MapReduce is an distributed algorithm. https://www.psc.edu/wp-content/uploads/2023/07/A-Brief-History-of-Big-Data.pdf Map: (in\_key, in\_value) \Rightarrow list(out\_key, intermediate\_value). Reduce: Group map outputs by out\_key (out\_key, list(intermediate\_value)) \Rightarrow list(out\_value) example of MapReduce Say, if you want to count word frequencies in a set of documents. Map: (document\_name, document\_contents) \Rightarrow list(word, #\ occurrences) You can see that this can be distributed to multiple processors. You can have each processor count the word frequencies in a single document. We have now broken the contents into divide and conquerable groups. Reduce: (word, list\ (occurrences\_per\_document)) \Rightarrow (word,sum) We just add up the occurrences that each of the nodes’ output for word frequency.