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Data-Intensive Text Processing with MapReduce
Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters...
| Autores principales: | , |
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| Lenguaje: | eng |
| Publicado: |
Morgan & Claypool Publishers
2010
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| Acceso en línea: | http://cds.cern.ch/record/1486557 |
| Sumario: | Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-underst |
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