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Michaelmalak (talk | contribs) Undid revision 1223249519 by JohnPritchard (talk) cite does not appear to be about map/reduce even though it contains both those words in the title |
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==Uses==
MapReduce is useful in a wide range of applications, including distributed pattern-based searching, distributed sorting, web link-graph reversal, Singular Value Decomposition,<ref>{{cite web |last1=Bosagh Zadeh|first1=Reza|last2=Carlsson|first2=Gunnar|title=Dimension Independent Matrix Square Using MapReduce |website=Stanford University |url=https://stanford.edu/~rezab/papers/dimsum.pdf|access-date=12 July 2014|bibcode=2013arXiv1304.1467B|year=2013|arxiv=1304.1467}}</ref> web access log stats, [[inverted index]] construction, [[document clustering]], [[machine learning]],<ref name="mrml">{{cite web| url=http://www.willowgarage.com/map-reduce-machine-learning-multicore| title=Map-Reduce for Machine Learning on Multicore|first1=Andrew Y. |last1=Ng |first2=Gary |last2=Bradski |first3=Cheng-Tao |last3=Chu |first4=Kunle |last4=Olukotun |first5=Sang Kyun |last5=Kim |first6=Yi-An |last6=Lin |first7=YuanYuan |last7=Yu| publisher=NIPS 2006| year=2006}}</ref> and [[statistical machine translation]]. Moreover, the MapReduce model has been adapted to several computing environments like multi-core and many-core systems,<ref name="evalMR">{{Cite book | doi = 10.1109/HPCA.2007.346181| chapter = Evaluating MapReduce for Multi-core and Multiprocessor Systems| title = 2007 IEEE 13th International Symposium on High Performance Computer Architecture| pages = 13| year = 2007| last1 = Ranger | first1 = C. | last2 = Raghuraman | first2 = R. | last3 = Penmetsa | first3 = A. | last4 = Bradski | first4 = G. | last5 = Kozyrakis | first5 = C. | isbn = 978-1-4244-0804-7| citeseerx = 10.1.1.220.8210| s2cid = 12563671}}</ref><ref name="graphicsMR">{{Cite book | doi = 10.1145/1454115.1454152| chapter = Mars: a MapReduce framework on graphics processors| title = Proceedings of the 17th international conference on Parallel architectures and compilation techniques – PACT '08| pages = 260| year = 2008| last1 = He | first1 = B. | last2 = Fang | first2 = W. | last3 = Luo | first3 = Q. | last4 = Govindaraju | first4 = N. K. | chapter-url = http://wenbin.org/doc/papers/Wenbin08PACT.pdf| last5 = Wang | first5 = T. | isbn = 9781605582825| s2cid = 207169888}}</ref><ref name="tiledMR">{{Cite book | doi = 10.1145/1854273.1854337| chapter = Tiled-MapReduce: optimizing resource usages of data-parallel applications on multicore with tiling| title = Proceedings of the 19th international conference on Parallel architectures and compilation techniques – PACT '10| pages = 523| year = 2010| last1 = Chen | first1 = R. | last2 = Chen | first2 = H. | last3 = Zang | first3 = B. | isbn = 9781450301787| s2cid = 2082196}}</ref> desktop grids,<ref name="gridMR">{{Cite book | doi = 10.1109/3PGCIC.2010.33| chapter = Towards MapReduce for Desktop Grid Computing| title = 2010 International Conference on P2P, Parallel, Grid, Cloud and Internet Computing| pages = 193| year = 2010| last1 = Tang | first1 = B. | last2 = Moca | first2 = M. | last3 = Chevalier | first3 = S. | last4 = He | first4 = H. | last5 = Fedak | first5 = G. | chapter-url = http://graal.ens-lyon.fr/~gfedak/papers/xtremmapreduce.3pgcic10.pdf| isbn = 978-1-4244-8538-3| citeseerx = 10.1.1.671.2763| s2cid = 15044391}}</ref>
multi-cluster,<ref name="HMR">{{Cite book | doi = 10.1145/1996023.1996026| chapter = A Hierarchical Framework for Cross-Domain MapReduce Execution|chapter-url = http://yuanluo.net/publications/LUO_ECMLS2011.pdf| title = Proceedings of the second international workshop on Emerging computational methods for the life sciences (ECMLS '11)| year = 2011| last1 = Luo | first1 = Y. | last2 = Guo | first2 = Z. | last3 = Sun | first3 = Y.| last4 = Plale | first4 = B. |author4-link=Beth Plale| last5 = Qiu | first5 = J. | last6=Li|
first6=W. |isbn = 978-1-4503-0702-4| citeseerx = 10.1.1.364.9898| s2cid = 15179363}}</ref> volunteer computing environments,<ref name="volunteerMR">{{Cite book | doi = 10.1145/1851476.1851489| chapter = MOON: MapReduce On Opportunistic eNvironments| title = Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing – HPDC '10| pages = 95| year = 2010| last1 = Lin | first1 = H. | last2 = Ma | first2 = X. | last3 = Archuleta | first3 = J. | last4 = Feng | first4 = W. C. | last5 = Gardner | first5 = M. | last6 = Zhang | first6 = Z. | chapter-url = http://eprints.cs.vt.edu/archive/00001089/01/moon.pdf| isbn = 9781605589428| s2cid = 2351790}}</ref> dynamic cloud environments,<ref name="dynCloudMR">{{Cite journal| doi = 10.1016/j.jcss.2011.12.021| title = P2P-MapReduce: Parallel data processing in dynamic Cloud environments| journal = [[Journal of Computer and System Sciences]]| volume = 78| issue = 5| pages = 1382–1402| year = 2012| last1 = Marozzo| first1 = F.| last2 = Talia| first2 = D.| last3 = Trunfio| first3 = P.| doi-access = free}}</ref> mobile environments,<ref name="mobileMR">{{Cite book | doi = 10.1145/1839294.1839332| chapter = Misco: a MapReduce framework for mobile systems| title = Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments – PETRA '10| pages = 1| year = 2010| last1 = Dou | first1 = A. | last2 = Kalogeraki | first2 = V. | last3 = Gunopulos | first3 = D. | last4 = Mielikainen | first4 = T. | last5 = Tuulos | first5 = V. H. | isbn = 9781450300711| s2cid = 14517696}}</ref> and high-performance computing environments.<ref>{{cite book|chapter=Characterization and Optimization of Memory-Resident MapReduce on HPC Systems|publisher=IEEE|date=May 2014|doi=10.1109/IPDPS.2014.87|isbn=978-1-4799-3800-1|title=2014 IEEE 28th International Parallel and Distributed Processing Symposium|last1=Wang|first1=Yandong|last2=Goldstone|first2=Robin|last3=Yu|first3=Weikuan|last4=Wang|first4=Teng|pages=799–808|s2cid=11157612}}</ref>
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