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Is it still necessary to understand map-reduce paradigms for machine learning on large data sets?

Is it still necessary to understand map-reduce paradigms for machine learning on large data sets?    Awantik Das

Spark has covered a lot of mileage in a couple of years. And, with of Spark 2.0 - the internal implementation & optimization is abstracted the best possible way.