DBD::SQLite::Cookbook - phpMan

NAME
    DBD::SQLite::Cookbook - The DBD::SQLite Cookbook

DESCRIPTION
    This is the DBD::SQLite cookbook.

    It is intended to provide a place to keep a variety of functions and
    formals for use in callback APIs in DBD::SQLite.

AGGREGATE FUNCTIONS
  Variance
    This is a simple aggregate function which returns a variance. It is
    adapted from an example implementation in pysqlite.

      package variance;

      sub new { bless [], shift; }

      sub step {
          my ( $self, $value ) = @_;

          push @$self, $value;
      }

      sub finalize {
          my $self = $_[0];

          my $n = @$self;

          # Variance is NULL unless there is more than one row
          return undef unless $n || $n == 1;

          my $mu = 0;
          foreach my $v ( @$self ) {
              $mu += $v;
          }
          $mu /= $n;

          my $sigma = 0;
          foreach my $v ( @$self ) {
              $sigma += ($v - $mu)**2;
          }
          $sigma = $sigma / ($n - 1);

          return $sigma;
      }

      # NOTE: If you use an older DBI (< 1.608),
      # use $dbh->func(..., "create_aggregate") instead.
      $dbh->sqlite_create_aggregate( "variance", 1, 'variance' );

    The function can then be used as:

      SELECT group_name, variance(score)
      FROM results
      GROUP BY group_name;

  Variance (Memory Efficient)
    A more efficient variance function, optimized for memory usage at the
    expense of precision:

      package variance2;

      sub new { bless {sum => 0, count=>0, hash=> {} }, shift; }

      sub step {
          my ( $self, $value ) = @_;
          my $hash = $self->{hash};

          # by truncating and hashing, we can comsume many more data points
          $value = int($value); # change depending on need for precision
                                # use sprintf for arbitrary fp precision
          if (exists $hash->{$value}) {
              $hash->{$value}++;
          } else {
              $hash->{$value} = 1;
          }
          $self->{sum} += $value;
          $self->{count}++;
      }

      sub finalize {
          my $self = $_[0];

          # Variance is NULL unless there is more than one row
          return undef unless $self->{count} > 1;

          # calculate avg
          my $mu = $self->{sum} / $self->{count};

          my $sigma = 0;
          while (my ($h, $v) = each %{$self->{hash}}) {
              $sigma += (($h - $mu)**2) * $v;
          }
          $sigma = $sigma / ($self->{count} - 1);

          return $sigma;
      }

    The function can then be used as:

      SELECT group_name, variance2(score)
      FROM results
      GROUP BY group_name;

  Variance (Highly Scalable)
    A third variable implementation, designed for arbitrarily large data
    sets:

      package variance3;

      sub new { bless {mu=>0, count=>0, S=>0}, shift; }

      sub step {
          my ( $self, $value ) = @_;
          $self->{count}++;
          my $delta = $value - $self->{mu};
          $self->{mu} += $delta/$self->{count};
          $self->{S} += $delta*($value - $self->{mu});
      }

      sub finalize {
          my $self = $_[0];
          return $self->{S} / ($self->{count} - 1);
      }

    The function can then be used as:

      SELECT group_name, variance3(score)
      FROM results
      GROUP BY group_name;

SUPPORT
    Bugs should be reported via the CPAN bug tracker at

    <http://rt.cpan.org/NoAuth/ReportBug.html?Queue=DBD-SQLite>

TO DO
    *   Add more and varied cookbook recipes, until we have enough to turn
        them into a separate CPAN distribution.

    *   Create a series of tests scripts that validate the cookbook recipes.

AUTHOR
    Adam Kennedy <adamk AT cpan.org>

COPYRIGHT
    Copyright 2009 - 2012 Adam Kennedy.

    This program is free software; you can redistribute it and/or modify it
    under the same terms as Perl itself.

    The full text of the license can be found in the LICENSE file included
    with this module.