MapReduce: differenze tra le versioni

Versione delle 13:32, 12 mar 2019

Versione delle 23:17, 2 mag 2019

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*{{en}} [http://pages.cs.wisc.edu/~dekruijf/docs/mapreduce-cell.pdf "MapReduce for the Cell B.E. Architecture"] — paper by Marc de Kruijf and Karthikeyan Sankaralingam; from [[University of Wisconsin–Madison]]

*{{en}} [https://web.archive.org/web/20090326060100/http://www.cse.ust.hk/catalac/users/saven/GPGPU/MapReduce/PACT08/171.pdf "Mars: A MapReduce Framework on Graphics Processors"] — paper by Bingsheng He, Wenbin Fang, Qiong Luo, Naga K. Govindaraju, Tuyong Wang; from [[Hong Kong University of Science and Technology]]; published in Proc. PACT 2008. It presents the design and implementation of MapReduce on graphics processors.

*{{en}} [httphttps://portal.acm.org/citation.cfm?doid=1247480.1247602 "Map-Reduce-Merge: Simplified Relational Data Processing on Large Clusters"] — paper by Hung-Chih Yang, Ali Dasdan, Ruey-Lung Hsiao, and D. Stott Parker; from [[Yahoo]] and [[UCLA]]; published in Proc. of ACM SIGMOD, pp. 1029–1040, 2007. (This paper shows how to extend MapReduce for relational data processing.)

*{{en}} FLuX: the [http://citeseer.ist.psu.edu/647742.html Fault-tolerant], [http://citeseer.ist.psu.edu/546646.html Load Balancing] eXchange operator from [[UC Berkeley]] provides an integration of partitioned parallelism with process pairs. This results in a more pipelined approach than Google's MapReduce with instantaneous failover, but with additional implementation cost.

*{{en}} [http://infolab.stanford.edu/~ullman/pub/mapred.pdf "A New Computation Model for Rack-Based Computing"] — paper by Foto N. Afrati; Jeffrey D. Ullman; from [[Stanford University]]; Not published as of Nov 2009. This paper is an attempt to develop a general model in which one can compare algorithms for computing in an environment similar to what map-reduce expects.

*{{en}} [httphttps://portal.acm.org/beta/citation.cfm?id=1723112.1723129 FPMR: MapReduce framework on FPGA] -- paper by Yi Shan, Bo Wang, Jing Yan, Yu Wang, Ningyi Xu, Huazhong Yang (2010), in FPGA '10, Proceedings of the 18th annual ACM/SIGDA international symposium on Field programmable gate arrays.

*{{en}} [https://web.archive.org/web/20110707024252/http://ppi.fudan.edu.cn/_media/publications%3Bostrich-pact10.pdf?id=rong_chen&cache=cache "Tiled-MapReduce: Optimizing Resource Usages of Data-parallel Applications on Multicore with Tiling"] -- paper by Rong Chen, Haibo Chen and Binyu Zang from [[Fudan University]]; published in Proc. PACT 2010. It presents the Tiled-MapReduce programming model which optimizes resource usages of MapReduce applications on multicore environment using tiling strategy.

*{{en}} [httphttps://dx.doi.org/10.1016/j.jpdc.2010.12.004 "Scheduling divisible MapReduce computations "] -- paper by Joanna Berlińska from [[Adam Mickiewicz University]] and Maciej Drozdowski from [[Poznan University of Technology]]; Journal of Parallel and Distributed Computing 71 (2011) 450-459, doi:10.1016/j.jpdc.2010.12.004. It presents scheduling and performance model of MapReduce.

; Libri

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;Educational courses

*{{en}}[httphttps://code.google.com/edu/submissions/mapreduce-minilecture/listing.html Cluster Computing and MapReduce] course from [httphttps://code.google.com/edu/ Google Code University] contains video lectures and related course materials from a series of lectures that was taught to Google software engineering interns during the Summer of 2007.

*{{en}} [httphttps://code.google.com/edu/submissions/mapreduce/listing.html MapReduce in a Week] course from [httphttps://code.google.com/edu/ Google Code University] contains a comprehensive introduction to MapReduce including lectures, reading material, and programming assignments.

*{{en}} [http://mr.iap.2008.googlepages.com/ MapReduce course], taught by engineers of [[Google]] Boston, part of 2008 Independent Activities Period at [[Massachusetts Institute of Technology|MIT]].