Your sliding window should not be small enough to get the median. For a free
running stream, your window should be of size not less than 100.

On Sun, May 15, 2011 at 7:35 PM, Akshata Sharma
<akshatasharm...@gmail.com>wrote:

> @Anand:
> if the stream is let 1,2,3,4,6,7,9
>
> and let we choose k=3
>
> then your algo is giving 7 as the median.
>
> On Mon, May 16, 2011 at 4:39 AM, Anand <anandut2...@gmail.com> wrote:
>
>> Complexity will be O(logK) to insert, delete and finding the predecessor
>> or successor of current median value in the BST.
>>
>>
>> On Sun, May 15, 2011 at 4:08 PM, Anand <anandut2...@gmail.com> wrote:
>>
>>> 1. Create a BST for first K elements of the running stream.
>>> 2. Find the median of first K elements.
>>> 3. With every new element from the stream, Insert the new element in
>>> Binary search Tree.
>>> 4. Delete the first element from BST.
>>> 5. if the new element is greater than the current median value, find the
>>> successor of current median value.
>>> 6. else if the new elment is less than the current median value, find the
>>> predecessor of the currend median value in BST.
>>>
>>>
>>>
>>> On Sun, May 15, 2011 at 2:51 AM, pacific :-) <pacific4...@gmail.com>wrote:
>>>
>>>> perfect.
>>>>
>>>> Thanks for the effort in explanation.
>>>>
>>>>
>>>> On Sun, May 15, 2011 at 12:20 AM, Dave <dave_and_da...@juno.com> wrote:
>>>>
>>>>> @Pacific: A balanced binary tree is commonly defined as a binary tree
>>>>> in which the height of the two subtrees of every node never differ by
>>>>> more than 1. Thus, there could be more nodes in one subtree than in
>>>>> the other. E.g., a balanced binary tree with 11 nodes could have 7
>>>>> nodes in the left subtree and only 3 nodes in the right subtree. Thus,
>>>>> the root would not be the median.
>>>>>
>>>>> An additional condition is needed: the number of nodes in the left
>>>>> subtree differs by at most one from the number of nodes in the right
>>>>> subtree.
>>>>>
>>>>> In fact, given that the heap structure is a balanced binary tree
>>>>> structure with implicit pointers to the left and right subtrees, the
>>>>> two-heap algorithm I described results in a balanced binary tree
>>>>> satisfying this additional condition, with an implicit root node equal
>>>>> to the median.
>>>>>
>>>>> Dave
>>>>>
>>>>> On May 14, 11:55 am, "pacific :-)" <pacific4...@gmail.com> wrote:
>>>>> > Will not a balanced binary tree do the job ? if we will pick the root
>>>>> each
>>>>> > time for the median.
>>>>> >
>>>>> >
>>>>> >
>>>>> >
>>>>> >
>>>>> > On Sat, May 14, 2011 at 9:10 PM, Dave <dave_and_da...@juno.com>
>>>>> wrote:
>>>>> > > @Ashish: The idea is to keep two heaps, a max-heap of the smallest
>>>>> > > half of the elements and a min-heap of the largest elements. You
>>>>> > > insert incoming elements into the appropriate heap. If the result
>>>>> is
>>>>> > > that the number of elements in the two heaps differs by more than
>>>>> 1,
>>>>> > > then you move the top element from the longer heap into the other
>>>>> one,
>>>>> > > thereby equalzing the number of elements. Thus, inserting an
>>>>> element
>>>>> > > is an O(log n) operation. To get the median, it is the top element
>>>>> of
>>>>> > > the longer heap, or, if the heaps are of equal length, it is the
>>>>> > > average of the two top elements. This is O(1).
>>>>> >
>>>>> > > Dave
>>>>> >
>>>>> > > On May 14, 8:34 am, Ashish Goel <ashg...@gmail.com> wrote:
>>>>> > > > not clear, can u elaborate..
>>>>> >
>>>>> > > > Best Regards
>>>>> > > > Ashish Goel
>>>>> > > > "Think positive and find fuel in failure"
>>>>> > > > +919985813081
>>>>> > > > +919966006652
>>>>> >
>>>>> > > > On Fri, May 13, 2011 at 7:15 PM, Bhavesh agrawal <
>>>>> agr.bhav...@gmail.com
>>>>> > > >wrote:
>>>>> >
>>>>> > > > > This problem can be solved using 2 heaps and the median can
>>>>> always be
>>>>> > > > > accessed in O(1) time ,the first node.
>>>>> >
>>>>> > > > > --
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>>>>
>>>>
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>>>> chinna.
>>>>
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