A reduce function may be called once, with a key and all corresponding values.
It may also be called multiple times, each time with a key and only a subset of the corresponding values, and the previous reduce results for that key. This scenario is called a re-reduce. In order to support re-reduces, your reduce function should be idempotent.
There are two key features in a idempotent reduce function:
- The return value of the reduce function should be in the same format as the values it takes in. So, if your reduce function accepts an array of strings, the function should return a string. If it accepts objects with several properties, it should return an object containing those same properties. This ensures that the function doesn't break when it is called with the result of a previous reduce.
- Don't make assumptions based on the number of values it takes in. It isn't guaranteed that the
values
parameter contains all the values for the given key. So using values.length
in calculations is very risky and should be avoided.
If your reduce function is idempotent, you shouldn't have any problems map-reducing multiple collections. Just re-reduce the results of each collection:
Step 1
Run the map-reduce on each required collection and save the results in a single, temporary collection. You can store the results using a finalize function:
finalize = function (key, value) {
db.tempResult.save({ _id: key, value: value });
}
db.someCollection.mapReduce(map, reduce, { finalize: finalize })
db.anotherCollection.mapReduce(map, reduce, { finalize: finalize })
Step 2
Run another map-reduce on the temporary collection, using the same reduce function. The map function is a simple function that selects the keys and values from the temporary collection:
map = function () {
emit(this._id, this.value);
}
db.tempResult.mapReduce(map, reduce)
This second map-reduce is basically a re-reduce and should give you the results you need.