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https://github.com/DBD-SQLite/DBD-SQLite
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168 lines
3.4 KiB
Text
168 lines
3.4 KiB
Text
=head1 NAME
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DBD::SQLite::Cookbook - The DBD::SQLite Cookbook
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=head1 DESCRIPTION
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This is the L<DBD::SQLite> cookbook.
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It is intended to provide a place to keep a variety of functions and
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formals for use in callback APIs in L<DBD::SQLite>.
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=head2 Variance
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This is a simple aggregate function which returns a variance. It is
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adapted from an example implementation in pysqlite.
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package variance;
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sub new { bless [], shift; }
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sub step {
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my ( $self, $value ) = @_;
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push @$self, $value;
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}
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sub finalize {
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my $self = $_[0];
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my $n = @$self;
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# Variance is NULL unless there is more than one row
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return undef unless $n || $n == 1;
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my $mu = 0;
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foreach my $v ( @$self ) {
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$mu += $v;
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}
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$mu /= $n;
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my $sigma = 0;
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foreach my $v ( @$self ) {
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$sigma += ($x - $mu)**2;
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}
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$sigma = $sigma / ($n - 1);
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return $sigma;
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}
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$dbh->func( "variance", 1, 'variance', "create_aggregate" );
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The function can then be used as:
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SELECT group_name, variance(score)
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FROM results
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GROUP BY group_name;
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=head2 Variance (Memory Efficient)
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A more efficient variance function, optimized for memory usage at the
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expense of precision:
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package variance2;
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my $sum = 0;
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my $count = 0;
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my %hash;
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sub new { bless [], shift; }
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sub step {
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my ( $self, $value ) = @_;
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# by truncating and hashing, we can comsume many more data points
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$value = int($value); # change depending on need for precision
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# use sprintf for arbitrary fp precision
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if (defined $hash{$value}) {
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$hash{$value}++;
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} else {
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$hash{$value} = 1;
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}
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$sum += $value;
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$count++;
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}
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sub finalize {
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my $self = $_[0];
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# Variance is NULL unless there is more than one row
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return undef unless $count > 1;
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# calculate avg
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my $mu = $sum / $count;
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my $sigma = 0;
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foreach my $h (keys %hash) {
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$sigma += (($h - $mu)**2) * $hash{$h};
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}
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$sigma = $sigma / ($count - 1);
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return $sigma;
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}
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The function can then be used as:
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SELECT group_name, variance2(score)
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FROM results
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GROUP BY group_name;
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=head2 Variance (Highly Scalable)
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A third variable implementation, designed for arbitrarily large data sets:
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package variance;
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my $mu = 0;
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my $count = 0;
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my $S = 0
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sub new { bless [], shift; }
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sub step {
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my ( $self, $value ) = @_;
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$count++;
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$delta = $value - $mu;
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$mu = $mu + $delta/$count
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$S = $S + $delta*($value - $mu);
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}
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sub finalize {
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my $self = $_[0];
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return $S / ($count - 1);
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}
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The function can then be used as:
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SELECT group_name, variance3(score)
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FROM results
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GROUP BY group_name;
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=head1 SUPPORT
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Bugs should be reported via the CPAN bug tracker at
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L<http://rt.cpan.org/NoAuth/ReportBug.html?Queue=DBD-SQLite>
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=head1 TO DO
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* Add more and varied cookbook recipes, until we have enough to
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turn them into a seperate CPAN distribution.
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* Create a series of tests scripts that validate the cookbook recipies.
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=head1 AUTHOR
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Adam Kennedy E<lt>adamk@cpan.orgE<gt>
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=head1 COPYRIGHT
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Copyright 2009 Adam Kennedy.
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This program is free software; you can redistribute
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it and/or modify it under the same terms as Perl itself.
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The full text of the license can be found in the
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LICENSE file included with this module.
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=cut
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