MapReduce is a programming model and an associated implementation for processing and generating large data sets with a parallel, distributed algorithm on a cluster. It works by dividing the work into two phases: the 'Map' phase, where data is processed and transformed into key-value pairs, and the 'Reduce' phase, where those pairs are aggregated to produce the final output. This model allows for efficient processing of vast amounts of data across many machines, making it a crucial component in big data storage solutions.
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