您可以使用保持排序的deque。
在每一步,如果双端队列中的第一个元素 (d.front.index) 相对于当前步骤早于 k 步骤,则将其弹出 (d.popFront())。
然后,当数组中当前位置的元素小于双端队列中的最后一个元素(d.back.value)时,从双端队列中弹出元素(d.popBack())。
最后,将当前值添加到双端队列的末尾 (d.pushBack())。
在每一步,d.front.value 将是[step - k + 1, step] 的最小值。
您可以将双端队列存储为大小为k 的链表。然后您将始终可以访问其中的第二个元素,这将是[step - k + 1, step] 中的第二小元素。如果由于弹出每个元素而最终只有一个元素,则必须小心。在这种情况下,弹出的可能是未来查询的第二小。您可以将它们保存在另一个列表中,与双端队列类似,请参见下面的示例。
这是O(n) amortized,因为数组中的每个元素最多会进入和离开双端队列一次。它可能看起来像O(nk),因为你会有一些嵌套循环,但如果你考虑一下操作的总数,你会发现它实际上是O(n)。
伪代码
for i = 0, i < n:
if not d.empty and i - d.front.index >= k:
d.popFront()
while not d.empty and d.back.value > a[i]:
d.popBack()
d.pushBack({index = i, value = a[i]})
output d.front.value as the minimum value in [i - k + 1, i]
跟踪第二个最小值的代码留作练习。
你的例子:
a = {12, 1, 78, 90, 57, 89, 56}, k = 3
d = {12}
d = {1} (12 popped, track this)
d = {1, 78} => we have to output smallest and second smallest in [0, 2].
=> smallest is always the first in the deque, so 1
=> second = min(12 [this was popped], 78) = 12
d = {1, 78, 90)
=> smallest 1, second is 78 (12 is too old now)
d = {57}
=> 1 popped for being too old, the others for being too large
=> smallest = 57, second = 78 (last popped)
d = {57, 89}
=> smallest = 57, second = 89
d = {56}
=> smallest = 56, second = 57
基本上,您保留第二小的数组。这将包含尚未太旧的弹出值。这些也将按降序排序。
此方法的示例运行,其中d2 是第二个数组:
a = {12, 1, 78, 90, 57, 89, 56}
d = {12}, d2 = {}
d = {1}, d2 = {12}
d = {1, 78}, d2 = {12}
=> output 1, 12
d = {1, 78, 90}, d2 = {} - 12 was too old
=> output 1, 78
d = {57} d2 = {90, 78}
=> output 57, 78
d = {57, 89} d2 = {90} - 78 too old
=> output 57, 89 (if we had 91 instead of 89, we'd have output the 90 in d2)
d = {56} d2 = {89, 57}
=> output 56, 57