Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2093#issuecomment-53379531
Some quick benchmark:
>>> from pyspark.rdd import MaxHeapQ
>>> import heapq, random, timeit
>>> l = range(1<<13)
>>> random.shuffle(l)
>>>
>>> def take1():
>>> q = MaxHeapQ(100)
>>> for i in l:
>>> q.insert(i)
>>> return q.getElements()
>>>
>>> def take2():
>>> return heapq.nsmallest(100, l)
>>> # for S >> N
>>> print timeit.timeit("take1()", "from __main__ import *", number=100)
0.748146057129
>>> print timeit.timeit("take2()", "from __main__ import *", number=100)
0.142593860626
>>> # for N > S
>>> l = range(80)
>>> random.shuffle(l)
>>> print timeit.timeit("take1()", "from __main__ import *",
number=1000)
0.156821012497
>>> print timeit.timeit("take2()", "from __main__ import *",
number=1000)
0.00907206535339
Whenever S < N or S > N, nsmallest() is much faster than MaxHeapQ.
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