If I have an array of data that I know to be sorted in increasing
order, and the array is less than 50 elements, and I want to find the
first element greater than a certain value, is a simple linear search
the best here(for loop from beginning to end of array)? It seems like
some other search algorithm like binary or whatever would be of no
benefit on this data set. 28 2725
joshc wrote: If I have an array of data that I know to be sorted in increasing order, and the array is less than 50 elements, and I want to find the first element greater than a certain value, is a simple linear search the best here(for loop from beginning to end of array)? It seems like some other search algorithm like binary or whatever would be of no benefit on this data set.
Alternatives
 hash table  insert n slements O(n); search O(1)
 quick sort  sort n elements O(n log n); search O(log n)
A hash table is close to optimal.
gtoomey
joshc wrote: If I have an array of data that I know to be sorted in increasing order, and the array is less than 50 elements, and I want to find the first element greater than a certain value, is a simple linear search the best here(for loop from beginning to end of array)? It seems like some other search algorithm like binary or whatever would be of no benefit on this data set.
Questions of efficiency are really outside the bounds
of the C language as such; there are many implementations
of C and the timing characteristics of a given operation
differ from one implementation to the next.
Still, for such a small array it seems likely (not
certain, of course) that the difference between a linear
search and a binary search will be negligible. The way
to find out, of course, is to implement the search both
ways and measure. Even then, of course, the result will
only be valid for the implementation at hand and will not
necessarily hold for others.

Eric Sosman es*****@acmdotorg.invalid
I realize this, but still, regardless, there are algorithms that are in
general better than others. Perhaps you could suggest a more general
programming newsgroup for this type of question? I remember coming
across one some time ago but am having trouble finding it. It was a
programming group in general.
Eric Sosman wrote: joshc wrote: If I have an array of data that I know to be sorted in increasing order, and the array is less than 50 elements, and I want to find
the first element greater than a certain value, is a simple linear
search the best here(for loop from beginning to end of array)? It seems
like some other search algorithm like binary or whatever would be of no benefit on this data set.
Questions of efficiency are really outside the bounds of the C language as such; there are many implementations of C and the timing characteristics of a given operation differ from one implementation to the next.
Still, for such a small array it seems likely (not certain, of course) that the difference between a linear search and a binary search will be negligible. The way to find out, of course, is to implement the search both ways and measure. Even then, of course, the result will only be valid for the implementation at hand and will not necessarily hold for others.
 Eric Sosman es*****@acmdotorg.invalid
joshc wrote: I realize this, but still, regardless, there are algorithms that are
in general better than others. Perhaps you could suggest a more general programming newsgroup for this type of question? I remember coming across one some time ago but am having trouble finding it. It was a programming group in general.
A long time ago I looked for some sort of generic "algorithms" group,
but the closest I found was for (primarily 3D) graphics algorithms. I
think you are thinking of comp.programming and that may be the best
spot.
In general the way to figure out how good an algorithm is, is using
"big O" This is just a way of saying, if you have an array of n items,
how many more loops will it take to find the answer as n increases. If
it is exponential then the algorithm isn't so good ( O(n^2) .) If it is
linear ( O(n) ) then it's pretty normal. And if it is logarithmic (
O(n^(1/2)) ) then that's pretty much as good as it gets. The only
modifying factor is that a more complex algorithm will take longer for
each iteration so for a small enough n, an O(n^2) can win over an
O(n^(1/2)).
If you do a brute force loop, this will be linear. If there are ten
items, it will at max take 10 loops. If there are 20 then 20, and if 30
then 30.
A binary search is able to cut off half the work each time so until you
double the size of the array there won't be any change in time. 1 item
will take 1 loop. 2 will take 2, 3 will take 2, 4 will take 3, 5>3,
6>3, 7>3, 8>4, etc. So this is a logorithmic and pretty much as good
as it gets. However it is harder to code and requires the computer to
do some extra stuff each loop so for a short enough array, it probably
isn't worth it.
Chris
Thanks for your reply Chris. I am familar with big O notation from my
algorithms class :). I am going to use a simple linear search due to
this being an embedded environment and concern over code size.
joshc wrote: I realize this, but still, regardless, there are algorithms that are in general better than others. Perhaps you could suggest a more general programming newsgroup for this type of question? I remember coming across one some time ago but am having trouble finding it. It was a programming group in general.
Chris Williams mentioned comp.programming, which I've
seen mentioned before but am not personally familiar with.
Given the small size ("less than 50 elements") of your
problem, though, I'll stick by my previous answer: the
difference between O(N) linear search and O(ln N) binary
search will probably be so small as to be difficult to
measure accurately. Keep in mind two things about bigOh:
It discards all constant factors, and it's only useful for
"sufficiently large" N. For small N, the constant factors
and even the lowerorder terms may be more important than
the asymptotic behavior.
Stepping back just a bit, permit me to question the
wisdom of fretting over this decision at an early stage in
the program development. Do you have any a priori reason
to believe the time for these searches will be significant?
If you need to perform ten million such searches per second
that might be the case  but if the program is going to do
anything other than searching it seems quite likely that the
other activities will have far more effect on the running
time than the searches will. A friend of mine used to speak
of picking the bottle caps off the beach so the sand would
be nice and clean around the rotting whale carcases ...
Jackson's Laws of Program Optimization:
First Law: Don't Do It.
Second Law (for experts only): Don't Do It Yet.

