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# -*- Mode: Perl -*- |
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# $Basename: InvertedIndex.pm $ |
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# $Revision: 1.30 $ |
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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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# Last Modified On: Tue May 9 08:33:28 2000 |
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# Language : CPerl |
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# |
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# (C) Copyright 1996-2000, Ulrich Pfeifer |
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# |
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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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use vars qw(%FUNC); |
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my $O = pack('C', 0xff)."o"; # occurances (document ferquency) |
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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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my $M = pack('C', 0xff)."m"; # maxtf (term frequency) |
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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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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 $filter = pop @_; |
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# Oops, we cannot overrule the user's choice. Other filters may kill |
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# stopwords, such as isotr clobbers "isn't" to "isnt". |
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# if ($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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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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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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} |
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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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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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$self->{cdict}->{$O,$word}++; |
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$self->{cache}->{$word} .= pack 'w2', $key, $noc; |
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} else { |
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$self->{cdict}->{$O,$word} = 1; |
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$self->{cache}->{$word} = pack 'w2', $key, $noc; |
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} |
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$self->{cached}++; |
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} |
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# This cache limit should be configurable |
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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 $_ > $maxtf; |
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} |
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$self->{db}->{$M, $key} = $maxtf; |
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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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for my $did (sort { $post->{$b} / $self->{db}->{$M, $b} |
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<=> |
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$post->{$a} / $self->{db}->{$M, $a} |
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} keys %$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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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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my $db; |
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defined $self->{db} or $self->open; |
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$db = $self->{db}; |
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$self->sync; |
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$self->{records}--; |
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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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grep $occ{$_}++, &{$self->{func}}(@_); |
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ulpfr |
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for (keys %occ) {# may reorder posting list |
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my %post = unpack 'w*', $db->{$_}; |
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delete $post{$key}; |
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$db->{$_} = $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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delete $db->{$M, $key}; |
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} |
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sub intervall { |
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my ($self, $first, $last) = @_; |
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my $value = ''; |
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my $word = ''; |
