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28-double-inverse-multiplexer/README.md
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Style #30
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==============================
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Very similar to style #12, but with an additional twist
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Constraints:
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- Input data is divided in chunks, similar to what an inverse multiplexer does to input signals
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- A map function applies a given worker function to each chunk of data, potentially in parallel
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- The results of the many worker functions are reshuffled in a way
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that allows for the reduce step to be also parallelized
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- The reshuffled chunks of data are given as input to a second map
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function that takes a reducible function as input
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Possible names:
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- Double inverse multiplexer
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- Map-reduce
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- Hadoop style
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