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https://github.com/meilisearch/meilisearch.git
synced 2024-11-30 09:04:59 +08:00
Fix the minimum proximity len
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parent
1c504471d3
commit
4ca9472e02
@ -10,7 +10,6 @@ use std::time::Instant;
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use anyhow::Context;
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use arc_cache::ArcCache;
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use bstr::ByteSlice as _;
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use cow_utils::CowUtils;
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use csv::StringRecord;
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use flate2::read::GzDecoder;
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use fst::IntoStreamer;
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@ -3,14 +3,14 @@ use std::collections::{HashMap, HashSet};
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use fst::{IntoStreamer, Streamer};
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use levenshtein_automata::DFA;
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use levenshtein_automata::LevenshteinAutomatonBuilder as LevBuilder;
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use log::debug;
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use log::{debug, error};
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use once_cell::sync::Lazy;
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use roaring::bitmap::{IntoIter, RoaringBitmap};
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use near_proximity::near_proximity;
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use crate::query_tokens::{QueryTokens, QueryToken};
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use crate::{Index, DocumentId, Position, Attribute};
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use crate::{Index, DocumentId};
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// Building these factories is not free.
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static LEVDIST0: Lazy<LevBuilder> = Lazy::new(|| LevBuilder::new(0, true));
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@ -118,10 +118,8 @@ impl<'a> Search<'a> {
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/// Returns the set of docids that contains all of the query words.
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fn compute_candidates(
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rtxn: &heed::RoTxn,
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index: &Index,
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derived_words: &[(HashMap<String, (u8, RoaringBitmap)>, RoaringBitmap)],
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) -> anyhow::Result<RoaringBitmap>
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) -> RoaringBitmap
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{
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// we do a union between all the docids of each of the derived words,
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// we got N unions (the number of original query words), we then intersect them.
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@ -135,7 +133,7 @@ impl<'a> Search<'a> {
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}
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}
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Ok(candidates)
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candidates
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}
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fn fecth_keywords(
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@ -153,8 +151,10 @@ impl<'a> Search<'a> {
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for (word, (_distance, docids)) in words {
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if docids.contains(candidate) {
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let positions = index.word_docid_positions.get(rtxn, &(word, candidate))?.unwrap();
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union_positions.union_with(&positions);
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match index.word_docid_positions.get(rtxn, &(word, candidate))? {
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Some(positions) => union_positions.union_with(&positions),
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None => error!("position missing for candidate {} and word {}", candidate, word),
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}
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}
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}
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keywords.push(union_positions.into_iter());
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@ -185,13 +185,13 @@ impl<'a> Search<'a> {
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}
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let derived_words = Self::fetch_words_docids(rtxn, index, &fst, dfas)?;
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let candidates = Self::compute_candidates(rtxn, index, &derived_words)?;
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let candidates = Self::compute_candidates(&derived_words);
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debug!("candidates: {:?}", candidates);
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let mut documents = Vec::new();
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let min_proximity = derived_words.len() as u32;
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let min_proximity = derived_words.len() as u32 - 1;
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let mut number_min_proximity = 0;
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let mut paths = Vec::new();
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