How can you obtain a randomized subset of a list in Java, without using Collections.shuffle?

I've got a List of Objects, this list could potentially contain thousands of elements.

I want to 开发者_StackOverflowobtain 10, 20, 34, 56 (whatever size portion the user chooses) subset of those, this subset must be randomly selected and I can't have duplicates.

Would Collections.shuffle() be sufficient for large Lists of POJOs? Or is there a more efficient/safer way of doing this?

Taking my example here, if myStrings had 50,000 Strings in it, would calling Collections.shuffle() be a good idea if you only wanted 5 items?

public class ShuffleMe
{

    public static void main(String[] args)
    {
        int NUM_OF_ELEMENTS_TO_PICK = 3;
        List<String> myStrings = new ArrayList<String>();

        myStrings.add("A");
        myStrings.add("B");
        myStrings.add("C");
        myStrings.add("D");
        myStrings.add("E");
        myStrings.add("F");

        Collections.shuffle(myStrings);

        for (int i = 0; i < NUM_OF_ELEMENTS_TO_PICK; i++)
        {
            System.out.println(myStrings.get(i));
        }
    }
}

Shuffling the whole list would be a bit of a waste of resources if what you want is significantly smaller. I'd personally just pick n unique random numbers between 0..size and use the objects at those indexes for the randomised subset.

If you're talking about picking a random subset very close to the size of the whole collection, then chances are you're better of just calling Collections.shuffle() and choosing the first n entries. But if we're talking about ~5 / 50,000, definitely use the above approach.

If the number of items you want is much less than the size of the collection, just draw them at random:

Set<Integer> randSubSet = new HashSet<Integer>();
while(randSubSet.size() < NUM_OF_ELEMENTS_TO_PICK) {
    randSubSet.add((int)(Math.random()*myStrings.size()));
}
for (int i : randSubSet) {
    System.out.println(myStrings.get(i));
}

Use a Fisher-Yates shuffle, but only run it far enough to pick the number of elements you need.