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my @result; |
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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'}) { |
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unless (exists $self->{'ifunc'}) { |
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$self->{'ifunc'} = |
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eval sprintf("sub {grep /./, %s}", _filtergen(@{$self->{intervall}})); |
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} |
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($first) = &{$self->{'ifunc'}}($first) if $first; |
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($last) = &{$self->{'ifunc'}}($last) if $last; |
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} |
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if (defined $first and $first ne '') { # set the cursor to $first |
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$dbh->seq($first, $value, R_CURSOR); |
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} else { |
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$dbh->seq($first, $value, R_FIRST); |
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} |
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# We assume that word do not start with the character \377 |
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# $last = pack 'C', 0xff unless defined $last and $last ne ''; |
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return () if defined $last and $first gt $last; # $first would be after the last word |
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push @result, $first; |
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while (!$dbh->seq($word, $value, R_NEXT)) { |
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# We should limit this to a "resonable" number of words |
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last if (defined $last and $word gt $last) or $word =~ /^($M|$O)/o; |
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push @result, $word; |
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} |
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\@result; # speed |
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} |
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sub prefix { |
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my ($self, $prefix) = @_; |
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my $value = ''; |
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my $word = ''; |
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my @result; |
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return () unless defined $prefix; # Full dictionary requested !! |
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return unless exists $self->{'prefix'}; |
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defined $self->{db} or $self->open; |
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$self->sync; |
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my $dbh = $self->{dbh}; |
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if (ref $self->{'prefix'}) { |
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unless (exists $self->{'pfunc'}) { |
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$self->{'pfunc'} = |
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eval sprintf("sub {grep /./, %s}", _filtergen(@{$self->{prefix}})); |
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} |
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($prefix) = &{$self->{'pfunc'}}($prefix); |
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} |
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if ($dbh->seq($word = $prefix, $value, R_CURSOR)) { |
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return (); |
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} |
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return () if $word !~ /^$prefix/; |
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push @result, $word; |
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while (!$dbh->seq($word, $value, R_NEXT)) { |
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# We should limit this to a "resonable" number of words |
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last if $word !~ /^$prefix/; |
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push @result, $word; |
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} |
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\@result; # speed |
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} |
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ulpfr |
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=head2 search($query) |
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The search method supports a range of search algorithms. It is |
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recommended to tune the index by calling |
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C<$table-E<gt>set(top=E<gt>1)> B<after> bulk inserting the documents |
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into the table. This is a computing intense operation and all inserts |
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and deletes after this optimization are slightly more expensive. Once |
