Allow iterating over sorted (by relevance) Terms
Knowing the ordered sequence of most relevant terms is very useful and `limit` is unlikely to be a number which makes the `into_sorted_vec` step prohibitive, so this patch simply makes Keywords hold a sorted Vec instead of a BinaryHeap.
- Id
- c03c72ee3f35401b4977db66137c00d4290152be
- Author
- Caio
- Commit time
- 2020-02-19T11:19:25+01:00
Modified tique/src/topterms.rs
let searcher = self.reader.searcher();
let num_docs = searcher.num_docs();
- let mut keywords = Keywords::new(limit);
+ let mut keywords = DescendingTopK::new(limit);
for (field, tokenizer) in self.field_tokenizers.iter() {
let termfreq = termfreq(&input, *field, tokenizer);
}
}
- keywords
+ keywords.into()
}
/// Same as `extract_from_doc`, but with support inspect/filter the
let searcher = self.reader.searcher();
let num_docs = searcher.num_docs();
- let mut keywords = Keywords::new(limit);
+ let mut keywords = DescendingTopK::new(limit);
for (field, _tokenizer) in self.field_tokenizers.iter() {
termfreq_for_doc(&searcher, *field, addr, |term, term_freq| {
});
}
- keywords
+ keywords.into()
}
}
/// Keywords is a collection of Term objects found via TopTerms
-pub struct Keywords(DescendingTopK<f32, Term>);
+pub struct Keywords(Vec<(Term, f32)>);
impl Keywords {
/// Convert into a Query. It can be used as a way to approximate a
/// nearest neighbors search, so it's expected that results are
/// similar to the source used to create this Keywords instance.
pub fn into_query(self) -> BooleanQuery {
- BooleanQuery::new_multiterms_query(
- self.0
- .into_vec()
- .into_iter()
- .map(|(term, _score)| term)
- .collect(),
- )
+ BooleanQuery::new_multiterms_query(self.0.into_iter().map(|(term, _score)| term).collect())
+ }
+
+ /// Iterates over the terms of this keywords set, more relevant
+ /// terms appear first
+ pub fn terms(&self) -> impl Iterator<Item = &Term> {
+ self.0.iter().map(|(term, _score)| term)
}
/// Exposes the ordered terms and their scores. Useful if you are
/// using the keywords for other purposes, like reporting, feeding
/// into a more complex query, etc.
pub fn into_sorted_vec(self) -> Vec<(Term, f32)> {
- self.0.into_sorted_vec()
+ self.0
}
// TODO into_boosted_query, using the scaled tf/idf scores scaled with
+}
- fn new(limit: usize) -> Self {
- Self(DescendingTopK::new(limit))
- }
-
- fn visit(&mut self, term: Term, score: f32) {
- self.0.visit(term, score);
+impl From<DescendingTopK<f32, Term>> for Keywords {
+ fn from(src: DescendingTopK<f32, Term>) -> Self {
+ Self(src.into_sorted_vec())
}
}