Re: factor 50.000 between std::list and std::set?

From:
Pete Becker <pete@versatilecoding.com>
Newsgroups:
comp.lang.c++
Date:
Mon, 25 Jun 2007 18:12:56 -0400
Message-ID:
<f5qdnXZhkqp0oB3bnZ2dnUVZ_u6rnZ2d@giganews.com>
desktop wrote:

Erik Wikstr?m wrote:

On 2007-06-25 22:21, desktop wrote:

If I have a sorted std::list with 1.000.000 elements it takes
1.000.000 operations to find element with value = 1.000.000 (need to
iterator through the whole list).

In comparison, if I have a std::set with 1.000.000 element it will
only take approx lg 1.000.000 = 20 operations! Can it really be true
that the difference is a factor of 1.000.000/20 = 50.000 in this case?

In operations yes, not necessarily in time. If the operations on the
list takes 1 time and the operations on the set takes 50,000 then
they'll be equally fast. This will of course not be true in any
implementation (the set will be significantly faster than the list)
but it shows that just because one container/algorithm has a better
asymptotic running time it will in fact perform better. All it says is
that for a sufficiently large set of input, the algorithm will perform
better.

In practice you'll often find that using a vector for small sets will
be faster than most other containers, even if you need to traverse the
whole vector.

Is it possible to make an exact measurement in the difference in time
for 1 operation for a set and a list?

Yes, but that's not what asymptotic complexity is about. Asymptotic
complexity measures how well an algorithm scales when you increase the
amount of data. It answers questions like: it takes twenty seconds to
find all the records matching X in my database; if I double the number
of data elements, how long will it take?

--

-- Pete
Roundhouse Consulting, Ltd. (www.versatilecoding.com)
Author of "The Standard C++ Library Extensions: a Tutorial and
Reference." (www.petebecker.com/tr1book)

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