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reorganized, the index is kept sorted automatically until you switch |
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the optimization off by calling C<$table-E<gt>set(top=E<gt>0)>. |
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When searching a tuned index, a query can be processed faster if the |
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caller requests only the topmost documents. This can be done by |
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passing a C<top =E<gt>> I<n> parameter to the search method. |
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For single term queries, the method returns only the I<n> top ranking |
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documents. For multi term queries two optimized algorithms are |
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available. The first algorithm computes the top n documents |
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approximately but very fast, sacrificing a little bit of precision for |
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speed. The second algorithm computes the topmost I<n> documents |
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precisely. This algorithm is slower and should be used only for small |
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values of I<n>. It can be requested by passing the query attribute |
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C<picky =E<gt> 1>. Both algorithms may return more than I<n> hits. |
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While the picky version might not be faster than the brute force |
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version on average for modest size databases it uses less memory and |
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the processing time is almost linear in the number of query terms, not |
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in the size of the lists. |
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=cut |
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ulpfr |
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sub search { |
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my $self = shift; |
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ulpfr |
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my $query = shift; |
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ulpfr |
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defined $self->{db} or $self->open; |
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$self->sync; |
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ulpfr |
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$self->search_raw($query, &{$self->{func}}(@_)); # No call to parse() here |
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ulpfr |
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} |
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sub parse { |
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my $self = shift; |
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defined $self->{db} or $self->open; |
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&{$self->{func}}(@_); |
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} |
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ulpfr |
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sub keys { |
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my $self = shift; |
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defined $self->{db} or $self->open; |
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keys %{$self->{db}}; |
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} |
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ulpfr |
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sub search_prefix { |
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my $self = shift; |
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# print "search_prefix(@_)\n"; |
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defined $self->{db} or $self->open; |
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$self->search_raw(map($self->prefix($_), @_)); |
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} |
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ulpfr |
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sub _complain ($$) { |
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|
|
my ($action, $term) = @_; |
377 |
|
|
|
378 |
|
|
require Carp; |
379 |
|
|
Carp::cluck |
380 |
|
|
(sprintf("WAIT database inconsistency during $action [%s]: ". |
381 |
|
|
"Please rebuild index\n", |
382 |
|
|
$term,)); |
383 |
|
|
} |
384 |
|
|
|
385 |
ulpfr |
10 |
sub search_raw { |
386 |
|
|
my $self = shift; |
387 |
ulpfr |
19 |
my $query = shift; |
388 |
ulpfr |
10 |
my %score; |
389 |
|
|
|
390 |
ulpfr |
19 |
# Top $wanted documents must be correct. Zero means all matching |
391 |
|
|
# documents. |
392 |
|
|
my $wanted = $query->{top}; |
393 |
|
|
my $strict = $query->{picky}; |
394 |
ulpfr |
10 |
|
395 |
ulpfr |
19 |
# Return at least $minacc documents. Zero means all matching |
396 |
|
|
# documents. |
397 |
|
|
# my $minacc = $query->{accus} || $wanted; |
398 |
|
|
|
399 |
|
|
# Open index and flush cache if necessary |
400 |
