@aarthi, Its seems like ur worried only about frequency, not the
sorting. If its a count sort you're trying to explain,then it requires
huge space.. And i guess there is no O(n) sort except count sort,
which won't be a gr8 soln. for the original problem

Regards,
Vignesh

On May 19, 4:09 pm, Aarthi Thangamani <aarthi.thangam...@gmail.com>
wrote:
> If you are using an extra space to count, why need a heap? An array of size
> k can be used to first count the occurances. Then run through the original
> array of size N and fill it according to the count our occirances using the
> constant k size array. Space O(k) and time O(N) is the best thing I think
> of. :(
>
> On Tue, May 18, 2010 at 7:11 PM, CHERUVU JAANU REDDY <
>
>
>
> jaanu.cher...@gmail.com> wrote:
>
> > Here u r using extra space to store count values..
>
> > ----------------------------------------
> > CHERUVU JAANU REDDY
> > M.Tech in CSIS
>
> > On Tue, May 18, 2010 at 7:01 PM, Jagadish M <jagadis...@gmail.com> wrote:
>
> >> On May 18, 8:29 am, Terence <technic....@gmail.com> wrote:
> >> > How do you maintain the heap? Could you explain in detail for the
> >> > following example:
> >> > 1 2 3 3 2 1 1 1 2 3 (n=10, k=3)
>
> >> Basically, in each node we maintain the key and its count.
>
> >> Initially, heap has the first element.
> >> 1:1
>
> >> Search for 2 and insert( since its not found)
> >>  1:1
> >>  /
> >> 2:1
>
> >> Search for 3 and insert ( since its not found).
>
> >>    1:1
> >>  /       \
> >> 2:1    3:1
>
> >> Search for 3; since 3 is already there increment its count by 1.
>
> >>    1:1
> >>  /       \
> >> 2:1    3:2
>
> >> Search for 2; since 2 is already there increment its count by 1.
>
> >>    1:1
> >>  /       \
> >> 2:2    3:2
>
> >> and so on...
>
> >> Since, there are only k distinct keys the heap size will at most be k;
> >> so each search/insert/increment operation takes O(log k) time.
>
> >> Jagadish
> >>http://www.cse.iitb.ac.in/~jagadish
>
> >> > On 2010-5-17 22:38, Jagadish M wrote:
>
> >> > > The best algorithm I can think of is to maintain a heap of k elements.
> >> > > Takes O(n log k) time.
> >> > > Is anything told about the values of the keys? If the keys have values
> >> > > less than N, then it is possible to do
> >> > > what you say, i.e sort them in place.
>
> >> > > -Jagadish
> >> > >http://www.cse.iitb.ac.in/~jagadish
>
> >> > > On May 13, 7:06 pm, divya<sweetdivya....@gmail.com>  wrote:
>
> >> > >> This problem was asked in google phone interview. We have N element
> >> > >> array with k distinct keys(No relation between k&  N given so assume
> >> > >> k<N)
> >> > >> What is the best method to sort this array without using any extra
> >> > >> memory? Please elaborate.
>
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