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ulpfr |
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# -*- Mode: Perl -*- |
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# $Basename: InvertedIndex.pm $ |
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# $Revision: 1.30 $ |
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ulpfr |
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# Author : Ulrich Pfeifer |
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# Created On : Thu Aug 8 13:05:10 1996 |
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# Last Modified By: Ulrich Pfeifer |
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ulpfr |
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# Last Modified On: Sun Nov 12 14:40:21 2000 |
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ulpfr |
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# Language : CPerl |
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ulpfr |
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# |
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# (C) Copyright 1996-2000, Ulrich Pfeifer |
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# |
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ulpfr |
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package WAIT::InvertedIndex; |
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use strict; |
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use DB_File; |
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use Fcntl; |
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use WAIT::Filter; |
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use Carp; |
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laperla |
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use vars qw(%FUNC $VERSION); |
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ulpfr |
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|
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laperla |
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$VERSION = "1.801"; # others test if we are loaded by checking $VERSION |
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ulpfr |
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# The dictionary has three different key types: |
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# 'o'.$word |
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# |
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# The document frequency is the number of documents a term occurs |
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# in. The idea is that a term occuring in a significant part of the |
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# documents is not too significant. |
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# |
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# 'm'.$word |
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# |
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# The maximum term frequency of a document is the frequency of the |
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# most frequent term in the document. It is related to the document |
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# length obviously. A document in which the most frequnet term occurs |
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# 100 times is probably much longer than a document whichs most |
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# frequent term occurs five time. |
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# |
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# 'p'.$word |
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# |
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# Under this key we store the actual posting list as pairs of |
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# packed integers. |
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ulpfr |
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|
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ulpfr |
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my $no_old_index_support = 0; # do not check for old indices if set |
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ulpfr |
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|
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ulpfr |
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sub new { |
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my $type = shift; |
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my %parm = @_; |
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my $self = {}; |
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$self->{file} = $parm{file} or croak "No file specified"; |
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$self->{attr} = $parm{attr} or croak "No attributes specified"; |
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$self->{filter} = $parm{filter}; |
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$self->{'name'} = $parm{'name'}; |
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$self->{records} = 0; |
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for (qw(intervall prefix)) { |
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if (exists $parm{$_}) { |
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if (ref $parm{$_}) { |
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$self->{$_} = [@{$parm{$_}}] # clone |
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} else { |
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$self->{$_} = $parm{$_} |
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} |
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} |
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} |
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bless $self, ref($type) || $type; |
