zhao, J., Gong, D., Shen, Y., Li, M., Lei, Y.: Parallelizing convolutional neural networks for action event recognition in surveillance videos. Int. J. Parallel Prog. (2016). doi: 10.1007/s10766-016-0451-4
5. Liu, Y., Xu, L., Li, M.: The parallelization of back propagation neural network in MapReduce and Spark. Int. J. Parallel Prog. (2016). doi: 10.1007/s10766-016-0401-1
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