bionic (3) Lucy::Docs::Cookbook::CustomQueryParser.3pm.gz
NAME
Lucy::Docs::Cookbook::CustomQueryParser - Sample subclass of QueryParser.
ABSTRACT
Implement a custom search query language using a subclass of Lucy::Search::QueryParser.
The language
At first, our query language will support only simple term queries and phrases delimited by double
quotes. For simplicity's sake, it will not support parenthetical groupings, boolean operators, or
prepended plus/minus. The results for all subqueries will be unioned together -- i.e. joined using an OR
-- which is usually the best approach for small-to-medium-sized document collections.
Later, we'll add support for trailing wildcards.
Single-field parser
Our initial parser implentation will generate queries against a single fixed field, "content", and it
will analyze text using a fixed choice of English PolyAnalyzer. We won't subclass
Lucy::Search::QueryParser just yet.
package FlatQueryParser;
use Lucy::Search::TermQuery;
use Lucy::Search::PhraseQuery;
use Lucy::Search::ORQuery;
use Carp;
sub new {
my $analyzer = Lucy::Analysis::PolyAnalyzer->new(
language => 'en',
);
return bless {
field => 'content',
analyzer => $analyzer,
}, __PACKAGE__;
}
Some private helper subs for creating TermQuery and PhraseQuery objects will help keep the size of our
main parse() subroutine down:
sub _make_term_query {
my ( $self, $term ) = @_;
return Lucy::Search::TermQuery->new(
field => $self->{field},
term => $term,
);
}
sub _make_phrase_query {
my ( $self, $terms ) = @_;
return Lucy::Search::PhraseQuery->new(
field => $self->{field},
terms => $terms,
);
}
Our private _tokenize() method treats double-quote delimited material as a single token and splits on
whitespace everywhere else.
sub _tokenize {
my ( $self, $query_string ) = @_;
my @tokens;
while ( length $query_string ) {
if ( $query_string =~ s/^\s+// ) {
next; # skip whitespace
}
elsif ( $query_string =~ s/^("[^"]*(?:"|$))// ) {
push @tokens, $1; # double-quoted phrase
}
else {
$query_string =~ s/(\S+)//;
push @tokens, $1; # single word
}
}
return \@tokens;
}
The main parsing routine creates an array of tokens by calling _tokenize(), runs the tokens through
through the PolyAnalyzer, creates TermQuery or PhraseQuery objects according to how many tokens emerge
from the PolyAnalyzer's split() method, and adds each of the sub-queries to the primary ORQuery.
sub parse {
my ( $self, $query_string ) = @_;
my $tokens = $self->_tokenize($query_string);
my $analyzer = $self->{analyzer};
my $or_query = Lucy::Search::ORQuery->new;
for my $token (@$tokens) {
if ( $token =~ s/^"// ) {
$token =~ s/"$//;
my $terms = $analyzer->split($token);
my $query = $self->_make_phrase_query($terms);
$or_query->add_child($phrase_query);
}
else {
my $terms = $analyzer->split($token);
if ( @$terms == 1 ) {
my $query = $self->_make_term_query( $terms->[0] );
$or_query->add_child($query);
}
elsif ( @$terms > 1 ) {
my $query = $self->_make_phrase_query($terms);
$or_query->add_child($query);
}
}
}
return $or_query;
}
Multi-field parser
Most often, the end user will want their search query to match not only a single 'content' field, but
also 'title' and so on. To make that happen, we have to turn queries such as this...
foo AND NOT bar
... into the logical equivalent of this:
(title:foo OR content:foo) AND NOT (title:bar OR content:bar)
Rather than continue with our own from-scratch parser class and write the routines to accomplish that
expansion, we're now going to subclass Lucy::Search::QueryParser and take advantage of some of its
existing methods.
Our first parser implementation had the "content" field name and the choice of English PolyAnalyzer hard-
coded for simplicity, but we don't need to do that once we subclass Lucy::Search::QueryParser.
QueryParser's constructor -- which we will inherit, allowing us to eliminate our own constructor --
requires a Schema which conveys field and Analyzer information, so we can just defer to that.
package FlatQueryParser;
use base qw( Lucy::Search::QueryParser );
use Lucy::Search::TermQuery;
use Lucy::Search::PhraseQuery;
use Lucy::Search::ORQuery;
use PrefixQuery;
use Carp;
# Inherit new()
We're also going to jettison our _make_term_query() and _make_phrase_query() helper subs and chop our
parse() subroutine way down. Our revised parse() routine will generate Lucy::Search::LeafQuery objects
instead of TermQueries and PhraseQueries:
sub parse {
my ( $self, $query_string ) = @_;
my $tokens = $self->_tokenize($query_string);
my $or_query = Lucy::Search::ORQuery->new;
for my $token (@$tokens) {
my $leaf_query = Lucy::Search::LeafQuery->new( text => $token );
$or_query->add_child($leaf_query);
}
return $self->expand($or_query);
}
The magic happens in QueryParser's expand() method, which walks the ORQuery object we supply to it
looking for LeafQuery objects, and calls expand_leaf() for each one it finds. expand_leaf() performs
field-specific analysis, decides whether each query should be a TermQuery or a PhraseQuery, and if
multiple fields are required, creates an ORQuery which mults out e.g. "foo" into "(title:foo OR
content:foo)".
Extending the query language
To add support for trailing wildcards to our query language, we need to override expand_leaf() to
accommodate PrefixQuery, while deferring to the parent class implementation on TermQuery and PhraseQuery.
sub expand_leaf {
my ( $self, $leaf_query ) = @_;
my $text = $leaf_query->get_text;
if ( $text =~ /\*$/ ) {
my $or_query = Lucy::Search::ORQuery->new;
for my $field ( @{ $self->get_fields } ) {
my $prefix_query = PrefixQuery->new(
field => $field,
query_string => $text,
);
$or_query->add_child($prefix_query);
}
return $or_query;
}
else {
return $self->SUPER::expand_leaf($leaf_query);
}
}
Ordinarily, those asterisks would have been stripped when running tokens through the PolyAnalyzer --
query strings containing "foo*" would produce TermQueries for the term "foo". Our override intercepts
tokens with trailing asterisks and processes them as PrefixQueries before "SUPER::expand_leaf" can
discard them, so that a search for "foo*" can match "food", "foosball", and so on.
Usage
Insert our custom parser into the search.cgi sample app to get a feel for how it behaves:
my $parser = FlatQueryParser->new( schema => $searcher->get_schema );
my $query = $parser->parse( decode( 'UTF-8', $cgi->param('q') || '' ) );
my $hits = $searcher->hits(
query => $query,
offset => $offset,
num_wanted => $page_size,
);
...