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} |
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sub name {$_[0]->{'name'}} |
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sub _split_pos { |
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my ($text, $pos) = @{$_[0]}; |
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my @result; |
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$text =~ s/(^\s+)// and $pos += length($1); |
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while ($text =~ s/(^\S+)//) { |
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my $word = $1; |
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push @result, [$word, $pos]; |
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$pos += length($word); |
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$text =~ s/(^\s+)// and $pos += length($1); |
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} |
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@result; |
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} |
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sub _xfiltergen { |
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my $filter = pop @_; |
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ulpfr |
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# Oops, we cannot overrule the user's choice. Other filters may kill |
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# stopwords, such as isotr clobbers "isn't" to "isnt". |
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# if ($filter eq 'stop') { # avoid the slow stopword elimination |
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# return _xfiltergen(@_); # it's cheaper to look them up afterwards |
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# } |
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ulpfr |
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if (@_) { |
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if ($filter =~ /^split(\d*)/) { |
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if ($1) { |
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"grep(length(\$_->[0])>=$1, map(&WAIT::Filter::split_pos(\$_), " . _xfiltergen(@_) .'))' ; |
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} else { |
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"map(&WAIT::Filter::split_pos(\$_), " . _xfiltergen(@_) .')' ; |
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} |
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} else { |
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"map ([&WAIT::Filter::$filter(\$_->[0]), \$_->[1]]," ._xfiltergen(@_) .')'; |
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} |
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} else { |
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if ($filter =~ /^split(\d*)/) { |
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if ($1) { |
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"grep(length(\$_->[0])>=$1, map(&WAIT::Filter::split_pos(\$_), [\$_[0], 0]))" ; |
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} else { |
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"map(&WAIT::Filter::split_pos(\$_), [\$_[0], 0])" ; |
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} |
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} else { |
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"map ([&WAIT::Filter::$filter(\$_->[0]), \$_->[1]], [\$_[0], 0])"; |
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} |
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} |
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} |
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sub parse_pos { |
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my $self = shift; |
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unless (exists $self->{xfunc}) { |
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$self->{xfunc} = |
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eval sprintf("sub {%s}", _xfiltergen(@{$self->{filter}})); |
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#printf "\nsub{%s}$@\n", _xfiltergen(@{$self->{filter}}); |
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} |
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&{$self->{xfunc}}($_[0]); |
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} |
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sub _filtergen { |
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my $filter = pop @_; |
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if (@_) { |
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"map(&WAIT::Filter::$filter(\$_), " . _filtergen(@_) . ')'; |
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} else { |
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"map(&WAIT::Filter::$filter(\$_), \@_)"; |
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} |
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} |
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sub drop { |
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my $self = shift; |
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if ((caller)[0] eq 'WAIT::Table') { # Table knows about this |
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my $file = $self->{file}; |
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! (!-e $file or unlink $file); |
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} else { # notify our database |
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croak ref($self)."::drop called directly"; |
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} |
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} |
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ulpfr |
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sub is_an_old_index { |
