Short answer : value. Count is not always equal to one.
Short answer : value. Count is not always equal to one. Long answer : This is the expected behavior of map reduce : the reduce function is aggreagating the results of the map function.
However, it does aggregate on the results of map function by small groups producing intermediate results (sub total in your case). Then reduce functions are runned again on these intermediate results as they were direct results of the map function. And so on until there is only one intermediate result left for each key, that's the final results.It can be seen as a pyramid of intermediate results : emit(...)-| |- reduce -> | emit(...)-| | | |- reduce ->| emit(...)-| | | | | | emit(...)-|- reduce -> | | | |-> reduce = final result emit(...)-| | | emit(...)--- reduce ------------ >| | emit(...)-----------------reduce ->| The number of reduce and their inputs is unpredicatable and is meant to remain hidden.
That's why you have to give a reduce function which return data of the same type (same schema) as input.
The reduce function does not only get called on the original input data, but also on its own output, until there is a final result. So it needs to be able to handle these intermediate results, such as {count: 5}, {count:3}, {count: 4} coming out of an earlier stage.
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