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DBD::SQLite::Cookbook(3) User Contributed Perl Documentation DBD::SQLite::Cookbook(3)

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.

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 ) {
          $sigma += ($x - $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;
  
  my $sum   = 0;
  my $count = 0;
  my %hash;
  
  sub new { bless [], shift; }
  
  sub step {
      my ( $self, $value ) = @_;
  
      # 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 (defined $hash{$value}) {
          $hash{$value}++;
      } else {
          $hash{$value} = 1;
      }
      $sum += $value;
      $count++;
  }
  
  sub finalize {
      my $self = $_[0];
  
      # Variance is NULL unless there is more than one row
      return undef unless $count > 1;
  
      # calculate avg
      my $mu = $sum / $count;
  
      my $sigma = 0;
      foreach my $h (keys %hash) {
          $sigma += (($h - $mu)**2) * $hash{$h};
      }
      $sigma = $sigma / ($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 variance;
  
  my $mu = 0;
  my $count = 0;
  my $S = 0
  
  sub new { bless [], shift; }
  
  sub step {
      my ( $self, $value ) = @_;
      $count++;
      $delta = $value - $mu;
      $mu = $mu + $delta/$count
      $S = $S + $delta*($value - $mu);
  }
  
  sub finalize {
      my $self = $_[0];
      return $S / ($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 seperate CPAN distribution.

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

AUTHOR

Adam Kennedy <adamk@cpan.org>

COPYRIGHT

Copyright 2009 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.

2009-11-23 perl v5.10.1