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my $self = shift; |
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return 0 if $no_old_index_support; |
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return $self->{old_index} if exists $self->{old_index}; |
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# We can only guess if this is an old index. We lookup the first 10 |
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# $O entries. If all values are integers, we assume that the index |
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# is an old one. |
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defined $self->{db} or $self->open; |
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$self->sync; |
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my $dbh = $self->{dbh}; # for convenience |
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my $O = pack('C', 0xff)."o"; |
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laperla |
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my ($word, $value) = ($O.$;); # $word and $value are modified by seq! |
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if ( my $ret = $dbh->seq($word, $value, R_CURSOR) ) { |
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# warn "DEBUG: ret[$ret], not an old index, either empty or no \$^O"; |
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return $self->{old_index} = 0; |
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} |
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ulpfr |
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for (my $i=0; $i<10;$i++) { |
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if ($value !~ /^\d+$/) { |
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laperla |
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# warn "DEBUG: word[$word]value[$value], not an old index"; |
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ulpfr |
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return $self->{old_index} = 0; |
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} |
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laperla |
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if (my $ret = $dbh->seq($word, $value, R_NEXT) or # no values left |
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ulpfr |
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$word !~ /^$O$;/o # no $O values left |
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ulpfr |
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) { |
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# we are not sure enough that this is an old index |
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laperla |
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# warn "DEBUG: ret[$ret]word[$word]value[$value], not an old index"; |
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ulpfr |
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return $self->{old_index} = 0; |
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} |
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} |
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laperla |
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# warn "DEBUG: old index"; |
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ulpfr |
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return $self->{old_index} = 1; |
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} |
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ulpfr |
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sub open { |
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my $self = shift; |
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my $file = $self->{file}; |
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if (defined $self->{dbh}) { |
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$self->{dbh}; |
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} else { |
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$self->{func} = |
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eval sprintf("sub {grep /./, %s}", _filtergen(@{$self->{filter}})); |
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$self->{dbh} = tie(%{$self->{db}}, 'DB_File', $file, |
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$self->{mode}, 0664, $DB_BTREE); |
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$self->{cache} = {} |
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if $self->{mode} & O_RDWR; |
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$self->{cdict} = {} |
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if $self->{mode} & O_RDWR; |
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$self->{cached} = 0; |
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ulpfr |
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if (!$no_old_index_support and $self->is_an_old_index()) { |
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warn "This is an old index, upgrade you database"; |
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require WAIT::InvertedIndexOld; |
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bless $self, 'WAIT::InvertedIndexOld'; |
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} |
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ulpfr |
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} |
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} |
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sub insert { |
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my $self = shift; |
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my $key = shift; |
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my %occ; |
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ulpfr |
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ulpfr |
