Re: Algorithm for randomly choosing a question

Omer Zak <w1-W6cp89mEpD1mR6Xm/[email protected]> Sun, 08 Jul 2012 11:14:30 +0300
Newsgroups gmane.culture.hackers.israel
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Hello Nadav,
Thanks for your answer.

I ended up implementing something similar to your proposal.
The questions are stored in a SQLite database, so I don't mind at all
O(N) disk space consumption.  I did want O(1) RAM consumption, as RAM is
to be considered as a scarce resource in smartphones.

The number of probability classes is finite (3 if to be exact).  In
principle, it is possible to have a more sophisticated algorithm for
selecting the next question (with unlimited, time varying probability
classes) but I don't think that the subject matter warrants this kind of
sophistication.

The disk files for each probability class are being kept implicitly - as
result sets of queries for each probability class.
The actual performance of the algorithm (O(1), O(N) or whatever)
actually depends upon the DB performance, which I didn't bother to
benchmark or fine tune as a function of the number of questions.

I did not (even implicitly) implement the optimization that you
suggested for O(1) disk filee modifications.

--- Omer


On Sun, 2012-07-08 at 10:23 +0300, Nadav Har'El wrote:
> On Sat, Jul 07, 2012, Omer Zak wrote about "Re: [hackers-il] Algorithm for randomly choosing a question":
> > The proposed approach has the problem of memory consumption of order of
> > O(N) (where N is the number of the questions).  I'd like to see an
> > algorithm whose memory consumption is closer to O(1) than to O(N).
> 
> Omer, here is an O(1) *RAM* algorithm. Note that you still have O(N)
> disk usage, of course - there are N questions, and they need to be saved
> somewhere, and so is the history of the success for them.
> If you drop the O(1) memory requirement (which I think is an overkill for
> any type of modern computer), you can make things simpler.
> 
> Note - I assume the number of probability classes (in your example,
> 1, 1/2 and 1/100, if I remember correctly) is constant (O(1)) and not
> O(N).
> 
> Keep on disk a file for each probability class - one list of questions
> with normal probability (1), another list of questions with half
> probability, and a third list of questions with 1/100 probability.
> Each will be a list of numbers (indexing questions stored in a separate
> file).
> 
> In *memory*, keep the number of questions in each class: n1, n2, n3,
> and the partial probability sums:
> 	p1 = n1*1
> 	p2 = n1*1 + n2*(1/2.)
> 	p3 = n1*1 + n2*(1/2.) + n3*(1/100.)
> 
> Each time you want to draw a random question, pick a random number
> between 0 and p3. If it's between 0 and p1, you decided to take a
> question from class 1. If it's between p1 and p2, you decided to take
> a question from class 3. If it's between p2 and p3, then from class 3.
> 
> You decide *which* question to take in the obvious way - e.g., if you
> got a random number p between p1 and p2, then the question number in the
> class 2 list is m=(p-p1)/(1/2). You then need to look at the m'th
> position in the on-disk list of class 2 questions, to get the actual
> index of the question.
> 
> Finally, when the user answers you need to update your data. You need
> to remove the question from the previous class (to do this in O(1) time,
> just move the last element of the list into the newly formed hole),
> and to add it to the new class (put it last), and of course update
> n1,n2,n3 and p1,p2,p3.
> 
> Again, if you don't mind O(N) memory usage - actually just N*4 bytes -
> then I suggest that you do keep the list of questions - just their
> numbers - in memory. Then you won't need to read and write the disk
> all the time.
> 
> Nadav.
> 
> P.S. This is of course a variant on the classic shuffling (or random
> permutation) algorithm.  In the shuffling algorithm, you need to draw
> random questions from the list, but after you used a question, you don't
> want to see it again (its probability becomes zero). Instead of keeping
> the used questions on the list (and getting O(N^2) time complexity for
> the whole shuffle operation), the trick is to move them to the end of
> the list, and to remember how many questions we still have (in the
> beginning of the list) to draw from.
-- 
Sent from a PC running a top secret test version of Windows 97.
My own blog is at http://www.zak.co.il/tddpirate/

My opinions, as expressed in this E-mail message, are mine alone.
They do not represent the official policy of any organization with which
I may be affiliated in any way.
WARNING TO SPAMMERS:  at http://www.zak.co.il/spamwarning.html


