PPT-Cloud Computing and MapReduce

Author : barbara | Published Date : 2023-06-23

Used slides from RAD Lab at UC Berkeley about the cloud httpabovethecloudscsberkeleyedu and slides from Jimmy Lin s slides httpwwwumiacsumdedujimmylincloud2010Springindexhtml

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Cloud Computing and MapReduce: Transcript

Used slides from RAD Lab at UC Berkeley about the cloud httpabovethecloudscsberkeleyedu and slides from Jimmy Lin s slides httpwwwumiacsumdedujimmylincloud2010Springindexhtml licensed under Creation Commons Attribution 30 License. S. A. L. S. A. . HPC Group . http://. salsahpc.indiana.edu. School of Informatics and Computing. Indiana University. Judy . Qiu. . Thilina. . Gunarathne. . CAREER Award. Outline. Iterative . Simplified Data Processing on Large . Clusters. by Jeffrey Dean and Sanjay . Ghemawa. Presented by Jon Logan. Outline. Problem Statement / Motivation. An Example Program. MapReduce. . vs. Hadoop. GFS / HDFS. Efficient and scalable architectures to perform pleasingly parallel, MapReduce and iterative data intensive computations on cloud environments. Thilina. . Gunarathne. (tgunarat@indiana.edu). Advisor : . IT4GIS. Keith T. Weber, GISP. GIS Director. ISU-GIS Training and Research Center. Goal of this presentation. Describe and demystify “The Cloud”. What is it?. How is it different from web services?. By . Yufei. Tao, . Wenqing. . Lin, . Xiaokui. . Xia. Edited by Tuval Rotem. First topic:. What is MapReduce. But first…. Regular day at work. You’re doing your regular work while suddenly your boss, . The Second International Workshop on . Data Intensive Computing in the Clouds (DataCloud-SC11) . at SC11. November 14 2011. Geoffrey Fox. gcf@indiana.edu. . . http://www.infomall.org. . Presented By. Shefali. . Gundecha. Srinivas . Narne. Yash. Kulkarni. Papers to be discussed…. Y. Shan, B. Wang, J. Yan, Y. Wang, N. Xu, and H. Yang, . " FPMR: MapReduce Framework on FPGA: A Case Study of . Yasin N. Silva and Jason Reed. Arizona State University. 1. This work is licensed under a Creative Commons Attribution-. NonCommercial. -. ShareAlike. 4.0 International License. See http://creativecommons.org/licenses/by-nc-sa/4.0/ for details.. ”. Cathy O’Neil & Rachel . Schutt. , 2013. R & Hadoop. Compute squares. 2. R. # create a list of 10 integers. ints. <- 1:10. # equivalent to . ints. <- c(1,2,3,4,5,6,7,8,9,10). # compute the squares. Jimmy Lin. The iSchool. University of Maryland. Monday, March 30, 2009. This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States. See http://creativecommons.org/licenses/by-nc-sa/3.0/us/ for details. 1. Table of contents:. 1. What is the Cloud?. 2. Cloud Computing Service Models.. - Software as a Service (SaaS).. - Platform as a Service (PaaS).. - Infrastructure as a Service (IaaS).. 3. Benefits of Cloud Computing.. 1. Heru. . Suhartanto. Faculty of Computer Science, . Universitas. Indonesia. E-mail: . heru@cs.ui.ac.id. Presented at University of YARSI. – General Course – on 27-th April 2011. A revised version of presentation at ICACSIS2010, . MapReduce. Architecture. MapReduce. Internals. MapReduce. Examples. JobTracker. Interface. MapReduce. : A Real World Analogy. Coins Deposit. ?. MapReduce. : A Real World Analogy. Coins Deposit. Coins Counting Machine. Prof. . Raffaele Montella, Ph.D.. http://raffaelemontella.it. raffaele.montella@uniparthenope.it. Outline - Computing in the Cloud. Introduction. Computing as a service. Virtualization and Containerization.

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