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defined $self->{db} or $self->open; |
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grep $occ{$_}++, &{$self->{func}}(@_); |
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my ($word, $noc); |
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$self->{records}++; |
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while (($word, $noc) = each %occ) { |
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if (defined $self->{cache}->{$word}) { |
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ulpfr |
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$self->{cdict}->{$word}++; |
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ulpfr |
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$self->{cache}->{$word} .= pack 'w2', $key, $noc; |
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ulpfr |
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} else { |
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$self->{cdict}->{$word} = 1; |
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ulpfr |
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$self->{cache}->{$word} = pack 'w2', $key, $noc; |
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ulpfr |
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} |
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ulpfr |
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$self->{cached}++; |
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} |
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ulpfr |
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# This cache limit should be configurable |
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ulpfr |
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$self->sync if $self->{cached} > 100_000; |
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my $maxtf = 0; |
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for (values %occ) { |
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$maxtf = $_ if $_ > $maxtf; |
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} |
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ulpfr |
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$self->{db}->{'m'. $key} = $maxtf; |
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ulpfr |
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} |
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ulpfr |
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# We sort postings by increasing max term frequency (~ by increasing |
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# document length. This reduces the quality degradation if we process |
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# only the first part of a posting list. |
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sub sort_postings { |
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my $self = shift; |
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my $post = shift; # reference to a hash or packed string |
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if (ref $post) { |
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# we skip the sort part, if the index is not sorted |
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return pack('w*', %$post) unless $self->{reorg}; |
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} else { |
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$post = { unpack 'w*', $post }; |
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} |
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my $r = ''; |
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# Sort posting list by increasing ratio of maximum term frequency (~ |
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# "document length") and term frequency. This rati multipied by the |
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# inverse document frequence gives the score for a term. This sort |
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# order can be exploited for tuning of single term queries. |
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laperla |
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for my $did (keys %$post) { # sanity check |
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unless ($self->{db}->{"m". $did}) { |
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warn "Warning from WAIT: DIVZERO threat from did[$did] post[$post->{$did}]"; |
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$self->{db}->{"m". $did} = 1; # fails if we have not opened for writing |
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} |
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} |
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ulpfr |
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for my $did (sort { $post->{$b} / $self->{db}->{'m'. $b} |
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ulpfr |
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<=> |
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ulpfr |
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$post->{$a} / $self->{db}->{'m'. $a} |
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ulpfr |
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} keys %$post) { |
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$r .= pack 'w2', $did, $post->{$did}; |
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} |
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#warn sprintf "reorg %d %s\n", scalar keys %$post, join ' ', unpack 'w*', $r; |
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$r; |
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} |
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ulpfr |
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sub delete { |
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my $self = shift; |
