Re: [algogeeks] Re: Hash Table

[Vicki Wen]

@Kumar: It's O(1) for searching an element in hash table as long as there is
no collision.

-Vicki

On Thu, Oct 27, 2011 at 10:38 AM, kumar raja wrote:

> @Prem :
> So is the time complexity is O(1) or O(log n) or O(n)???
>
>
> On 27 October 2011 07:28, Prem Krishna Chettri  wrote:
>
>> Well, if we talk abt space complexity in Hash.. M srry we require O(n)
>> for Hash Datastructure... As each Bucket can contain at most one data
>> value of Key Value pair,thats where key is gonna hash your value..
>>
>> However, when we talk abt time complexity, its alwayz, the Hash
>> Function dependable question...
>>
>> On 10/27/11, ligerdave  wrote:
>> > I am a bit confused. Are you talking about the runtime of hash function
>> > itself or to find the position.
>> > Agree on the efficient hash function design. However, no function could
>> be
>> > designed to fit all cases. A key to make a particular hash function
>> > efficient is to know the potential data size.
>> >
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>
>
> --
> Regards
> Kumar Raja
> M.Tech(SIT)
> IIT Kharagpur,
> 10it60...@iitkgp.ac.in
>
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Re: [algogeeks] MICROSOFT WRITTEN QUESTION-2010

[Vicki Wen]

@ bharat: merging 2 sorted arrays is O(n)

On Tue, Sep 13, 2011 at 12:42 AM, bharatkumar bagana <
bagana.bharatku...@gmail.com> wrote:

> @jai gupta : merge sort for 2 sorted arrays --O(nlogn) right?
>
>
> On Tue, Sep 13, 2011 at 1:03 PM, jai gupta wrote:
>
>> @bharat: When each step of nishant's algo is O(n) how can it sum up to
>> O(nlogn)???
>>
>> On Tue, Sep 13, 2011 at 9:18 AM, bharatkumar bagana <
>> bagana.bharatku...@gmail.com> wrote:
>>
>>> @nishant : your algo takes O(nlogn) time with higher constant behind
>>> this.  can't we write better than this ?
>>> @sairam : will u pls provide implementation logic of u'r idea ..
>>>
>>>
>>> On Mon, Sep 12, 2011 at 12:43 PM, Sairam Ravu  wrote:
>>>
 By merging smaller trees into larger trees we can obtain a much more
 efficient solution.




 --
 With love and regards,
 Sairam Ravu
 I M. Tech(CS)
 Sri Sathya Sai Institute of Higher Learning
 "To live life, you must think it, measure it, experiment with it,
 dance it, paint it, draw it, and calculate it"

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>>>
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