ulpfr |
10 |
defined $self->{db} or $self->open; |
401 |
|
|
$self->sync; |
402 |
ulpfr |
19 |
|
403 |
|
|
# We keep duplicates |
404 |
|
|
my @terms = |
405 |
|
|
# Sort words by decreasing document frequency |
406 |
|
|
sort { $self->{db}->{$O,$a} <=> $self->{db}->{$O,$b} } |
407 |
|
|
# check which words occur in the index. |
408 |
|
|
grep { $self->{db}->{$O,$_} } @_; |
409 |
|
|
|
410 |
|
|
return () unless @terms; # nothing to search for |
411 |
|
|
|
412 |
|
|
# We special-case one term queries here. If the index was sorted, |
413 |
|
|
# choping off the rest of the list will return the same ranking. |
414 |
|
|
if ($wanted and @terms == 1) { |
415 |
|
|
my $term = shift @terms; |
416 |
|
|
my $idf = log($self->{records}/$self->{db}->{$O,$term}); |
417 |
|
|
my @res; |
418 |
|
|
|
419 |
|
|
if ($self->{reorg}) { # or not $query->{picky} |
420 |
|
|
@res = unpack "w". int(2*$wanted), $self->{db}->{$term}; |
421 |
|
|
} else { |
422 |
|
|
@res = unpack 'w*', $self->{db}->{$term}; |
423 |
|
|
} |
424 |
|
|
|
425 |
|
|
for (my $i=1; $i<@res; $i+=2) { |
426 |
|
|
$res[$i] /= $self->{db}->{$M, $res[$i-1]} / $idf; |
427 |
|
|
} |
428 |
|
|
|
429 |
|
|
return @res |
430 |
|
|
} |
431 |
|
|
|
432 |
|
|
# We separate exhaustive search here to avoid overhead and make the |
433 |
|
|
# code more readable. The block can be removed without changing the |
434 |
|
|
# result. |
435 |
|
|
unless ($wanted) { |
436 |
|
|
for (@terms) { |
437 |
|
|
my $df = $self->{db}->{$O,$_}; |
438 |
|
|
|
439 |
|
|
# The frequency *must* be 1 at least since the posting list is nonempty |
440 |
|
|
_complain('search for term', $_) and $df = 1 if $df < 1; |
441 |
|
|
|
442 |
|
|
# Unpack posting list for current query term $_ |
443 |
ulpfr |
10 |
my %post = unpack 'w*', $self->{db}->{$_}; |
444 |
ulpfr |
19 |
|
445 |
|
|
_complain('search for term', $_) if $self->{db}->{$O,$_} != keys %post; |
446 |
|
|
# This is the inverse document frequency. The log of the inverse |
447 |
|
|
# fraction of documents the term occurs in. |
448 |
|
|
my $idf = log($self->{records}/$df); |
449 |
|
|
for my $did (keys %post) { |
450 |
|
|
if (my $freq = $self->{db}->{$M, $did}) { |
451 |
|
|
$score{$did} += $post{$did} / $freq * $idf; |
452 |
|
|
} |
453 |
ulpfr |
10 |
} |
454 |
|
|
} |
455 |
ulpfr |
19 |
# warn sprintf "Used %d accumulators\n", scalar keys %score; |
456 |
|
|
return %score; |
457 |
ulpfr |
10 |
} |
458 |
ulpfr |
19 |
|
459 |
|
|
# A sloppy but fast algorithm for multiple term queries. |
460 |
|
|
unless ($strict) { |
461 |
|
|
for (@terms) { |
462 |
|
|
# Unpack posting list for current query term $_ |
463 |
|
|
my %post = unpack 'w*', $self->{db}->{$_}; |
464 |
|
|
|
465 |
|
|
# Lookup the number of documents the term occurs in (document frequency) |
466 |
|
|
my $occ = $self->{db}->{$O,$_}; |
467 |
|
|
|
468 |
|
|
_complain('search for term', $_) if $self->{db}->{$O,$_} != keys %post; |
469 |
|
|
# The frequency *must* be 1 at least since the posting list is nonempty |
470 |
|
|
_complain('search for term', $_) and $occ = 1 if $occ < 1; |
471 |
|
|
|
472 |
|
|
# This is the inverse document frequency. The log of the inverse |
473 |
|
|
# fraction of documents the term occurs in. |
474 |
|
|
my $idf = log($self->{records}/$occ); |
475 |
|
|
|
476 |
|
|
# If we have a reasonable number of accumulators, change the |
477 |
|
|
# loop to iterate over the accumulators. This will compromise |
478 |
|
|
# quality for better speed. The algorithm still computes the |
479 |
|
|
# exact weights, but the result is not guaranteed to contain the |
480 |
|
|
# *best* results. The database might contain documents better |
481 |
|
|
# than the worst returned document. |
482 |
|
|
|
483 |
|
|
# We process the lists in order of increasing length. When the |
484 |
|
|
# number of accumulators exceeds $wanted, no new documents are |
485 |
|
|
# added, only the ranking/weighting of the seen documents is |
486 |
|
|
# improved. The resulting ranking list must be pruned, since only |
487 |
|
|
# the top most documents end up near their "optimal" rank. |
488 |
|
|
|
489 |
|
|
if (keys %score < $wanted) { |
490 |
|
|
for my $did (keys %post) { |
491 |
|
|
if (my $freq = $self->{db}->{$M, $did}) { |
492 |
|
|
$score{$did} += $post{$did} / $freq * $idf; |
493 |
|
|
} |
494 |
|
|
} |
495 |
|
|
} else { |
496 |
|
|
for my $did (keys %score) { |
497 |
|
|
next unless exists $post{$did}; |
498 |
|
|
if (my $freq = $self->{db}->{$M, $did}) { |
499 |
|
|
$score{$did} += $post{$did} / $freq * $idf; |
500 |
|
|
} |
501 |
|
|
} |
502 |
|
|
} |
503 |
|
|
} |
504 |
|
|
return %score; |
505 |
|
|
} |
506 |
|
|
my @max; $max[$#terms+1]=0; |
507 |
|
|
my @idf; |
508 |
|
|
|
509 |
|
|
# Preparation loop. This extra loop makes sense only when "reorg" |
510 |
|
|
# and "wanted" are true. But at the time beeing, keeping the code |
511 |
|
|
# for the different search algorithms in one place seems more |
512 |
|
|
# desirable than some minor speedup of the brute force version. We |
513 |
|
|
# do cache $idf though. |
514 |
|
|
|
515 |
|
|
for (my $i = $#terms; $i >=0; $i--) { |
516 |
|
|
local $_ = $terms[$i]; |
517 |
|
|
# Lookup the number of documents the term occurs in (document frequency) |
518 |
|
|
my $df = $self->{db}->{$O,$_}; |
519 |
|
|
|
520 |
|
|