Eric Sosman es*****@acmdotorg.invalid
*** Rude topposting fixed ***
joshc wrote: Eric Sosman wrote: joshc wrote:
If I have an array of data that I know to be sorted in increasing order, and the array is less than 50 elements, and I want to find the first element greater than a certain value, is a simple linear search the best here(for loop from beginning to end of array)? It seems like some other search algorithm like binary or whatever would be of no benefit on this data set.
Questions of efficiency are really outside the bounds of the C language as such; there are many implementations of C and the timing characteristics of a given operation differ from one implementation to the next.
Still, for such a small array it seems likely (not certain, of course) that the difference between a linear search and a binary search will be negligible. The way to find out, of course, is to implement the search both ways and measure. Even then, of course, the result will only be valid for the implementation at hand and will not necessarily hold for others.
I realize this, but still, regardless, there are algorithms that are in general better than others. Perhaps you could suggest a more general programming newsgroup for this type of question? I remember coming across one some time ago but am having trouble finding it. It was a programming group in general.
comp.programming would be suitable.
Please don't toppost. Your answer belongs after (or intermixed
with) the material to which you reply, with nongermane stuff
snipped out.
As long as you only have 50 elements the complexity of anything
more elegant than a simple linear search suggest you shouldn't
bother. You can even avoid any need for sorting with a linear
search, except that you will have to check the entire array rather
than just values up to a threshold (one half, on average).

"If you want to post a followup via groups.google.com, don't use
the broken "Reply" link at the bottom of the article. Click on
"show options" at the top of the article, then click on the
"Reply" at the bottom of the article headers."  Keith Thompson
Gregory Toomey <no****@bigpond.com> wrote: joshc wrote:
If I have an array of data that I know to be sorted in increasing order, and the array is less than 50 elements, and I want to find the first element greater than a certain value, is a simple linear search the best here(for loop from beginning to end of array)? It seems like some other search algorithm like binary or whatever would be of no benefit on this data set. Alternatives  hash table  insert n slements O(n); search O(1)  quick sort  sort n elements O(n log n); search O(log n)
It's already known to be sorted.
A hash table is close to optimal.
For fewer than 50 elements?
Richard
On 15 Feb 2005 19:27:59 0800, in comp.lang.c , "joshc"
<jo********@gmail.com> wrote: I realize this, but still, regardless, there are algorithms that are in general better than others. Perhaps you could suggest a more general programming newsgroup for this type of question? I
comp.programming?

Mark McIntyre
CLC FAQ <http://www.eskimo.com/~scs/Cfaq/top.html>
CLC readme: <http://www.ungerhu.com/jxh/clc.welcome.txt>
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On 15 Feb 2005 18:35:49 0800, in comp.lang.c , "joshc"
<jo********@gmail.com> wrote: If I have an array of data that I know to be sorted in increasing order, and the array is less than 50 elements, and I want to find the first element greater than a certain value, is a simple linear search the best here(for loop from beginning to end of array)? It seems like some other search algorithm like binary or whatever would be of no benefit on this data set.
for such a small data set, unless the comparison of elements to your target
is horribly expensive or you loop repeatedly on the search, a linear search
will be perfectly adequate. For advice on general algos try
comp.programming.

Mark McIntyre
CLC FAQ <http://www.eskimo.com/~scs/Cfaq/top.html>
CLC readme: <http://www.ungerhu.com/jxh/clc.welcome.txt>
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On 15 Feb 2005 19:27:59 0800, in comp.lang.c , "joshc"
<jo********@gmail.com> wrote: I realize this, but still, regardless, there are algorithms that are in general better than others. Perhaps you could suggest a more general programming newsgroup for this type of question? I
comp.programming?

Mark McIntyre
CLC FAQ <http://www.eskimo.com/~scs/Cfaq/top.html>
CLC readme: <http://www.ungerhu.com/jxh/clc.welcome.txt>
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On 15 Feb 2005 19:27:59 0800, in comp.lang.c , "joshc"
<jo********@gmail.com> wrote: I realize this, but still, regardless, there are algorithms that are in general better than others. Perhaps you could suggest a more general programming newsgroup for this type of question? I
comp.programming?

Mark McIntyre
CLC FAQ <http://www.eskimo.com/~scs/Cfaq/top.html>
CLC readme: <http://www.ungerhu.com/jxh/clc.welcome.txt>
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On Tue, 15 Feb 2005 20:46:00 0800, Chris Williams wrote:
.... In general the way to figure out how good an algorithm is, is using "big O" This is just a way of saying, if you have an array of n items, how many more loops will it take to find the answer as n increases. If it is exponential then the algorithm isn't so good ( O(n^2) .)
That is polynomiual, exponential woul be something like O(2^n). E.g. an
algorithm that searched every bit patter of n bits.
If it is linear ( O(n) ) then it's pretty normal. And if it is logarithmic ( O(n^(1/2)) )
That is also polynomial although a better behaved one. Logarithmic is
O(log(n))
then that's pretty much as good as it gets.
There are O(1) algorithms. Hash table lookups are (or can be) effectively
O(1).
Lawrence
joshc wrote: If I have an array of data that I know to be sorted in increasing order, and the array is less than 50 elements, and I want to find the first element greater than a certain value, is a simple linear search the best here(for loop from beginning to end of array)? It seems like some other search algorithm like binary or whatever would be of no benefit on this data set.
You need to better define this procedure.
What is this "certain value"? Is this certain value guaranteed to
be in the array or not? If it isn't then search algrothm's may
be useless to find the first element after a certain value.
