'Map string input key' presentation slideshows

Distributed Computations MapReduce/Dryad

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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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Introduction to MapReduce

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Jimmy Lin The iSchool University of Maryland Wednesday, January 30, 2008

Cloud Computing Lecture #2 From Lisp to MapReduce and GFS. Jimmy Lin The iSchool University of Maryland Wednesday, January 30, 2008.

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In the news

In the news. " The cloud isn't this big fluffy area up in the sky ," said Rich Miller, who edits Data Center Knowledge, a publication that follows the data center industry. "It's buildings filled with servers and generators.".

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MapReduce: Theory and Implementation

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MapReduce: Theory and Implementation

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Large Scale Machine Learning based on MapReduce & GPU

Large Scale Machine Learning based on MapReduce & GPU. Lanbo Zhang. Motivation. Massive data challenges More and more data to process (Google: 20,000 terabytes per day) Data arrives faster and faster Solutions Invent faster ML algorithms: online algorithms

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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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MapReduce

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C-Store: MapReduce

C-Store: MapReduce. Jianlin Feng School of Software SUN YAT-SEN UNIVERSITY May. 22, 2009. Motivation: Large Scale Data Processing. Many tasks: Process lots of data to produce other data. The Problems How to parallelize the computation? How to distribute the data?

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