Question

If we have a Map<T, Integer>, let’s say the Integer value represents “how many” Ts there are. Thus, I want to uniformly select a T based on its Integer value. If the map contains Strings with “a”=4 and “b”=6, then I want it so that 40% of the time “a” is selected and 60% of the time “b” is selected.

Most importantly, I’d like this in O(n), n being two (not ten) in my previous example. I originally made an ArrayList containing the keys by how many values it had (and simply returning any random index), but this process is not only very slow, but completely counterintuitive for what the Map<T, Integer> represents.

Answer 1

OP here.

I came up with an elegant solution! For any misunderstandings: My original idea of storing all the keys by how many values in an ArrayList was completely disregarding the point of using a Map to store “instances of the Key using Integers”; any similar solutions are counterproductive! Assuming the Map is unordered, here is my solution:

public T randomPick(Random r) {

        int randomValue = r.nextInt(size());
        int currentSum = 0;
        T lastElement = null;

        for (T t : map.keySet()){
            if (randomValue < currentSum + map.get(t)){
                return t;
            }
            currentSum+= map.get(t);
            lastElement = t;
        }
        return lastElement;
    }

It compares the random value with a current sum + the current element's value. If it is less than that, we return the current key. Else, keep going and add that value to the sum. If it is the case such that the random value is never less than any of the values, we return the lastElement.

Hope this clears it up.