And what is "first element greater than a certain value". Greater
in element number or value? For example, what if there are two
or more "certain values" in the array. Do you want the element which
has a larger value or do you want the next element which might
contain a value equal to the "certain value"?

Al Bowers
Tampa, Fl USA
mailto: xa******@myrapidsys.com (remove the x to send email) http://www.geocities.com/abowers822/
Mr. CBFalconer, I'm pretty new to the newsgroups but how did I toppost?
I am using google groups so to avoid their buginess I clicked the show
options>reply button on the most recent post. Is that not what I am
*supposed* to do?
Al Bowers wrote: You need to better define this procedure.
What is this "certain value"? Is this certain value guaranteed to be in the array or not? If it isn't then search algrothm's may be useless to find the first element after a certain value.
And what is "first element greater than a certain value". Greater in element number or value? For example, what if there are two or more "certain values" in the array. Do you want the element which has a larger value or do you want the next element which might contain a value equal to the "certain value"?
Alright, everyone, no need to waste anymore time on this thread. In all
honesty I don't know whether the search is taking up a significant
amount of time, but I do know that some functions that perform the
linear search as part of their processing are accounting for most of
the execution time(I profiled it). I doubt it's the search though since
there are some multiplications and divisions in the functions.
I realize it was probably a stupid question to ask since the search is
probably not even what's slowing my code down.
Lawrence Kirby wrote: On Tue, 15 Feb 2005 20:46:00 0800, Chris Williams wrote: If it is exponential then the algorithm isn't so good ( O(n^2) .) That is polynomiual, exponential woul be something like O(2^n). E.g.
an algorithm that searched every bit patter of n bits.
Hm. Had thought exponential growth referred to _any_ curve which
increased "steepness" as you went along the x axis. If it is linear ( O(n) ) then it's pretty normal. And if it is logarithmic ( O(n^(1/2)) )
That is also polynomial although a better behaved one. Logarithmic is O(log(n))
=\ then that's pretty much as good as it gets.
There are O(1) algorithms. Hash table lookups are (or can be)
effectively O(1).
That makes sense. And in the example of the OP's array, if there was
some sort of pattern to the data you might be able to formulate an 0(1)
mathematical formula with which to access the array.
Thank you,
Chris
joshc wrote: Mr. CBFalconer, I'm pretty new to the newsgroups but how did I toppost? I am using google groups so to avoid their buginess I clicked the show options>reply button on the most recent post. Is that not what I am *supposed* to do?
Do that on the particular message you wish to reply to. Then
delete the quoted portions that are not germane to your reply.
Then put your reply AFTER (or intermixed with) the portions you are
replying to. That way the result stands by itself and reads
correctly.

"If you want to post a followup via groups.google.com, don't use
the broken "Reply" link at the bottom of the article. Click on
"show options" at the top of the article, then click on the
"Reply" at the bottom of the article headers."  Keith Thompson
"joshc" <jo********@gmail.com> writes: If I have an array of data that I know to be sorted in increasing order, and the array is less than 50 elements, and I want to find the first element greater than a certain value, is a simple linear search the best here(for loop from beginning to end of array)? It seems like some other search algorithm like binary or whatever would be of no benefit on this data set.
Gosh folks...
A linear search will take about 25 compares on the average.
A binary search will take about 6 compares on the average.
Roughly speaking, a reasonable guess is that the binary search will
run about 3 times as fast as the linear search. Whether that makes
any perceptible difference in the application or not is another
question altogether.
Programming a binary search should be something any competent
programmer can do almost as fast as he/she can write it down:
/* Return the smallest index of an element greater than
* the supplied argument x. If there is no such element,
* return the index where the element would be if there
* were one (which will be 'how_many' if how_many < 0
* is true).
*
* NEEDS: argument 'v' array be sorted in increasing
* order. NOT CHECKED.
*
* Disclaimer: not tested or compiled in any way.
*/
int
first_larger( SomeType v[], int how_many, SomeType x ){
int i = 0, j = how_many;
if( i >= j  v[0] > x ) return 0;
while( i + 1 != j ){
int m = (i + j) / 2;
if( v[m] <= x ) i = m;
else j = m;
}
return j;
}
And, just a few metacomments.
The comp.lang.c group isn't normally the place to ask this kind of
question; comp.programming is better.
If you asked this question because you got assigned it as homework,
then look over the comments and the code until you think you see how
it works, then stop looking at it and try to write the code yourself.
If you don't you're cheating yourself (and besides which karma will
get you :).
On 16 Feb 2005 19:04:00 0800, Tim Rentsch <tx*@alumnus.caltech.edu>
wrote: "joshc" <jo********@gmail.com> writes:
If I have an array of data that I know to be sorted in increasing order, and the array is less than 50 elements, and I want to find the first element greater than a certain value, is a simple linear search the best here(for loop from beginning to end of array)? It seems like some other search algorithm like binary or whatever would be of no benefit on this data set. Gosh folks...
A linear search will take about 25 compares on the average.
A binary search will take about 6 compares on the average.
Roughly speaking, a reasonable guess is that the binary search will run about 3 times as fast as the linear search. Whether that makes any perceptible difference in the application or not is another question altogether.
