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Current Path : /proc/thread-self/root/lib64/perl5/vendor_perl/DBD/SQLite/ |
Current File : //proc/thread-self/root/lib64/perl5/vendor_perl/DBD/SQLite/Cookbook.pod |
=head1 NAME DBD::SQLite::Cookbook - The DBD::SQLite Cookbook =head1 DESCRIPTION This is the L<DBD::SQLite> cookbook. It is intended to provide a place to keep a variety of functions and formals for use in callback APIs in L<DBD::SQLite>. =head1 AGGREGATE FUNCTIONS =head2 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; =head2 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; =head2 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; =head1 SUPPORT Bugs should be reported via the CPAN bug tracker at L<http://rt.cpan.org/NoAuth/ReportBug.html?Queue=DBD-SQLite> =head1 TO DO =over =item * Add more and varied cookbook recipes, until we have enough to turn them into a separate CPAN distribution. =item * Create a series of tests scripts that validate the cookbook recipes. =back =head1 AUTHOR Adam Kennedy E<lt>adamk@cpan.orgE<gt> =head1 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.