'Reduce key' diaporamas de présentation

MapReduce & Pregel

MapReduce & Pregel. http://net.pku.edu.cn/~wbia ??? hle@net.pku.edu.cn ?????????? 1 2/09/2014. MapReduce. Imperative Programming. In computer science , imperative programming is a programming paradigm that describes computation in terms of statements that change a program state.

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MapReduce , HBase , Pig and Hive

656 views • 64 slides

MapReduce & BigTable

MapReduce & BigTable. http://net.pku.edu.cn/~wbia ??? hle@net.pku.edu.cn ?????????? 1 2/10/2013. MapReduce. Imperative Programming. In computer science , imperative programming is a programming paradigm that describes computation in terms of statements that change a program state.

794 views • 57 slides

Map-Reduce: Win -or- Epic Win

CSC313: Advanced Programming Topics. Map-Reduce: Win -or- Epic Win. Brief History of Google. BackRub : 1996 4 disk drives 24 GB total storage. Brief History of Google. BackRub : 1996 4 disk drives 24 GB total storage. =. Brief History of Google. Google: 1998 44 disk drives

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Data Parallel and Graph Parallel Systems for Large-scal e Data P rocessing

Data Parallel and Graph Parallel Systems for Large-scal e Data P rocessing. Presenter: Kun Li. Threads, Locks, and Messages. ML experts repeatedly solve the same parallel design challenges: Implement and debug complex parallel system Tune for a specific parallel platform

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An Innovative Approach to Parallel Processing Data

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Daniel Abadi Yale University November 23 rd , 2011

Tradeoffs Between Parallel Database Systems, Hadoop, and HadoopDB as Platforms for Petabyte-Scale Analysis. Daniel Abadi Yale University November 23 rd , 2011. Data, Data, Everywhere. Data explosion Web 2.0 ? more user data More devices that sense data

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MapReduce: Simplified Data Processing on Large Clusters

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Map Reduce

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MapReduce: Simplified Data Processing on Large Clusters

MapReduce: Simplified Data Processing on Large Clusters. Authors: Jeffrey Dean and Sanjay Ghemawat Presenter: Guangdong Liu Jan 28th, 2011. Presentation Outline. Motivation Goal Programming Model Implementation Refinement. Motivation. Large-scale data processing

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The Technology Behind

The Technology Behind. The World Wide Web. In July 2008, Google announced that they found 1 trillion unique webpages! Billions of new web pages appear each day! About 1 billion Internet users (and growing)!!. The World Wide Web in 2003. Image source: http://www.opte.org/.

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MapReduce Theory and Practice

MapReduce Theory and Practice. http://net.pku.edu.cn/~course/cs402/2010/ ?? pb@net.pku.edu.cn ???????????? 7/15/2010. Last Course Review. Quiz. What are they? ?? (data) Bit Byte ???? (data types) ?? (information). Data.

367 views • 22 slides