This isn't right. First of all you need two compares in the binary
search loop, one for the element compare, and one for the loop test,
so the number of compares is about 12. Secondly the binary search
loop requires an addition and a divide by 2. On the other hand the
linear compare loop only requires a compare. Programming a binary search should be something any competent programmer can do almost as fast as he/she can write it down:
I haven't checked your code; however coding a binary search completely
correctly is notoriously trickier than it seems. /* Return the smallest index of an element greater than * the supplied argument x. If there is no such element, * return the index where the element would be if there * were one (which will be 'how_many' if how_many < 0 * is true). * * NEEDS: argument 'v' array be sorted in increasing * order. NOT CHECKED. * * Disclaimer: not tested or compiled in any way. */
int first_larger( SomeType v[], int how_many, SomeType x ){ int i = 0, j = how_many;
if( i >= j  v[0] > x ) return 0;
while( i + 1 != j ){ int m = (i + j) / 2; if( v[m] <= x ) i = m; else j = m; }
return j; }
And, just a few metacomments.
The comp.lang.c group isn't normally the place to ask this kind of question; comp.programming is better.
True. If you asked this question because you got assigned it as homework, then look over the comments and the code until you think you see how it works, then stop looking at it and try to write the code yourself. If you don't you're cheating yourself (and besides which karma will get you :).
IMO it doesn't sound like a homework question; rather it sounds like
the sort of question that an inexperienced programmer would ask.
Richard Harter, cr*@tiac.net http://home.tiac.net/~cri, http://www.varinoma.com
All my life I wanted to be someone;
I guess I should have been more specific. cr*@tiac.net (Richard Harter) writes: On 16 Feb 2005 19:04:00 0800, Tim Rentsch <tx*@alumnus.caltech.edu> wrote:
"joshc" <jo********@gmail.com> writes:
If I have an array of data that I know to be sorted in increasing order, and the array is less than 50 elements, and I want to find the first element greater than a certain value, is a simple linear search the best here(for loop from beginning to end of array)? It seems like some other search algorithm like binary or whatever would be of no benefit on this data set.
Gosh folks...
A linear search will take about 25 compares on the average.
A binary search will take about 6 compares on the average.
Roughly speaking, a reasonable guess is that the binary search will run about 3 times as fast as the linear search. Whether that makes any perceptible difference in the application or not is another question altogether.
This isn't right. First of all you need two compares in the binary search loop, one for the element compare, and one for the loop test, so the number of compares is about 12. Secondly the binary search loop requires an addition and a divide by 2. On the other hand the linear compare loop only requires a compare.
The linear search needs two compares per loop iteration also  one to
test the value, and one to check the loop index.
The binary search needs an add and a divide by 2 (usually a shift);
also one assignment. The linear search needs an increment. Since
25/6 > 4, I think "about 3 as fast" is a fair statement, especially
since it was given as a "reasonable guess". Programming a binary search should be something any competent programmer can do almost as fast as he/she can write it down:
I haven't checked your code; however coding a binary search completely correctly is notoriously trickier than it seems.
I used to think that too before I learned how to write a binary search
that is both simple and solid. I suspect the idea that writing a
binary search is tricky was much of the motivation of the OP; that's
part of why I wrote this.
Incidentally, looking over the code, it still looks right to me. The
comment, however, has an error  should read 'how_many >= 0'. And for
those who notice nits, "increasing" should be "nondecreasing"
instead. /* Return the smallest index of an element greater than * the supplied argument x. If there is no such element, * return the index where the element would be if there * were one (which will be 'how_many' if how_many < 0 * is true). * * NEEDS: argument 'v' array be sorted in increasing * order. NOT CHECKED. * * Disclaimer: not tested or compiled in any way. */
int first_larger( SomeType v[], int how_many, SomeType x ){ int i = 0, j = how_many;
if( i >= j  v[0] > x ) return 0;
while( i + 1 != j ){ int m = (i + j) / 2; if( v[m] <= x ) i = m; else j = m; }
return j; }
On Wed, 16 Feb 2005 05:17:17 0800, Chris Williams wrote: Lawrence Kirby wrote: On Tue, 15 Feb 2005 20:46:00 0800, Chris Williams wrote: > If > it is exponential then the algorithm isn't so good ( O(n^2) .)
That is polynomiual, exponential woul be something like O(2^n). E.g. an algorithm that searched every bit patter of n bits.
Hm. Had thought exponential growth referred to _any_ curve which increased "steepness" as you went along the x axis.
Exponential typically refers to somthing of the form X^N where ^ is the
power operator. It is sometimes loosely used to refer to something that
grows faster than polynomial (i.e. N^X for arbirary large X). For example
2^N will exceed N^X with sufficiently large N, no matter how large you
make X.
Lawrence
In article <kf*************@alumnus.caltech.edu>, Tim Rentsch <tx*@alumnus.caltech.edu> writes: cr*@tiac.net (Richard Harter) writes: On 16 Feb 2005 19:04:00 0800, Tim Rentsch <tx*@alumnus.caltech.edu> wrote:"joshc" <jo********@gmail.com> writes:
> If I have an array of data that I know to be sorted in increasing > order, and the array is less than 50 elements, and I want to find the > first element greater than a certain value, is a simple linear search > the best here(for loop from beginning to end of array)?
A linear search will take about 25 compares on the average.
A binary search will take about 6 compares on the average.
Roughly speaking, a reasonable guess is that the binary search will run about 3 times as fast as the linear search. Whether that makes any perceptible difference in the application or not is another question altogether.
However, a linear search will correctly predict nearly all the
branches, while a binary search will mispredict half of them, on
average.
Unless comparison time dominates, I wouldn't call your guess
"reasonable", for that reason alone  and there are others.
(Consider we know nothing of the size of items and the memory
management features of the platform, so we can't guess whether the
binary search will tend to cause more cache misses, for example.)
