Request database query results by curve

Question

I have a table of songs and their bits per minute value, and I would like to create playlists that follow the curve as follows:

  ^       . . .
  |     .       .
b |   .           .
p |  .              .
m | .                .
  x-------------------->
    time

I understand that this is probably not possible in a single SQL statement, but I am interested in auditory solutions. At the moment, the best approach that I see is choosing more tracks than necessary and ordering in my application code (python).

Answer 1

BPM SQL. , , , . , BPM . BPM.

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Answer 2

, sql- , :

• sql , (, x - y , z).

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, - ?

  function makePlaylist(array songList,int playListLength,function curve)
    int x=songList[0].length;
    array playList=new array();//empty array
    int max=getHighestBpmFromList(songList);//getHighestBpmFromList implementation not shown here
    song closestMatch;

    while (playList.length<playListLength)
      currentLength=song.length
      optimalBPM=-(x-songList[0].length)^2+max;//your curve as described above

      closestMatch=findClosestMatch(optimalBPM);//findClosestMatch would find a song
                                                //in the list whose bpm is as close
                                                //as possible to what the bpm 
                                                //should be at x on the curve
                                                //(maybe binary search, since 
                                                //the list is sorted)
      playList.push(closestMatch);
      x++

    return playList;

Answer 3

My idea is to join a table in which there is one field “Time” (which contains integers 1..MAX, you can build this table on the fly) using the song table, where the corresponding SongID for each “Time” represents a song with bps closest to f (time). f is a function representing a curve. Then you can order the result in time and get a curve.

This method does not concern duplicates, and I do not know whether it is easy to implement it in SQL (I am not an SQL expert).