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Simplify the search algorithm

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Kerollmops 2020-08-26 15:16:41 +02:00
parent ba2eb0d7ad
commit 38ddc71b83
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GPG Key ID: 92ADA4E935E71FA4
1 changed files with 27 additions and 35 deletions
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58
src/search.rs
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@ -272,6 +272,7 @@ impl<'a> Search<'a> {
pub fn execute(&self) -> anyhow::Result<SearchResult> {
let rtxn = self.rtxn;
let index = self.index;
let limit = self.limit;
let fst = match index.fst(rtxn)? {
Some(fst) => fst,
@ -292,6 +293,8 @@ impl<'a> Search<'a> {
let (derived_words, union_positions) = Self::fetch_words_positions(rtxn, index, &fst, dfas)?;
let candidates = Self::compute_candidates(rtxn, index, &derived_words)?;
debug!("candidates: {:?}", candidates);
let union_cache = HashMap::new();
let mut non_disjoint_cache = HashMap::new();
@ -342,66 +345,55 @@ impl<'a> Search<'a> {
positions.iter().enumerate().for_each(|(word, pos)| {
union_cache.entry((word, *pos)).or_insert_with(|| {
let words = &&derived_words[word];
Self::union_word_position(rtxn, index, words, *pos).unwrap()
});
});
// Retrieve the unions along with the popularity of it.
let mut to_intersect: Vec<_> = positions.iter()
.enumerate()
.map(|(word, pos)| {
let docids = union_cache.get(&(word, *pos)).unwrap();
(docids.len(), docids)
})
.collect();
let mut to_intersect = Vec::new();
for (word, pos) in positions.into_iter().enumerate() {
let docids = union_cache.get(&(word, pos)).unwrap();
to_intersect.push((docids.len(), docids));
}
// Sort the unions by popularity to help reduce
// the number of documents as soon as possible.
to_intersect.sort_unstable_by_key(|(l, _)| *l);
let intersect_docids: Option<RoaringBitmap> = to_intersect.into_iter()
.fold(None, |acc, (_, union_docids)| {
match acc {
Some(mut left) => {
left.intersect_with(&union_docids);
Some(left)
},
None => Some(union_docids.clone()),
// Intersect all the unions in the inverse popularity order.
let mut intersect_docids = RoaringBitmap::new();
for (i, (_, union_docids)) in to_intersect.into_iter().enumerate() {
if i == 0 {
intersect_docids = union_docids.clone();
} else {
intersect_docids.intersect_with(union_docids);
}
}
});
if let Some(intersect_docids) = intersect_docids {
same_proximity_union.union_with(&intersect_docids);
}
// We found enough documents we can stop here
if documents.iter().map(RoaringBitmap::len).sum::<u64>() + same_proximity_union.len() >= 20 {
break;
}
}
// We achieve to find valid documents ids so we remove them from the candidates list.
candidates.difference_with(&same_proximity_union);
documents.push(same_proximity_union);
// We remove documents we have already been seen in previous
// fetches from this set of documents we just fetched.
for previous_documents in &documents {
same_proximity_union.difference_with(previous_documents);
}
// We remove the double occurences of documents.
for i in 0..documents.len() {
if let Some((docs, others)) = documents[..=i].split_last_mut() {
others.iter().for_each(|other| docs.difference_with(other));
if !same_proximity_union.is_empty() {
documents.push(same_proximity_union);
}
}
documents.retain(|rb| !rb.is_empty());
// We found enough documents we can stop here.
if documents.iter().map(RoaringBitmap::len).sum::<u64>() >= 20 {
if documents.iter().map(RoaringBitmap::len).sum::<u64>() >= limit as u64 {
break;
}
}
let found_words = derived_words.into_iter().flatten().map(|(w, _, _)| w).collect();
let documents_ids = documents.iter().flatten().take(20).collect();
let documents_ids = documents.iter().flatten().take(limit).collect();
Ok(SearchResult { found_words, documents_ids })
}