This isn't right. First of all you need two compares in the binary search loop, one for the element compare, and one for the loop test, so the number of compares is about 12. Secondly the binary search loop requires an addition and a divide by 2. On the other hand the linear compare loop only requires a compare.
The linear search needs two compares per loop iteration also  one to test the value, and one to check the loop index.
Any decent optimizer will unroll the loop, so loop index comparisons
will only add N/O comparisons, where O is the unrolling factor.
And if loop index comparisons take about as long as value comparisons,
then the latter must be very quick  so you fall foul of the branch
misprediction penalty of binary search.
And this is why premature optimization is a poor idea.
Now, in this case, the OP did follow up by stating that profiling had
indicated his search function was a hot spot; and since that's the
case, he might indeed want to try various alternatives. If compar
isons are very expensive, the binary search might even help  though
I suspect he'd be better off revisiting his data structure, as
various people suggested.

Michael Wojcik mi************@microfocus.com
Every allegiance to some community eventually involves such a fetish,
which functions as the disavowal of its founding crime: is not 'America'
the fetish of an infinitely open space enabling every individual to
pursue happiness in his or her own way?  Slavoj Zizek
On 17 Feb 2005 02:30:11 0800, Tim Rentsch <tx*@alumnus.caltech.edu>
wrote: cr*@tiac.net (Richard Harter) writes:
On 16 Feb 2005 19:04:00 0800, Tim Rentsch <tx*@alumnus.caltech.edu> wrote:
>"joshc" <jo********@gmail.com> writes: > >> If I have an array of data that I know to be sorted in increasing >> order, and the array is less than 50 elements, and I want to find the >> first element greater than a certain value, is a simple linear search >> the best here(for loop from beginning to end of array)? It seems like >> some other search algorithm like binary or whatever would be of no >> benefit on this data set. > >Gosh folks... > >A linear search will take about 25 compares on the average. > >A binary search will take about 6 compares on the average. > >Roughly speaking, a reasonable guess is that the binary search will >run about 3 times as fast as the linear search. Whether that makes >any perceptible difference in the application or not is another >question altogether. This isn't right. First of all you need two compares in the binary search loop, one for the element compare, and one for the loop test, so the number of compares is about 12. Secondly the binary search loop requires an addition and a divide by 2. On the other hand the linear compare loop only requires a compare.
The linear search needs two compares per loop iteration also  one to test the value, and one to check the loop index.
One comparison suffices if you use a sentinel. The following code
fragment is illustrative (but unchecked).
if (data[0] >= testval) return 0;
ptr = data + data_length;
while (*ptr >= testval);
return ptrdata;
One decrement, one compare per element. The binary search needs an add and a divide by 2 (usually a shift); also one assignment. The linear search needs an increment. Since 25/6 > 4, I think "about 3 as fast" is a fair statement, especially since it was given as a "reasonable guess".
It's a reasonable guess if you don't do the arithmetic and count
operations, and if you've never benchmarked the two approaches. For a
linear search the costs per iteration are
1 data compare & branch
1 increment/decrement
For the binary search the costs per iteration are:
1 data compare & branch
1/2 branch (then clause)
1 index compare and branch
1 addition
1 assignment
1 divide by 2
1 addition by 1 (avoidable)
If we just count operations that's 2 for a linear search and 6.5 for a
binary search which is just about a wash. However the code for the
linear search is a better candidate for optimization. Some years ago
I ran benchmarks on just this question; the break even point was
somewhere around 50. I expect that the results would be about the
same on more modern machines.
>Programming a binary search should be something any competent >programmer can do almost as fast as he/she can write it down: I haven't checked your code; however coding a binary search completely correctly is notoriously trickier than it seems.
I used to think that too before I learned how to write a binary search that is both simple and solid. I suspect the idea that writing a binary search is tricky was much of the motivation of the OP; that's part of why I wrote this.
It's not just me or you; errors in writing binary searches are (or
were) common. IIRC Bentley makes just that observation in
"Programming Pearls" and, of course, Dijkstra had some pungent
comments on the subject. Incidentally, looking over the code, it still looks right to me. The comment, however, has an error  should read 'how_many >= 0'. And for those who notice nits, "increasing" should be "nondecreasing" instead.
Well you see, "looks right" is not quite as reassuring as "proven
right". I expect it probably is  most of us reuse validated code
schemas for these little exercises.
> /* Return the smallest index of an element greater than > * the supplied argument x. If there is no such element, > * return the index where the element would be if there > * were one (which will be 'how_many' if how_many < 0 > * is true). > * > * NEEDS: argument 'v' array be sorted in increasing > * order. NOT CHECKED. > * > * Disclaimer: not tested or compiled in any way. > */ > > int > first_larger( SomeType v[], int how_many, SomeType x ){ > int i = 0, j = how_many; > > if( i >= j  v[0] > x ) return 0; > > while( i + 1 != j ){ > int m = (i + j) / 2; > if( v[m] <= x ) i = m; > else j = m; > } > > return j; > } >
Richard Harter, cr*@tiac.net http://home.tiac.net/~cri, http://www.varinoma.com
All my life I wanted to be someone;
I guess I should have been more specific. cr*@tiac.net (Richard Harter) writes: On 17 Feb 2005 02:30:11 0800, Tim Rentsch <tx*@alumnus.caltech.edu> wrote:
cr*@tiac.net (Richard Harter) writes:
On 16 Feb 2005 19:04:00 0800, Tim Rentsch <tx*@alumnus.caltech.edu> wrote:
>"joshc" <jo********@gmail.com> writes: > >> If I have an array of data that I know to be sorted in increasing >> order, and the array is less than 50 elements, and I want to find the >> first element greater than a certain value, is a simple linear search >> the best here(for loop from beginning to end of array)? It seems like >> some other search algorithm like binary or whatever would be of no >> benefit on this data set. > >Gosh folks... > >A linear search will take about 25 compares on the average. > >A binary search will take about 6 compares on the average. > >Roughly speaking, a reasonable guess is that the binary search will >run about 3 times as fast as the linear search. Whether that makes >any perceptible difference in the application or not is another >question altogether.
