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algorithm - Retrieving the top 100 numbers from one hundred million of numbers

One of my friend has been asked with a question

Retrieving the max top 100 numbers from one hundred million of numbers

in a recent job interview. Do you have any idea to come up with an efficient way to solve it?

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Run them all through a min-heap of size 100: for each input number k, replace the current min m with max(k, m). Afterwards the heap holds the 100 largest inputs.

A search engine like Lucene can use this method, with refinements, to choose the most-relevant search answers.

Edit: I fail the interview -- I got the details wrong twice (after having done this before, in production). Here's code to check it; it's almost the same as Python's standard heapq.nlargest():

import heapq

def funnel(n, numbers):
    if n == 0: return []
    heap = numbers[:n]
    heapq.heapify(heap)
    for k in numbers[n:]:
        if heap[0] < k:
            heapq.heapreplace(heap, k)
    return heap

>>> funnel(4, [3,1,4,1,5,9,2,6,5,3,5,8])
[5, 8, 6, 9]

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