table of contents
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.
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
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@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.
2016-04-21 | perl v5.30.1 |