This isn't right. First of all you need two compares in the binary search loop, one for the element compare, and one for the loop test, so the number of compares is about 12. Secondly the binary search loop requires an addition and a divide by 2. On the other hand the linear compare loop only requires a compare.
The linear search needs two compares per loop iteration also  one to test the value, and one to check the loop index.
One comparison suffices if you use a sentinel. The following code fragment is illustrative (but unchecked).
if (data[0] >= testval) return 0; ptr = data + data_length; while (*ptr >= testval); return ptrdata;
One decrement, one compare per element.
The binary search needs an add and a divide by 2 (usually a shift); also one assignment. The linear search needs an increment. Since 25/6 > 4, I think "about 3 as fast" is a fair statement, especially since it was given as a "reasonable guess".
It's a reasonable guess if you don't do the arithmetic and count operations, and if you've never benchmarked the two approaches. For a linear search the costs per iteration are
1 data compare & branch 1 increment/decrement
For the binary search the costs per iteration are:
1 data compare & branch 1/2 branch (then clause) 1 index compare and branch 1 addition 1 assignment 1 divide by 2 1 addition by 1 (avoidable)
If we just count operations that's 2 for a linear search and 6.5 for a binary search which is just about a wash. However the code for the linear search is a better candidate for optimization. Some years ago I ran benchmarks on just this question; the break even point was somewhere around 50. I expect that the results would be about the same on more modern machines.
>Programming a binary search should be something any competent >programmer can do almost as fast as he/she can write it down:
I haven't checked your code; however coding a binary search completely correctly is notoriously trickier than it seems.
I used to think that too before I learned how to write a binary search that is both simple and solid. I suspect the idea that writing a binary search is tricky was much of the motivation of the OP; that's part of why I wrote this.
It's not just me or you; errors in writing binary searches are (or were) common. IIRC Bentley makes just that observation in "Programming Pearls" and, of course, Dijkstra had some pungent comments on the subject.
Incidentally, looking over the code, it still looks right to me. The comment, however, has an error  should read 'how_many >= 0'. And for those who notice nits, "increasing" should be "nondecreasing" instead.
Well you see, "looks right" is not quite as reassuring as "proven right". I expect it probably is  most of us reuse validated code schemas for these little exercises.
> /* Return the smallest index of an element greater than > * the supplied argument x. If there is no such element, > * return the index where the element would be if there > * were one (which will be 'how_many' if how_many < 0 > * is true). > * > * NEEDS: argument 'v' array be sorted in increasing > * order. NOT CHECKED. > * > * Disclaimer: not tested or compiled in any way. > */ > > int > first_larger( SomeType v[], int how_many, SomeType x ){ > int i = 0, j = how_many; > > if( i >= j  v[0] > x ) return 0; > > while( i + 1 != j ){ > int m = (i + j) / 2; > if( v[m] <= x ) i = m; > else j = m; > } > > return j; > } >
Actually I think we are mostly in agreement here, despite the apparent
differences in the postings. There are some different assumptions and
the language used may have been misleading in places. Let's see if
those can be straightened out.
The phrase "is a reasonable guess" (for the performance factor of
three) probably is better put as "is a reasonable back of the envelope
estimate". That's meant with the usual errors bars and ignoring of
(unknown or unspecified) secondorder effects.
I admit, the estimate was skewed toward the case where the element
compare was "expensive" relative to other operations. That assumption
is reasonably good if the elements being compared are strings; fair
if the elements being compared are floating point or mixedmode; poor
if the elements being compared are int's. I still think it's a fair
assumption for calculating a BOTE estimate, since it's standard in
comparing algorithm performance; but you're right that it's not a
good assumption when the elements being compared are int's.
You're also right that, for int arrays of 50 elements, a straight
linear search (not with sentinel) runs only a little slower than a
binary search like the one I illustrated. Out of curiosity I ran a
few benchmarks, and the simple linear search was only 25% slower than
the simple binary search. (In case anyone was wondering, the platform
here is an x86 architecture, with gcc O2 doing the compiles.)
Using a sentinel on the linear search is nice technique, and
definitely an improvement. (Incidentally, the code snippet posted has
two errors  the two >= comparisons should be > comparisons, and the
return value should be 'ptrdata + 1' rather than 'ptrdata'.) A
linear search using the sentinel technique ran roughly 1.7 times as
fast as a simple linear search, or 40% faster than a simple binary
search. Completely unrolling the linear search  which is reasonable
for only 50 elements  gives a 1.2x speedup relative to the sentinel
linear, or a factor of almost 2.1 over the original simple linear
search. Nice!
