MapReduce Word Count
Step through Split → Map → Shuffle → Reduce and see how distributed word counting works.
MapReduce is a programming model for processing large datasets in parallel across a cluster. The idea is simple: split the input, apply a function to each piece (Map), group the intermediate results by key (Shuffle), then combine them (Reduce).
Type any text in the input box, then click Next to step through each phase. Watch how words get distributed to workers, turned into (word, 1) pairs, grouped by key, and summed into final counts.
Notice that each worker operates independently during Map — they don't need to talk to each other. The Shuffle phase is where communication happens, regrouping all pairs so that every occurrence of the same word ends up together for the Reduce step.