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| In ] '''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. | In ] '''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. | ||
| ==References== | |||
| * Dean, Jeffrey & Ghemawat, Sanjay (2004). . Retrieved Apr. 6, 2005. | |||
Revision as of 00:56, 7 April 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.
References
- Dean, Jeffrey & Ghemawat, Sanjay (2004). "MapReduce: Simplified Data Processing on Large Clusters". Retrieved Apr. 6, 2005.