I will grant you that many programmers will get binary search wrong
(and that this observation may have been made by messieurs Bentley and
Dijkstra). However, I believe this result obtains not because binary
search is inherently difficult, but because it is practiced wrongly by
less competent programmers, and because the myth of it being difficult
is perpetuated by instructors who don't teach it very well. When I
said the binary search code I wrote "looks right" I meant it looked
like there were no clerical errors; I'm sure the invariants were
right, as I was sure they were when I first posted it. It's become
second nature for me to make sure loop invariants are right, and
anyone who adopts this discipline can program binary searches with
confidence. (Come to think of it, asking a candidate to program a
simple binary search might make a good interview question.)
Fortunately for the poor binary search, it still has something to
offer in response to the performance of linear/sentinel search and
unrolled linear search in our 'int array of 50 element' benchmarks.
Combining two levels of binary comparison and then doing a simple
linear search (that is, not using the sentinel technique) runs a tad
faster (roughly 10%) than a linear search with sentinel .
The function
uint
binary_sentinel( int v[], uint n, int x ){
/** NEEDS: n > 0 **/
if( v[n/2] > x ){
uint i = 0;
while( v[i] <= x ) i++;
return i;
} else {
while( v[n] > x ) {}
return n+1;
}
}
which combines a single binary split with a linear/sentinel search,
outperforms even the fully unrolled linear search. (Here also the
speedup is roughly 10%.)
Finally, if we compare fully unrolled linear search and fully unrolled
binary search  both reasonable on 50 element arrays if the search is
on the critical path for performance  the binary search is 2.3 times
as fast as the linear search. The fully unrolled binary search also
has the nice property that it can work on arrays of any size up to 50
(ok, 63), rather than just a single fixed size of 50.
That all fit with what you were saying? mw*****@newsguy.com (Michael Wojcik) writes: In article <kf*************@alumnus.caltech.edu>, Tim Rentsch <tx*@alumnus.caltech.edu> writes: cr*@tiac.net (Richard Harter) writes: On 16 Feb 2005 19:04:00 0800, Tim Rentsch <tx*@alumnus.caltech.edu> wrote: >"joshc" <jo********@gmail.com> writes: > >> If I have an array of data that I know to be sorted in increasing >> order, and the array is less than 50 elements, and I want to find the >> first element greater than a certain value, is a simple linear search >> the best here(for loop from beginning to end of array)? > >A linear search will take about 25 compares on the average. > >A binary search will take about 6 compares on the average. > >Roughly speaking, a reasonable guess is that the binary search will >run about 3 times as fast as the linear search. Whether that makes >any perceptible difference in the application or not is another >question altogether. However, a linear search will correctly predict nearly all the branches, while a binary search will mispredict half of them, on average.
Unless comparison time dominates, I wouldn't call your guess "reasonable", for that reason alone  and there are others. (Consider we know nothing of the size of items and the memory management features of the platform, so we can't guess whether the binary search will tend to cause more cache misses, for example.) This isn't right. First of all you need two compares in the binary search loop, one for the element compare, and one for the loop test, so the number of compares is about 12. Secondly the binary search loop requires an addition and a divide by 2. On the other hand the linear compare loop only requires a compare.
The linear search needs two compares per loop iteration also  one to test the value, and one to check the loop index.
Any decent optimizer will unroll the loop, so loop index comparisons will only add N/O comparisons, where O is the unrolling factor.
And if loop index comparisons take about as long as value comparisons, then the latter must be very quick  so you fall foul of the branch misprediction penalty of binary search.
And this is why premature optimization is a poor idea.
Now, in this case, the OP did follow up by stating that profiling had indicated his search function was a hot spot; and since that's the case, he might indeed want to try various alternatives. If compar isons are very expensive, the binary search might even help  though I suspect he'd be better off revisiting his data structure, as various people suggested.
I have the sense you think I was trying to provide some sort of
detailed performance analysis. I wasn't. There was no optimization 
premature or otherwise  in my posting. There were only observations,
no recommendation.
What I was trying to do is give a notverydeep, but helpful, answer
to a question about whether binary searching would be an improvement
over linear searching. The answer I gave was intended to address the
question asked, as it was stated.
I was also trying to illustrate a way of thinking that would likely to
be helpful to someone thinking about whether it might be worth some
effort trying to improve the performance of this particular function.
I don't specialize in performance enhancement; but engineers that I
know who do (and who are good at what they do) say that big gains in
performance are almost always due to algorithmic improvements rather
than fussing with lowlevel machine details. I think that view is
borne out here; please see my response to Richard Harter's posting
for details.
On 23 Feb 2005 02:41:17 0800, Tim Rentsch <tx*@alumnus.caltech.edu>
wrote: Actually I think we are mostly in agreement here, despite the apparent differences in the postings. There are some different assumptions and the language used may have been misleading in places. Let's see if those can be straightened out.
Agreed. (Mostly :)) The phrase "is a reasonable guess" (for the performance factor of three) probably is better put as "is a reasonable back of the envelope estimate". That's meant with the usual errors bars and ignoring of (unknown or unspecified) secondorder effects.
Yes and no. The problem here is that we are comparing algorithms with
different cost functions on a restricted range. If we just use number
of iterations for our reasonable guess we're ignoring cost per
iteration. The "reasonable guess" will be off by some constant
factor. This doesn't matter for large n; big O dominants. It's a
different matter for a small restricted range of n. Still, it's a
reasonable guess. I admit, the estimate was skewed toward the case where the element compare was "expensive" relative to other operations. That assumption is reasonably good if the elements being compared are strings; fair if the elements being compared are floating point or mixedmode; poor if the elements being compared are int's. I still think it's a fair assumption for calculating a BOTE estimate, since it's standard in comparing algorithm performance; but you're right that it's not a good assumption when the elements being compared are int's.