# The frequency *must* be 1 at least since the posting list is nonempty |
521 |
|
|
_complain('search for term', $_) and $df = 1 if $df < 1; |
522 |
|
|
|
523 |
|
|
# This is the inverse document frequency. The log of the inverse |
524 |
|
|
# fraction of documents the term occurs in. |
525 |
|
|
$idf[$i] = log($self->{records}/$df); |
526 |
|
|
|
527 |
|
|
my ($did,$occ); |
528 |
|
|
if ($self->{reorg}) { |
529 |
|
|
($did,$occ) = unpack 'w2', $self->{db}->{$_}; |
530 |
|
|
} else { # Maybe this costs more than it helps |
531 |
|
|
($did,$occ) = unpack 'w2', $self->sort_postings($self->{db}->{$_}); |
532 |
|
|
} |
533 |
|
|
my $freq = $self->{db}->{$M, $did}; |
534 |
|
|
my $max = $occ/$freq*$idf[$i]; |
535 |
|
|
$max[$i] = $max + $max[$i+1]; |
536 |
|
|
} |
537 |
|
|
|
538 |
|
|
# Main loop |
539 |
|
|
for my $i (0 .. $#terms) { |
540 |
|
|
my $term = $terms[$i]; |
541 |
|
|
# Unpack posting list for current query term $term. We loose the |
542 |
|
|
# sorting order because the assignment to a hash. |
543 |
|
|
my %post = unpack 'w*', $self->{db}->{$term}; |
544 |
|
|
|
545 |
|
|
_complain('search for term', $term) |
546 |
|
|
if $self->{db}->{$O,$term} != keys %post; |
547 |
|
|
|
548 |
|
|
my $idf = $idf[$i]; |
549 |
|
|
my $full; # Need to process all postings |
550 |
|
|
my $chop; # Score necessary to enter the ranking list |
551 |
|
|
|
552 |
|
|
if (# We know that wanted is true since we especial cased the |
553 |
|
|
# exhaustive search. |
554 |
|
|
|
555 |
|
|
$wanted and |
556 |
|
|
|
557 |
|
|
# We did sort here if necessary in |
558 |
|
|
# the preparation loop |
559 |
|
|
# $self->{reorg} and |
560 |
|
|
|
561 |
|
|
scalar keys %score > $wanted) { |
562 |
|
|
$chop = (sort { $b <=> $a } values %score)[$wanted]; |
563 |
|
|
$full = $max[$i] > $chop; |
564 |
|
|
} else { |
565 |
|
|
$full = 1; |
566 |
|
|
} |
567 |
|
|
|
568 |
|
|
if ($full) { |
569 |
|
|
# We need to inspect the full list. Either $wanted is not given, |
570 |
|
|
# the index is not sorted, or we don't have enough accumulators |
571 |
|
|
# yet. |
572 |
|
|
if (defined $chop) { |
573 |
|
|
# We might be able to avoid allocating accumulators |
574 |
|
|
for my $did (keys %post) { |
575 |
|
|
if (my $freq = $self->{db}->{$M, $did}) { |
576 |
|
|
my $wgt = $post{$did} / $freq * $idf; |
577 |
|
|
# We add an accumulator if $wgt exeeds $chop |
578 |
|
|
if (exists $score{$did} or $wgt > $chop) { |
579 |
|
|
$score{$did} += $wgt; |
580 |
|
|
} |
581 |
|
|
} |
582 |
|
|
} |
583 |
|
|
} else { |
584 |
|
|
# Allocate acumulators for each seen document. |
585 |
|
|
for my $did (keys %post) { |
586 |
|
|
if (my $freq = $self->{db}->{$M, $did}) { |
587 |
|
|
$score{$did} += $post{$did} / $freq * $idf; |
588 |
|
|
} |
589 |
|
|
} |
590 |
|
|
} |
591 |
|
|
} else { |
592 |
|
|
# Update existing accumulators |
593 |
|
|
for my $did (keys %score) { |
594 |
|
|
next unless exists $post{$did}; |
595 |
|
|
if (my $freq = $self->{db}->{$M, $did}) { |
596 |
|
|
$score{$did} += $post{$did} / $freq * $idf; |
597 |
|
|
} |
598 |
|
|
} |
599 |
|
|
} |
600 |
|
|
} |
601 |
|
|
#warn sprintf "Used %d accumulators\n", scalar keys %score; |
602 |
ulpfr |
10 |
%score; |
603 |
|
|
} |
604 |
|
|
|
605 |
ulpfr |
19 |
sub set { |
606 |
|
|
my ($self, $attr, $value) = @_; |
607 |
|
|
|
608 |
|
|
die "No such indexy attribute: '$attr'" unless $attr eq 'top'; |
609 |
|
|
|
610 |
|
|
return delete $self->{reorg} if $value == 0; |
611 |
|
|
|
612 |
|
|
return if $self->{reorg}; # we are sorted already |
613 |
|
|
return unless $self->{mode} & O_RDWR; |
614 |
|
|
defined $self->{db} or $self->open; |
615 |
|
|
|
616 |
|
|
$self->sync; |
617 |
|
|
while (my($key, $value) = each %{$self->{db}}) { |
618 |
|
|
next if $key =~ /^\377[om]/; |
619 |
|
|
$self->{db}->{$key} = $self->sort_postings($value); |
620 |
|
|
} |
621 |
|
|
$self->{reorg} = 1; |
622 |
|
|
} |
623 |
|
|
|
624 |
ulpfr |
10 |
sub sync { |
625 |
|
|
my $self = shift; |
626 |
|
|
|
627 |
|
|
if ($self->{mode} & O_RDWR) { |
628 |
ulpfr |
19 |
print STDERR "Flushing $self->{cached} postings\n" if $self->{cached}; |
629 |
ulpfr |
10 |
while (my($key, $value) = each %{$self->{cache}}) { |
630 |
ulpfr |
19 |
if ($self->{reorg}) { |
631 |
|
|
$self->{db}->{$key} = $self->sort_postings($self->{db}->{$key} |
632 |
|
|
. $value); |
633 |
|
|
} else { |
634 |
|
|
$self->{db}->{$key} .= $value; |
635 |
|
|
} |
636 |
ulpfr |
10 |
} |
637 |
|
|
while (my($key, $value) = each %{$self->{cdict}}) { |
638 |
|
|
$self->{db}->{$key} = 0 unless $self->{db}->{$key}; |
639 |
|
|
$self->{db}->{$key} += $value; |
640 |
|
|
} |
641 |
ulpfr |
19 |
$self->{cache} = {}; |
642 |
|
|
$self->{cdict} = {}; |
643 |
ulpfr |
10 |
$self->{cached} = 0; |
644 |
|
|
} |
645 |
|
|
} |
646 |
|
|
|
647 |
|
|
sub close { |
648 |
|
|
my $self = shift; |
649 |
|
|
|
650 |
|
|
if ($self->{dbh}) { |
651 |
|
|
$self->sync; |
652 |
|
|
delete $self->{dbh}; |
653 |
|
|
untie %{$self->{db}}; |
654 |
|
|
delete $self->{db}; |
655 |
|
|
delete $self->{func}; |
656 |
|
|
delete $self->{cache}; |
657 |
|
|
delete $self->{cached}; |
658 |
|
|
delete $self->{cdict}; |
659 |
|
|
delete $self->{pfunc} if defined $self->{pfunc}; |
660 |
|
|
delete $self->{ifunc} if defined $self->{ifunc}; |
661 |
|
|
delete $self->{xfunc} if defined $self->{xfunc}; |
662 |
|
|
} |
663 |
|
|
} |
664 |
|
|
|
665 |
|
|
1; |
666 |
|
|
|