In Pictures: 18 essential Hadoop tools for crunching big data

Making the most of this powerful MapReduce platform means mastering a vibrant ecosystem of quickly evolving code

In Pictures: 18 essential Hadoop tools for crunching big data prev next

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Mahout There are a great number of algorithms for data analysis, classification, and filtering, and Mahout is a project designed to bring implementations of these to Hadoop clusters. Many of the standard algorithms, such as K-Means, Dirichelet, parallel pattern, and Bayesian classification, are ready to run on your data with a Hadoop-style map and reduce.

The image at left shows the result of a canopy-clustering algorithm that chooses points and radii to cover the collection of points. It's just one of the various data analysis tools built into Hadoop.

Mahout comes from the Apache project and is distributed under the Apache license from http://mahout.apache.org/.

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In Pictures: 18 essential Hadoop tools for crunching big data

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