Granted. As a caveat comparison costs on strings are distribution
dependent. For quasiuniform distributions comparison costs for
binary searches will be less than those of linear searches. Surprise! You're also right that, for int arrays of 50 elements, a straight linear search (not with sentinel) runs only a little slower than a binary search like the one I illustrated. Out of curiosity I ran a few benchmarks, and the simple linear search was only 25% slower than the simple binary search. (In case anyone was wondering, the platform here is an x86 architecture, with gcc O2 doing the compiles.)
Using a sentinel on the linear search is nice technique, and definitely an improvement. (Incidentally, the code snippet posted has two errors  the two >= comparisons should be > comparisons, and the return value should be 'ptrdata + 1' rather than 'ptrdata'.)
Oops.
A linear search using the sentinel technique ran roughly 1.7 times as fast as a simple linear search, or 40% faster than a simple binary search. Completely unrolling the linear search  which is reasonable for only 50 elements  gives a 1.2x speedup relative to the sentinel linear, or a factor of almost 2.1 over the original simple linear search. Nice!
I will grant you that many programmers will get binary search wrong (and that this observation may have been made by messieurs Bentley and Dijkstra). However, I believe this result obtains not because binary search is inherently difficult, but because it is practiced wrongly by less competent programmers, and because the myth of it being difficult is perpetuated by instructors who don't teach it very well. When I said the binary search code I wrote "looks right" I meant it looked like there were no clerical errors; I'm sure the invariants were right, as I was sure they were when I first posted it. It's become second nature for me to make sure loop invariants are right, and anyone who adopts this discipline can program binary searches with confidence. (Come to think of it, asking a candidate to program a simple binary search might make a good interview question.)
Ah, okay. I agree, programming a simple binary search would make a
good interview question. Fortunately for the poor binary search, it still has something to offer in response to the performance of linear/sentinel search and unrolled linear search in our 'int array of 50 element' benchmarks.
Combining two levels of binary comparison and then doing a simple linear search (that is, not using the sentinel technique) runs a tad faster (roughly 10%) than a linear search with sentinel .
The function
uint binary_sentinel( int v[], uint n, int x ){ /** NEEDS: n > 0 **/ if( v[n/2] > x ){ uint i = 0; while( v[i] <= x ) i++; return i; } else { while( v[n] > x ) {} return n+1; } }
which combines a single binary split with a linear/sentinel search, outperforms even the fully unrolled linear search. (Here also the speedup is roughly 10%.)
Finally, if we compare fully unrolled linear search and fully unrolled binary search  both reasonable on 50 element arrays if the search is on the critical path for performance  the binary search is 2.3 times as fast as the linear search. The fully unrolled binary search also has the nice property that it can work on arrays of any size up to 50 (ok, 63), rather than just a single fixed size of 50.
You can use a switch for the unrolled linear search. Still, I like
the unrolled binary search. That all fit with what you were saying?
Pretty much. Whether or not optimization is premature, successful
optimization requires a full assessment of alternatives, a full
understanding of the data being operated upon, and careful
measurement.
Richard Harter, cr*@tiac.net http://home.tiac.net/~cri, http://www.varinoma.com
All my life I wanted to be someone;
I guess I should have been more specific. cr*@tiac.net (Richard Harter) writes: On 23 Feb 2005 02:41:17 0800, Tim Rentsch <tx*@alumnus.caltech.edu> wrote: [snip] Finally, if we compare fully unrolled linear search and fully unrolled binary search  both reasonable on 50 element arrays if the search is on the critical path for performance  the binary search is 2.3 times as fast as the linear search. The fully unrolled binary search also has the nice property that it can work on arrays of any size up to 50 (ok, 63), rather than just a single fixed size of 50. You can use a switch for the unrolled linear search.
I tried code that used a 'switch' to vector into an unrolled linear
search. On this problem at least, the simple loopusingsentinel ran
faster, by about 20%.
Still, I like the unrolled binary search.
I have an interesting story about that. I tried two versions of the
unrolled binary search  one version like this:
if( v[3] > x )
if( v[1] > x ) return v[0] > x ? 0 : 1;
else return v[2] > x ? 2 : 3;
else
if( v[5] > x ) return v[4] > x ? 4 : 5;
else return v[6] > x ? 6 : 7;
(only of course moreso, to cover all 50 cases), where the number of
elements in the array must match exactly the unrolling in the code;
and another version like this:
if( n < 4  v[3] > x )
if( n < 2  v[1] > x ) return n < 1  v[0] > x ? 0 : 1;
else return n < 3  v[2] > x ? 2 : 3;
else
if( n < 6  v[5] > x ) return n < 5  v[4] > x ? 4 : 5;
else return n < 7  v[6] > x ? 6 : 7;
where the number of array elements is checked in parallel construction
with the tests of the values, so now any array size up to the unrolled
size will work. To my surprise the second version actually ran faster
than the first  not by much, only a few percent, but it was nice to
get the more general functionality and have it be "better than free".
Incidentally, I have no explanation for why this might be so. The
code in the second case was roughly twice as many instructions down
each path. I guess branch prediction was doing its thing. That all fit with what you were saying?
Pretty much. Whether or not optimization is premature, successful optimization requires a full assessment of alternatives, a full understanding of the data being operated upon, and careful measurement.
Roger that. This discussion thread is closed Replies have been disabled for this discussion. Similar topics
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