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my $key = shift; |
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my %occ; |
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ulpfr |
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my $db; |
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ulpfr |
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defined $self->{db} or $self->open; |
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ulpfr |
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$db = $self->{db}; |
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ulpfr |
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$self->sync; |
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$self->{records}--; |
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ulpfr |
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|
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# less than zero documents in database? |
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_complain('delete of document', $key) and $self->{records} = 0 |
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if $self->{records} < 0; |
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ulpfr |
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grep $occ{$_}++, &{$self->{func}}(@_); |
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ulpfr |
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|
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laperla |
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# Be prepared for "Odd number of elements in hash assignment" |
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local $SIG{__WARN__} = sub { |
293 |
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my $warning = shift; |
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chomp $warning; |
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warn "Catching warning[$warning] during delete of key[$key]"; |
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}; |
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ulpfr |
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for (keys %occ) {# may reorder posting list |
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ulpfr |
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my %post = unpack 'w*', $db->{'p'.$_}; |
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ulpfr |
10 |
delete $post{$key}; |
300 |
ulpfr |
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$db->{'p'.$_} = $self->sort_postings(\%post); |
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_complain('delete of term', $_) if $db->{'o'.$_}-1 != keys %post; |
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$db->{'o'.$_} = scalar keys %post; |
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ulpfr |
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} |
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ulpfr |
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delete $db->{'m'. $key}; |
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ulpfr |
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} |
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307 |
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sub intervall { |
308 |
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my ($self, $first, $last) = @_; |
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my $value = ''; |
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my $word = ''; |
311 |
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my @result; |
312 |
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313 |
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return unless exists $self->{'intervall'}; |
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defined $self->{db} or $self->open; |
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$self->sync; |
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my $dbh = $self->{dbh}; # for convenience |
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if (ref $self->{'intervall'}) { |
320 |
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unless (exists $self->{'ifunc'}) { |
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$self->{'ifunc'} = |
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eval sprintf("sub {grep /./, %s}", _filtergen(@{$self->{intervall}})); |
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} |
324 |
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($first) = &{$self->{'ifunc'}}($first) if $first; |
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($last) = &{$self->{'ifunc'}}($last) if $last; |
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} |
327 |
ulpfr |
22 |
$first = 'p'.($first||''); |
328 |
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$last = (defined $last)?'p'.$last:'q'; |
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# set the cursor to $first |
331 |
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$dbh->seq($first, $value, R_CURSOR); |
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333 |
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# $first would be after the last word |
334 |
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return () if $first gt $last; |
335 |
ulpfr |
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|
336 |
ulpfr |
22 |
push @result, substr($first,1); |
337 |
ulpfr |
10 |
while (!$dbh->seq($word, $value, R_NEXT)) { |
338 |
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# We should limit this to a "resonable" number of words |
339 |
ulpfr |
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last if $word gt $last; |
340 |
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push @result, substr($word,1); |
341 |
ulpfr |
10 |
} |
342 |
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\@result; # speed |
343 |
