'Reduce function' diaporamas de présentation

ecs251 Spring 2012 : Operating System #4: Map/Reduce, HDFS, Applications

ecs251 Spring 2012 : Operating System #4: Map/Reduce, HDFS, Applications. Dr. S. Felix Wu Computer Science Department University of California, Davis. fork. fork. fork. Master. assign map. assign reduce. Worker. Output File 0. write. Worker. local write. Split 0. read. Worker.

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Cloud Computing with MapReduce and Hadoop

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Parallel Computing and Programming Enviroments

Distributed and Cloud Computing K. Hwang, G. Fox and J. Dongarra Chapter 6: Cloud Programming and Software Environments Part 1 Adapted from Kai Hwang, University of Southern California with additions from Matei Zaharia , EECS, UC Berkeley November 25, 2012.

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Large-scale Processing with MapReduce

Large-scale Processing with MapReduce. Based on the text by Jimmy Lin and Chris Dryer. Motivation. Systems are defined by large repositories of data they collect and process gathering , analyzing, monitoring, filtering, searching, or organizing data, web-scale data

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Chapter 7 A Peer-to-Peer Framework for Supporting MapReduce Applications in Dynamic

Chapter 7 A Peer-to-Peer Framework for Supporting MapReduce Applications in Dynamic Cloud Environments Fabrizio Marozzo, Domenico Talia, and Paolo Trunfio. Abstract.

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.NET and MongoDB

Building Applications with NoRM and MongoDB Fairfield/Westchester Code Camp 2010 2010-11-06 John C. Zablocki Development Lead, MagazineRadar Adjunct, Fairfield University. .NET and MongoDB. Agenda. What is NoSQL? NoSQL Databases Introducing MongoDB .NET Drivers for MongoDB

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MapReduce:

MapReduce:. Acknowledgements: Some slides form Google University (licensed under the Creative Commons Attribution 2.5 License) others from Jure Leskovik. MapReduce. Concept from functional programming Applied to large number of problems. Java: int fooA(String[] list) {

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Map Reduce Architecture

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Google MapReduce Framework

A Summary of: MapReduce & Hadoop API. Google MapReduce Framework. Slides prepared by Peter Erickson (poe9514@rit.edu). What is MapReduce?. Massively parallel processing of very large data sets (larger than 1TB) ? . Parallelize the computations over hundreds or thousands of CPUs.

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Distributed MapReduce Team B

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Resource Provisioning Framework for MapReduce Jobs with Performance Goals

Resource Provisioning Framework for MapReduce Jobs with Performance Goals. Abhishek Verma 1,2 , Lucy Cherkasova 2 , Roy H. Campbell 1 1 University of Illinois at Urbana-Champaign 2 HP Labs. Unprecedented Data Growth.

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Distributed and Parallel Processing Technology Chapter2. MapReduce

Distributed and Parallel Processing Technology Chapter2. MapReduce. Sun Jo. Introduction. MapReduce is a programming model for data processing. Hadoop can run MapReduce programs written in various languages. We shall look at the same program expressed in Java, Ruby, Python, and C++.

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Hadoop

Hadoop. Ida Mele. Parallel programming. Parallel programming is used to improve performance and efficiency In a parallel program, the processing is broken up into parts, that run on different machines concurrently

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Hadoop : The Definitive Guide Chap. 2 MapReduce

Hadoop : The Definitive Guide Chap. 2 MapReduce. Kisung Kim. MapReduce. Programming model for parallel data processing Hadoop can run MapReduce programs written in various languages: e.g . Java, Ruby, Python, C ++ In this chapter Introduce MapReduce programming using a simple example

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Shivnath Babu

CPS216: Advanced Database Systems (Data-intensive Computing Systems) Introduction to MapReduce and Hadoop. Shivnath Babu. Word Count over a Given Set of Web Pages. see 1 bob 1 throw 1 see 1 spot 1 run 1. bob 1 run 1 see 2 spot 1 throw 1. see bob throw.

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Shivnath Babu

CPS216: Advanced Database Systems (Data-intensive Computing Systems) Introduction to MapReduce and Hadoop. Shivnath Babu. Word Count over a Given Set of Web Pages. see 1 bob 1 throw 1 see 1 spot 1 run 1. bob 1 run 1 see 2 spot 1 throw 1. see bob throw.

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MapReduce : Simplified Data Processing on Large Clusters

MapReduce : Simplified Data Processing on Large Clusters. Appendix A: Word Frequency Alex Newton Billy Coss. Contents. Abstract Introduction MapReduce Word Frequency Analysis Sample Code. Abstract. MapReduce is a model used to analyze large amounts of data

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Towards Large Scale Semantic Annotation Built on MapReduce Architecture

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MapReduce

MapReduce. Simplified Data Processing on Large Clusters. Jeffery Dean and Sanjay Ghemawat Google, Inc. Abstract & Introduction. MapReduce ? programming model & an associated implementation for processing & generating large data sets Users specify a map and reduce function

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