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      <p>Hello Nadav,<br>
Thanks for your answer.<br>
<br>
I ended up implementing something similar to your proposal.<br>
The questions are stored in a SQLite database, so I don't mind at all<br>
O(N) disk space consumption.  I did want O(1) RAM consumption, as RAM is<br>
to be considered as a scarce resource in smartphones.<br>
<br>
The number of probability classes is finite (3 if to be exact).  In<br>
principle, it is possible to have a more sophisticated algorithm for<br>
selecting the next question (with unlimited, time varying probability<br>
classes) but I don't think that the subject matter warrants this kind of<br>
sophistication.<br>
<br>
The disk files for each probability class are being kept implicitly - as<br>
result sets of queries for each probability class.<br>
The actual performance of the algorithm (O(1), O(N) or whatever)<br>
actually depends upon the DB performance, which I didn't bother to<br>
benchmark or fine tune as a function of the number of questions.<br>
<br>
I did not (even implicitly) implement the optimization that you<br>
suggested for O(1) disk filee modifications.<br>
<br>
--- Omer<br>
<br>
On Sun, 2012-07-08 at 10:23 &#43;0300, Nadav Har'El wrote:<br>
&gt; On Sat, Jul 07, 2012, Omer Zak wrote about &quot;Re: [hackers-il] Algorithm for randomly choosing a question&quot;:<br>
&gt; &gt; The proposed approach has the problem of memory consumption of order of<br>
&gt; &gt; O(N) (where N is the number of the questions).  I'd like to see an<br>
&gt; &gt; algorithm whose memory consumption is closer to O(1) than to O(N).<br>
&gt; <br>
&gt; Omer, here is an O(1) *RAM* algorithm. Note that you still have O(N)<br>
&gt; disk usage, of course - there are N questions, and they need to be saved<br>
&gt; somewhere, and so is the history of the success for them.<br>
&gt; If you drop the O(1) memory requirement (which I think is an overkill for<br>
&gt; any type of modern computer), you can make things simpler.<br>
&gt; <br>
&gt; Note - I assume the number of probability classes (in your example,<br>
&gt; 1, 1/2 and 1/100, if I remember correctly) is constant (O(1)) and not<br>
&gt; O(N).<br>
&gt; <br>
&gt; Keep on disk a file for each probability class - one list of questions<br>
&gt; with normal probability (1), another list of questions with half<br>
&gt; probability, and a third list of questions with 1/100 probability.<br>
&gt; Each will be a list of numbers (indexing questions stored in a separate<br>
&gt; file).<br>
&gt; <br>
&gt; In *memory*, keep the number of questions in each class: n1, n2, n3,<br>
&gt; and the partial probability sums:<br>
&gt; 	p1 = n1*1<br>
&gt; 	p2 = n1*1 + n2*(1/2.)<br>
&gt; 	p3 = n1*1 + n2*(1/2.) + n3*(1/100.)<br>
&gt; <br>
&gt; Each time you want to draw a random question, pick a random number<br>
&gt; between 0 and p3. If it's between 0 and p1, you decided to take a<br>
&gt; question from class 1. If it's between p1 and p2, you decided to take<br>
&gt; a question from class 3. If it's between p2 and p3, then from class 3.<br>
&gt; <br>
&gt; You decide *which* question to take in the obvious way - e.g., if you<br>
&gt; got a random number p between p1 and p2, then the question number in the<br>
&gt; class 2 list is m=(p-p1)/(1/2). You then need to look at the m'th<br>
&gt; position in the on-disk list of class 2 questions, to get the actual<br>
&gt; index of the question.<br>
&gt; <br>
&gt; Finally, when the user answers you need to update your data. You need<br>
&gt; to remove the question from the previous class (to do this in O(1) time,<br>
&gt; just move the last element of the list into the newly formed hole),<br>
&gt; and to add it to the new class (put it last), and of course update<br>
&gt; n1,n2,n3 and p1,p2,p3.<br>
&gt; <br>
&gt; Again, if you don't mind O(N) memory usage - actually just N*4 bytes -<br>
&gt; then I suggest that you do keep the list of questions - just their<br>
&gt; numbers - in memory. Then you won't need to read and write the disk<br>
&gt; all the time.<br>
&gt; <br>
&gt; Nadav.<br>
&gt; <br>
&gt; P.S. This is of course a variant on the classic shuffling (or random<br>
&gt; permutation) algorithm.  In the shuffling algorithm, you need to draw<br>
&gt; random questions from the list, but after you used a question, you don't<br>
&gt; want to see it again (its probability becomes zero). Instead of keeping<br>
&gt; the used questions on the list (and getting O(N^2) time complexity for<br>
&gt; the whole shuffle operation), the trick is to move them to the end of<br>
&gt; the list, and to remember how many questions we still have (in the<br>
&gt; beginning of the list) to draw from.<br>
-- <br>
Sent from a PC running a top secret test version of Windows 97.<br>
My own blog is at <a href="http://www.zak.co.il/tddpirate/">http://www.zak.co.il/tddpirate/</a><br>
<br>
My opinions, as expressed in this E-mail message, are mine alone.<br>
They do not represent the official policy of any organization with which<br>
I may be affiliated in any way.<br>
WARNING TO SPAMMERS:  at <a href="http://www.zak.co.il/spamwarning.html">http://www.zak.co.il/spamwarning.html</a><br>
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