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} |
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345 |
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sub prefix { |
346 |
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my ($self, $prefix) = @_; |
347 |
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my $value = ''; |
348 |
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my $word = ''; |
349 |
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my @result; |
350 |
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351 |
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return () unless defined $prefix; # Full dictionary requested !! |
352 |
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return unless exists $self->{'prefix'}; |
353 |
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defined $self->{db} or $self->open; |
354 |
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$self->sync; |
355 |
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my $dbh = $self->{dbh}; |
356 |
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357 |
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if (ref $self->{'prefix'}) { |
358 |
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unless (exists $self->{'pfunc'}) { |
359 |
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$self->{'pfunc'} = |
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eval sprintf("sub {grep /./, %s}", _filtergen(@{$self->{prefix}})); |
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} |
362 |
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($prefix) = &{$self->{'pfunc'}}($prefix); |
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} |
364 |
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|
365 |
ulpfr |
22 |
if ($dbh->seq($word = 'p'.$prefix, $value, R_CURSOR)) { |
366 |
ulpfr |
10 |
return (); |
367 |
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} |
368 |
ulpfr |
22 |
return () if $word !~ /^p$prefix/; |
369 |
|
|
push @result, substr($word,1); |
370 |
ulpfr |
10 |
|
371 |
|
|
while (!$dbh->seq($word, $value, R_NEXT)) { |
372 |
|
|
# We should limit this to a "resonable" number of words |
373 |
ulpfr |
22 |
last if $word !~ /^p$prefix/; |
374 |
|
|
push @result, substr($word,1); |
375 |
ulpfr |
10 |
} |
376 |
|
|
\@result; # speed |
377 |
|
|
} |
378 |
|
|
|
379 |
ulpfr |
19 |
=head2 search($query) |
380 |
|
|
|
381 |
|
|
The search method supports a range of search algorithms. It is |
382 |
|
|
recommended to tune the index by calling |
383 |
|
|
C<$table-E<gt>set(top=E<gt>1)> B<after> bulk inserting the documents |
384 |
|
|
into the table. This is a computing intense operation and all inserts |
385 |
|
|
and deletes after this optimization are slightly more expensive. Once |
386 |
|
|
reorganized, the index is kept sorted automatically until you switch |
387 |
|
|
the optimization off by calling C<$table-E<gt>set(top=E<gt>0)>. |
388 |
|
|
|
389 |
|
|
When searching a tuned index, a query can be processed faster if the |
390 |
|
|
caller requests only the topmost documents. This can be done by |
391 |
|
|
passing a C<top =E<gt>> I<n> parameter to the search method. |
392 |
|
|
|
393 |
|
|
For single term queries, the method returns only the I<n> top ranking |
394 |
|
|
documents. For multi term queries two optimized algorithms are |
395 |
|
|
available. The first algorithm computes the top n documents |
396 |
|
|
approximately but very fast, sacrificing a little bit of precision for |
397 |
|
|
speed. The second algorithm computes the topmost I<n> documents |
398 |
|
|
precisely. This algorithm is slower and should be used only for small |
399 |
|
|
values of I<n>. It can be requested by passing the query attribute |
400 |
|
|
C<picky =E<gt> 1>. Both algorithms may return more than I<n> hits. |
401 |
|
|
While the picky version might not be faster than the brute force |
402 |
|
|
version on average for modest size databases it uses less memory and |
403 |
|
|
the processing time is almost linear in the number of query terms, not |
404 |
|
|
in the size of the lists. |
405 |
|
|
|
406 |
|
|
=cut |
407 |
|
|
|
408 |
ulpfr |
10 |
sub search { |
409 |
|
|
my $self = shift; |
410 |
ulpfr |
19 |
my $query = shift; |
411 |
ulpfr |
10 |
|
412 |
|
|
defined $self->{db} or $self->open; |
413 |
|
|
$self->sync; |
414 |
ulpfr |
19 |
$self->search_raw($query, &{$self->{func}}(@_)); # No call to parse() here |
415 |
ulpfr |
10 |
} |
416 |
|
|
|
417 |
|
|
sub parse { |
418 |
|
|
my $self = shift; |
419 |
|
|
|
420 |
|
|
defined $self->{db} or $self->open; |
421 |
|
|
&{$self->{func}}(@_); |
422 |
|
|
} |
423 |
|
|
|
424 |
ulpfr |
13 |
sub keys { |
425 |
|
|
my $self = shift; |
426 |
|
|
|
427 |
|
|
defined $self->{db} or $self->open; |
428 |
|
|
keys %{$self->{db}}; |
429 |
|
|
} |
430 |
|
|
|
431 |
ulpfr |
10 |
sub search_prefix { |
432 |
|
|
my $self = shift; |
433 |
|
|
|
434 |
|
|
# print "search_prefix(@_)\n"; |
435 |
|
|
defined $self->{db} or $self->open; |
436 |
|
|
$self->search_raw(map($self->prefix($_), @_)); |
437 |
|
|
} |
438 |
|
|
|
439 |
ulpfr |
19 |
sub _complain ($$) { |
440 |
|
|
my ($action, $term) = @_; |
441 |
|
|
|
442 |
|
|
require Carp; |
443 |
|
|
Carp::cluck |
444 |
|
|
(sprintf("WAIT database inconsistency during $action [%s]: ". |
445 |
|
|
"Please rebuild index\n", |
446 |
|
|
$term,)); |
447 |
|
|
} |
448 |
|
|
|
449 |
ulpfr |
10 |
sub search_raw { |
450 |
|
|
my $self = shift; |
451 |
ulpfr |
19 |
my $query = shift; |
452 |
ulpfr |
10 |
my %score; |
453 |
|
|
|
454 |
ulpfr |
19 |
# Top $wanted documents must be correct. Zero means all matching |
455 |
|
|
# documents. |
456 |
|
|
my $wanted = $query->{top}; |
457 |
|
|
my $strict = $query->{picky}; |
458 |
ulpfr |
10 |
|
459 |
ulpfr |
19 |
# Return at least $minacc documents. Zero means all matching |
460 |
|
|
# documents. |
461 |
