Write a program to find 100 largest numbers out of an array of 1 billion numbers

Question

I recently attended an interview where I was asked \"write a program to find 100 largest numbers out of an array of 1 billion numbers.\"

I was only able to give a br

Answer 1

Although the other quickselect solution has been downvoted, the fact remains that quickselect will find the solution faster than using a queue of size 100. Quickselect has an expected running time of 2n + o(n), in terms of comparisons. A very simply implementation would be

array = input array of length n
r = Quickselect(array,n-100)
result = array of length 100
for(i = 1 to n)
  if(array[i]>r)
     add array[i] to result

This will take 3n + o(n) comparisons on average. Moreover, it can be made more efficient using the fact that quickselect will leave the largest 100 items in the array in the 100 right-most locations. So in fact, the running time can be improved to 2n+o(n).

There is the issue that this is expected running time, and not worst case, but by using a decent pivot selection strategy (e.g. pick 21 elements at random, and choose the median of those 21 as pivot), then the number of comparisons can be guaranteed with high probability to be at most (2+c)n for an arbitrarily small constant c.

In fact, by using an optimized sampling strategy (e.g. sample sqrt(n) elements at random, and choose the 99th percentile), the running time can be gotten down to (1+c)n + o(n) for arbitrarily small c (assuming that K, the number of elements to be selected is o(n)).

On the other hand, using a queue of size 100 will require O(log(100)n) comparisons, and log base 2 of 100 is approximately equal to 6.6.

If we think of this problem in the more abstract sense of choosing the largest K elements from an array of size N, where K=o(N) but both K and N go to infinity, then the running time of the quickselect version will be O(N) and the queue version will be O(N log K), so in this sense quickselect is also asymptotically superior.

In comments, it was mentioned that the queue solution will run in expected time N + K log N on a random input. Of course, the random input assumption is never valid unless the question states it explicitly. The queue solution could be made to traverse the array in a random order, but this will incur the additional cost of N calls to a random number generator as well as either permuting the entire input array or else allocating a new array of length N containing the random indices.

If the problem doesn't allow you to move around the elements in the original array, and the cost of allocating memory is high so duplicating the array is not an option, that is a different matter. But strictly in terms of running time, this is the best solution.