Then MapReduce shuffles the map output by key and does another parallel computation on the redistributed map output, writing the results to the file system in the Reduce phase of the computation.
A key selling point for MapReduce is its ability to abstract the operational parallelization semantics - how parallel programming works - away from the developer.
MapReduce的关键特点是它能够对开发人员隐藏操作并行语义—并行编程的具体工作方式。
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In the initial example above, the key data was user profiles, which could be distributed (partitioned) across a set of machines for parallel processing.