|
|
# my $minacc = $query->{accus} || $wanted; |
462 |
|
|
|
463 |
|
|
# Open index and flush cache if necessary |
464 |
ulpfr |
10 |
defined $self->{db} or $self->open; |
465 |
|
|
$self->sync; |
466 |
ulpfr |
19 |
|
467 |
|
|
# We keep duplicates |
468 |
|
|
my @terms = |
469 |
|
|
# Sort words by decreasing document frequency |
470 |
ulpfr |
22 |
sort { $self->{db}->{'o'.$a} <=> $self->{db}->{'o'.$b} } |
471 |
ulpfr |
19 |
# check which words occur in the index. |
472 |
ulpfr |
22 |
grep { $self->{db}->{'o'.$_} } @_; |
473 |
ulpfr |
19 |
|
474 |
laperla |
40 |
return unless @terms; |
475 |
ulpfr |
19 |
|
476 |
|
|
# We special-case one term queries here. If the index was sorted, |
477 |
|
|
# choping off the rest of the list will return the same ranking. |
478 |
|
|
if ($wanted and @terms == 1) { |
479 |
|
|
my $term = shift @terms; |
480 |
ulpfr |
22 |
my $idf = log($self->{records}/$self->{db}->{'o'.$term}); |
481 |
ulpfr |
19 |
my @res; |
482 |
|
|
|
483 |
|
|
if ($self->{reorg}) { # or not $query->{picky} |
484 |
ulpfr |
22 |
@res = unpack "w". int(2*$wanted), $self->{db}->{'p'.$term}; |
485 |
ulpfr |
19 |
} else { |
486 |
ulpfr |
22 |
@res = unpack 'w*', $self->{db}->{'p'.$term}; |
487 |
ulpfr |
19 |
} |
488 |
|
|
|
489 |
|
|
for (my $i=1; $i<@res; $i+=2) { |
490 |
laperla |
30 |
# $res[$i] /= $self->{db}->{'m'. $res[$i-1]} / $idf; |
491 |
|
|
# above was written badly, allows two DIV_ZERO problems. |
492 |
|
|
my $maxtf = $self->{db}->{"m". $res[$i-1]}; |
493 |
|
|
unless ($maxtf) { |
494 |
|
|
warn "WAIT-Warning: Averting DIVZERO for i[$i] \$res[\$i-1][$res[$i-1]] term[$term]"; |
495 |
|
|
$maxtf = 1; |
496 |
|
|
} |
497 |
|
|
$res[$i] = ($res[$i] / $maxtf) * $idf; |
498 |
ulpfr |
19 |
} |
499 |
|
|
|
500 |
|
|
return @res |
501 |
|
|
} |
502 |
|
|
|
503 |
|
|
# We separate exhaustive search here to avoid overhead and make the |
504 |
|
|
# code more readable. The block can be removed without changing the |
505 |
|
|
# result. |
506 |
|
|
unless ($wanted) { |
507 |
|
|
for (@terms) { |
508 |
ulpfr |
22 |
my $df = $self->{db}->{'o'.$_}; |
509 |
ulpfr |
19 |
|
510 |
|
|
# The frequency *must* be 1 at least since the posting list is nonempty |
511 |
|
|
_complain('search for term', $_) and $df = 1 if $df < 1; |
512 |
|
|
|
513 |
|
|
# Unpack posting list for current query term $_ |
514 |
ulpfr |
22 |
my %post = unpack 'w*', $self->{db}->{'p'.$_}; |
515 |
ulpfr |
19 |
|
516 |
ulpfr |
22 |
_complain('search for term', $_) if $self->{db}->{'o'.$_} != keys %post; |
517 |
ulpfr |
19 |
# This is the inverse document frequency. The log of the inverse |
518 |
|
|
# fraction of documents the term occurs in. |
519 |
|
|
my $idf = log($self->{records}/$df); |
520 |
|
|
for my $did (keys %post) { |
521 |
ulpfr |
22 |
if (my $freq = $self->{db}->{'m'. $did}) { |
522 |
ulpfr |
19 |
$score{$did} += $post{$did} / $freq * $idf; |
523 |
|
|
} |
524 |
ulpfr |
10 |
} |
525 |
|
|
} |
526 |
ulpfr |
19 |
# warn sprintf "Used %d accumulators\n", scalar keys %score; |
527 |
|
|
return %score; |
528 |
ulpfr |
10 |
} |
529 |
ulpfr |
19 |
|
530 |
|
|
# A sloppy but fast algorithm for multiple term queries. |
531 |
|
|
unless ($strict) { |
532 |
|
|
for (@terms) { |
533 |
|
|
# Unpack posting list for current query term $_ |
534 |
ulpfr |
22 |
my %post = unpack 'w*', $self->{db}->{'p'.$_}; |
535 |
ulpfr |
19 |
|
536 |
|
|
# Lookup the number of documents the term occurs in (document frequency) |
537 |
ulpfr |
22 |
my $occ = $self->{db}->{'o'.$_}; |
538 |
ulpfr |
19 |
|
539 |
ulpfr |
22 |
_complain('search for term', $_) if $self->{db}->{'o'.$_} != keys %post; |
540 |
ulpfr |
19 |
# The frequency *must* be 1 at least since the posting list is nonempty |
541 |
|
|
_complain('search for term', $_) and $occ = 1 if $occ < 1; |
542 |
|
|
|
543 |
|
|
# This is the inverse document frequency. The log of the inverse |
544 |
|
|
# fraction of documents the term occurs in. |
545 |
|
|
my $idf = log($self->{records}/$occ); |
546 |
|
|
|
547 |
|
|
# If we have a reasonable number of accumulators, change the |
548 |
|
|
# loop to iterate over the accumulators. This will compromise |
549 |
|
|
# quality for better speed. The algorithm still computes the |
550 |
|
|
# exact weights, but the result is not guaranteed to contain the |
551 |
|
|
# *best* results. The database might contain documents better |
552 |
|
|
# than the worst returned document. |
553 |
|
|
|
554 |
|
|
# We process the lists in order of increasing length. When the |
555 |
|
|
# number of accumulators exceeds $wanted, no new documents are |
556 |
|
|
# added, only the ranking/weighting of the seen documents is |
557 |
|
|
# improved. The resulting ranking list must be pruned, since only |
558 |
|
|
# the top most documents end up near their "optimal" rank. |
559 |
|
|
|
560 |
|
|
if (keys %score < $wanted) { |
561 |
|
|
for my $did (keys %post) { |
562 |
ulpfr |
22 |
if (my $freq = $self->{db}->{'m'. $did}) { |
563 |
ulpfr |
19 |
$score{$did} += $post{$did} / $freq * $idf; |
564 |
|
|
} |
565 |
|
|
} |
566 |
|
|
} else { |
567 |
|
|
for my $did (keys %score) { |
568 |
|
|
next unless exists $post{$did}; |
569 |
ulpfr |
22 |
if (my $freq = $self->{db}->{'m'. $did}) { |
570 |
ulpfr |
19 |
$score{$did} += $post{$did} / $freq * $idf; |
571 |
|
|
} |
572 |
|
|
} |
573 |
|
|
} |
574 |
|
|
} |
575 |
|
|
return %score; |
576 |
|
|
} |
577 |
|
|
my @max; $max[$#terms+1]=0; |
578 |
|
|
my @idf; |
579 |
|
|
|
580 |
|
|
# Preparation loop. This extra loop makes sense only when "reorg" |
581 |
|
|
# and "wanted" are true. But at the time beeing, keeping the code |
582 |
|
|
# for the different search algorithms in one place seems more |
583 |
|
|
# desirable than some minor speedup of the brute force version. We |
584 |
|
|
# do cache $idf though. |
585 |
|
|
|
586 |
|
|
for (my $i = $#terms; $i >=0; $i--) { |
587 |
|
