use std::sync::Arc;
use crate::dsl::Field;
use crate::segment::SegmentReader;
use crate::structures::BlockPostingList;
use crate::{DocId, Score};
use super::{CountFuture, EmptyScorer, GlobalStats, Query, Scorer, ScorerFuture, TermQueryInfo};
#[derive(Clone)]
pub struct TermQuery {
pub field: Field,
pub term: Vec<u8>,
global_stats: Option<Arc<GlobalStats>>,
}
impl std::fmt::Debug for TermQuery {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
f.debug_struct("TermQuery")
.field("field", &self.field)
.field("term", &String::from_utf8_lossy(&self.term))
.field("has_global_stats", &self.global_stats.is_some())
.finish()
}
}
impl TermQuery {
pub fn new(field: Field, term: impl Into<Vec<u8>>) -> Self {
Self {
field,
term: term.into(),
global_stats: None,
}
}
pub fn text(field: Field, text: &str) -> Self {
Self {
field,
term: text.to_lowercase().into_bytes(),
global_stats: None,
}
}
pub fn with_global_stats(field: Field, text: &str, stats: Arc<GlobalStats>) -> Self {
Self {
field,
term: text.to_lowercase().into_bytes(),
global_stats: Some(stats),
}
}
pub fn set_global_stats(&mut self, stats: Arc<GlobalStats>) {
self.global_stats = Some(stats);
}
}
impl Query for TermQuery {
fn scorer<'a>(&self, reader: &'a SegmentReader, _limit: usize) -> ScorerFuture<'a> {
let field = self.field;
let term = self.term.clone();
let global_stats = self.global_stats.clone();
Box::pin(async move {
let postings = reader.get_postings(field, &term).await?;
match postings {
Some(posting_list) => {
let (idf, avg_field_len) = if let Some(ref stats) = global_stats {
let term_str = String::from_utf8_lossy(&term);
let global_idf = stats.text_idf(field, &term_str);
if global_idf > 0.0 {
(global_idf, stats.avg_field_len(field))
} else {
let num_docs = reader.num_docs() as f32;
let doc_freq = posting_list.doc_count() as f32;
let idf = super::bm25_idf(doc_freq, num_docs);
(idf, reader.avg_field_len(field))
}
} else {
let num_docs = reader.num_docs() as f32;
let doc_freq = posting_list.doc_count() as f32;
let idf = super::bm25_idf(doc_freq, num_docs);
(idf, reader.avg_field_len(field))
};
let positions = reader.get_positions(field, &term).await.ok().flatten();
let mut scorer = TermScorer::new(
posting_list,
idf,
avg_field_len,
1.0, );
if let Some(pos) = positions {
scorer = scorer.with_positions(field.0, pos);
}
Ok(Box::new(scorer) as Box<dyn Scorer + 'a>)
}
None => Ok(Box::new(EmptyScorer) as Box<dyn Scorer + 'a>),
}
})
}
fn count_estimate<'a>(&self, reader: &'a SegmentReader) -> CountFuture<'a> {
let field = self.field;
let term = self.term.clone();
Box::pin(async move {
match reader.get_postings(field, &term).await? {
Some(list) => Ok(list.doc_count()),
None => Ok(0),
}
})
}
fn as_term_query_info(&self) -> Option<TermQueryInfo> {
Some(TermQueryInfo {
field: self.field,
term: self.term.clone(),
})
}
}
struct TermScorer {
iterator: crate::structures::BlockPostingIterator<'static>,
idf: f32,
avg_field_len: f32,
field_boost: f32,
field_id: u32,
positions: Option<crate::structures::PositionPostingList>,
}
impl TermScorer {
pub fn new(
posting_list: BlockPostingList,
idf: f32,
avg_field_len: f32,
field_boost: f32,
) -> Self {
Self {
iterator: posting_list.into_iterator(),
idf,
avg_field_len,
field_boost,
field_id: 0,
positions: None,
}
}
pub fn with_positions(
mut self,
field_id: u32,
positions: crate::structures::PositionPostingList,
) -> Self {
self.field_id = field_id;
self.positions = Some(positions);
self
}
}
impl Scorer for TermScorer {
fn doc(&self) -> DocId {
self.iterator.doc()
}
fn score(&self) -> Score {
let tf = self.iterator.term_freq() as f32;
super::bm25f_score(tf, self.idf, tf, self.avg_field_len, self.field_boost)
}
fn advance(&mut self) -> DocId {
self.iterator.advance()
}
fn seek(&mut self, target: DocId) -> DocId {
self.iterator.seek(target)
}
fn size_hint(&self) -> u32 {
0
}
fn matched_positions(&self) -> Option<super::MatchedPositions> {
let positions = self.positions.as_ref()?;
let doc_id = self.iterator.doc();
let pos = positions.get_positions(doc_id)?;
Some(vec![(self.field_id, pos.to_vec())])
}
}