| Revision as of 00:56, 8 September 2005 edit84.42.164.136 (talk) cs:← Previous edit | Revision as of 10:27, 19 December 2005 edit undoMParaz (talk | contribs)90 edits Nutch implementationNext edit → | ||
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| MapReduce is often used in conjunction with ], for greater parallelization. | MapReduce is often used in conjunction with ], for greater parallelization. | ||
| ==Other Implementations== | |||
| ] has an experimental implementation of MapReduce. | |||
| ==References== | ==References== | ||
Revision as of 10:27, 19 December 2005
In Google's MapReduce programming model, parallel computations over large data sets are implemented by specifying a Map function that maps key-value pairs to new key-value pairs and a subsequent Reduce function that consolidates all mapped key-value pairs sharing the same keys to single key-value pairs.
MapReduce is often used in conjunction with Google File System, for greater parallelization.
Other Implementations
Nutch has an experimental implementation of MapReduce.
References
- Dean, Jeffrey & Ghemawat, Sanjay (2004). "MapReduce: Simplified Data Processing on Large Clusters". Retrieved Apr. 6, 2005.
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