|
local $_ = $terms[$i]; |
588 |
|
|
# Lookup the number of documents the term occurs in (document frequency) |
589 |
ulpfr |
22 |
my $df = $self->{db}->{'o'.$_}; |
590 |
ulpfr |
19 |
|
591 |
|
|
# The frequency *must* be 1 at least since the posting list is nonempty |
592 |
|
|
_complain('search for term', $_) and $df = 1 if $df < 1; |
593 |
|
|
|
594 |
|
|
# This is the inverse document frequency. The log of the inverse |
595 |
|
|
# fraction of documents the term occurs in. |
596 |
|
|
$idf[$i] = log($self->{records}/$df); |
597 |
|
|
|
598 |
|
|
my ($did,$occ); |
599 |
|
|
if ($self->{reorg}) { |
600 |
ulpfr |
22 |
($did,$occ) = unpack 'w2', $self->{db}->{'p'.$_}; |
601 |
ulpfr |
19 |
} else { # Maybe this costs more than it helps |
602 |
ulpfr |
22 |
($did,$occ) = unpack 'w2', $self->sort_postings($self->{db}->{'p'.$_}); |
603 |
ulpfr |
19 |
} |
604 |
ulpfr |
22 |
my $freq = $self->{db}->{'m'. $did}; |
605 |
ulpfr |
19 |
my $max = $occ/$freq*$idf[$i]; |
606 |
|
|
$max[$i] = $max + $max[$i+1]; |
607 |
|
|
} |
608 |
|
|
|
609 |
|
|
# Main loop |
610 |
|
|
for my $i (0 .. $#terms) { |
611 |
|
|
my $term = $terms[$i]; |
612 |
|
|
# Unpack posting list for current query term $term. We loose the |
613 |
|
|
# sorting order because the assignment to a hash. |
614 |
ulpfr |
22 |
my %post = unpack 'w*', $self->{db}->{'p'.$term}; |
615 |
ulpfr |
19 |
|
616 |
|
|
_complain('search for term', $term) |
617 |
ulpfr |
22 |
if $self->{db}->{'o'.$term} != keys %post; |
618 |
ulpfr |
19 |
|
619 |
|
|
my $idf = $idf[$i]; |
620 |
|
|
my $full; # Need to process all postings |
621 |
|
|
my $chop; # Score necessary to enter the ranking list |
622 |
|
|
|
623 |
|
|
if (# We know that wanted is true since we especial cased the |
624 |
|
|
# exhaustive search. |
625 |
|
|
|
626 |
|
|
$wanted and |
627 |
|
|
|
628 |
|
|
# We did sort here if necessary in |
629 |
|
|
# the preparation loop |
630 |
|
|
# $self->{reorg} and |
631 |
|
|
|
632 |
|
|
scalar keys %score > $wanted) { |
633 |
|
|
$chop = (sort { $b <=> $a } values %score)[$wanted]; |
634 |
|
|
$full = $max[$i] > $chop; |
635 |
|
|
} else { |
636 |
|
|
$full = 1; |
637 |
|
|
} |
638 |
|
|
|
639 |
|
|
if ($full) { |
640 |
|
|
# We need to inspect the full list. Either $wanted is not given, |
641 |
|
|
# the index is not sorted, or we don't have enough accumulators |
642 |
|
|
# yet. |
643 |
|
|
if (defined $chop) { |
644 |
|
|
# We might be able to avoid allocating accumulators |
645 |
|
|
for my $did (keys %post) { |
646 |
ulpfr |
22 |
if (my $freq = $self->{db}->{'m'. $did}) { |
647 |
ulpfr |
19 |
my $wgt = $post{$did} / $freq * $idf; |
648 |
|
|
# We add an accumulator if $wgt exeeds $chop |
649 |
|
|
if (exists $score{$did} or $wgt > $chop) { |
650 |
|
|
$score{$did} += $wgt; |
651 |
|
|
} |
652 |
|
|
} |
653 |
|
|
} |
654 |
|
|
} else { |
655 |
|
|
# Allocate acumulators for each seen document. |
656 |
|
|
for my $did (keys %post) { |
657 |
ulpfr |
22 |
if (my $freq = $self->{db}->{'m'. $did}) { |
658 |
ulpfr |
19 |
$score{$did} += $post{$did} / $freq * $idf; |
659 |
|
|
} |
660 |
|
|
} |
661 |
|
|
} |
662 |
|
|
} else { |
663 |
|
|
# Update existing accumulators |
664 |
|
|
for my $did (keys %score) { |
665 |
|
|
next unless exists $post{$did}; |
666 |
ulpfr |
22 |
if (my $freq = $self->{db}->{'m'. $did}) { |
667 |
ulpfr |
19 |
$score{$did} += $post{$did} / $freq * $idf; |
668 |
|
|
} |
669 |
|
|
} |
670 |
|
|
} |
671 |
|
|
} |
672 |
|
|
#warn sprintf "Used %d accumulators\n", scalar keys %score; |
673 |
ulpfr |
10 |
%score; |
674 |
|
|
} |
675 |
|
|
|
676 |
ulpfr |
19 |
sub set { |
677 |
|
|
my ($self, $attr, $value) = @_; |
678 |
|
|
|
679 |
|
|
die "No such indexy attribute: '$attr'" unless $attr eq 'top'; |
680 |
|
|
|
681 |
|
|
return delete $self->{reorg} if $value == 0; |
682 |
|
|
|
683 |
|
|
return if $self->{reorg}; # we are sorted already |
684 |
|
|
return unless $self->{mode} & O_RDWR; |
685 |
|
|
defined $self->{db} or $self->open; |
686 |
|
|
|
687 |
|
|
$self->sync; |
688 |
|
|
while (my($key, $value) = each %{$self->{db}}) { |
689 |
ulpfr |
22 |
next if $key !~ /^p/; |
690 |
ulpfr |
19 |
$self->{db}->{$key} = $self->sort_postings($value); |
691 |
|
|
} |
692 |
|
|
$self->{reorg} = 1; |
693 |
|
|
} |
694 |
|
|
|
695 |
ulpfr |
10 |
sub sync { |
696 |
|
|
my $self = shift; |
697 |
|
|
|
698 |
|
|
if ($self->{mode} & O_RDWR) { |
699 |
ulpfr |
19 |
print STDERR "Flushing $self->{cached} postings\n" if $self->{cached}; |
700 |
ulpfr |
10 |
while (my($key, $value) = each %{$self->{cache}}) { |
701 |
laperla |
30 |
$self->{db}->{"p". $key} ||= ""; |
702 |
ulpfr |
19 |
if ($self->{reorg}) { |
703 |
ulpfr |
22 |
$self->{db}->{'p'.$key} = $self->sort_postings($self->{db}->{'p'.$key} |
704 |
ulpfr |
19 |
. $value); |
705 |
|
|
} else { |
706 |
ulpfr |
22 |
$self->{db}->{'p'.$key} .= $value; |
707 |
ulpfr |
19 |
} |
708 |
ulpfr |
10 |
} |
709 |
|
|
while (my($key, $value) = each %{$self->{cdict}}) { |
710 |
ulpfr |
22 |
$self->{db}->{'o'.$key} = 0 unless $self->{db}->{'o'.$key}; |
711 |
|
|
$self->{db}->{'o'.$key} += $value; |
712 |
ulpfr |
10 |
} |
713 |
ulpfr |
19 |
$self->{cache} = {}; |
714 |
|
|
$self->{cdict} = {}; |
715 |
ulpfr |
10 |
$self->{cached} = 0; |
716 |
|
|
} |
717 |
|
|
} |
718 |
|
|
|
719 |
|
|
sub close { |
720 |
|
|
my $self = shift; |
721 |
|
|
|
722 |
|
|
if ($self->{dbh}) { |
723 |
|
|
$self->sync; |
724 |
|
|
delete $self->{dbh}; |
725 |
|
|
untie %{$self->{db}}; |
726 |
|
|
delete $self->{db}; |
727 |
|
|
delete $self->{func}; |
728 |
|
|
delete $self->{cache}; |
729 |
|
|
delete $self->{cached}; |
730 |
|
|
delete $self->{cdict}; |
731 |
|
|
delete $self->{pfunc} if defined $self->{pfunc}; |
732 |
|
|
delete $self->{ifunc} if defined $self->{ifunc}; |
733 |
|
|
delete $self->{xfunc} if defined $self->{xfunc}; |
734 |
|
|
} |
735 |
|
|
} |
736 |
|
|
|
737 |
|
|
1; |
738 |
|
|
|