mirror of
https://github.com/meilisearch/MeiliSearch
synced 2025-07-03 20:07:09 +02:00
Merge remote-tracking branch 'origin/main' into tmp-release-v1.15.1
This commit is contained in:
commit
9bda9a9a64
58 changed files with 2312 additions and 1756 deletions
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@ -1,11 +1,13 @@
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use std::cmp::Ordering;
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use heed::RoTxn;
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use itertools::Itertools;
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use roaring::RoaringBitmap;
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use crate::score_details::{ScoreDetails, ScoreValue, ScoringStrategy};
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use crate::search::new::{distinct_fid, distinct_single_docid};
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use crate::search::SemanticSearch;
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use crate::{MatchingWords, Result, Search, SearchResult};
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use crate::{Index, MatchingWords, Result, Search, SearchResult};
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struct ScoreWithRatioResult {
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matching_words: MatchingWords,
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@ -91,7 +93,10 @@ impl ScoreWithRatioResult {
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keyword_results: Self,
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from: usize,
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length: usize,
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) -> (SearchResult, u32) {
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distinct: Option<&str>,
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index: &Index,
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rtxn: &RoTxn<'_>,
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) -> Result<(SearchResult, u32)> {
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#[derive(Clone, Copy)]
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enum ResultSource {
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Semantic,
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@ -106,8 +111,9 @@ impl ScoreWithRatioResult {
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vector_results.document_scores.len() + keyword_results.document_scores.len(),
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);
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let mut documents_seen = RoaringBitmap::new();
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for ((docid, (main_score, _sub_score)), source) in vector_results
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let distinct_fid = distinct_fid(distinct, index, rtxn)?;
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let mut excluded_documents = RoaringBitmap::new();
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for res in vector_results
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.document_scores
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.into_iter()
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.zip(std::iter::repeat(ResultSource::Semantic))
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@ -121,13 +127,33 @@ impl ScoreWithRatioResult {
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compare_scores(left, right).is_ge()
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},
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)
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// remove documents we already saw
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.filter(|((docid, _), _)| documents_seen.insert(*docid))
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// remove documents we already saw and apply distinct rule
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.filter_map(|item @ ((docid, _), _)| {
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if !excluded_documents.insert(docid) {
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// the document was already added, or is indistinct from an already-added document.
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return None;
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}
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if let Some(distinct_fid) = distinct_fid {
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if let Err(error) = distinct_single_docid(
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index,
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rtxn,
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distinct_fid,
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docid,
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&mut excluded_documents,
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) {
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return Some(Err(error));
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}
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}
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Some(Ok(item))
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})
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// start skipping **after** the filter
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.skip(from)
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// take **after** skipping
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.take(length)
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{
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let ((docid, (main_score, _sub_score)), source) = res?;
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if let ResultSource::Semantic = source {
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semantic_hit_count += 1;
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}
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@ -136,10 +162,24 @@ impl ScoreWithRatioResult {
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document_scores.push(main_score);
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}
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(
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// compute the set of candidates from both sets
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let candidates = vector_results.candidates | keyword_results.candidates;
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let must_remove_redundant_candidates = distinct_fid.is_some();
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let candidates = if must_remove_redundant_candidates {
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// patch-up the candidates to remove the indistinct documents, then add back the actual hits
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let mut candidates = candidates - excluded_documents;
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for docid in &documents_ids {
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candidates.insert(*docid);
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}
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candidates
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} else {
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candidates
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};
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Ok((
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SearchResult {
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matching_words: keyword_results.matching_words,
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candidates: vector_results.candidates | keyword_results.candidates,
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candidates,
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documents_ids,
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document_scores,
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degraded: vector_results.degraded | keyword_results.degraded,
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@ -147,7 +187,7 @@ impl ScoreWithRatioResult {
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| keyword_results.used_negative_operator,
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},
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semantic_hit_count,
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)
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))
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}
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}
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@ -226,8 +266,15 @@ impl Search<'_> {
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let keyword_results = ScoreWithRatioResult::new(keyword_results, 1.0 - semantic_ratio);
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let vector_results = ScoreWithRatioResult::new(vector_results, semantic_ratio);
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let (merge_results, semantic_hit_count) =
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ScoreWithRatioResult::merge(vector_results, keyword_results, self.offset, self.limit);
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let (merge_results, semantic_hit_count) = ScoreWithRatioResult::merge(
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vector_results,
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keyword_results,
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self.offset,
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self.limit,
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search.distinct.as_deref(),
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search.index,
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search.rtxn,
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)?;
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assert!(merge_results.documents_ids.len() <= self.limit);
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Ok((merge_results, Some(semantic_hit_count)))
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}
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@ -4,7 +4,9 @@ use super::logger::SearchLogger;
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use super::ranking_rules::{BoxRankingRule, RankingRuleQueryTrait};
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use super::SearchContext;
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use crate::score_details::{ScoreDetails, ScoringStrategy};
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use crate::search::new::distinct::{apply_distinct_rule, distinct_single_docid, DistinctOutput};
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use crate::search::new::distinct::{
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apply_distinct_rule, distinct_fid, distinct_single_docid, DistinctOutput,
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};
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use crate::{Result, TimeBudget};
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pub struct BucketSortOutput {
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@ -35,16 +37,7 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
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logger.ranking_rules(&ranking_rules);
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logger.initial_universe(universe);
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let distinct_field = match distinct {
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Some(distinct) => Some(distinct),
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None => ctx.index.distinct_field(ctx.txn)?,
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};
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let distinct_fid = if let Some(field) = distinct_field {
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ctx.index.fields_ids_map(ctx.txn)?.id(field)
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} else {
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None
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};
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let distinct_fid = distinct_fid(distinct, ctx.index, ctx.txn)?;
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if universe.len() < from as u64 {
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return Ok(BucketSortOutput {
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@ -9,7 +9,7 @@ use crate::heed_codec::facet::{
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FacetGroupKey, FacetGroupKeyCodec, FacetGroupValueCodec, FieldDocIdFacetCodec,
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};
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use crate::heed_codec::BytesRefCodec;
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use crate::{Index, Result, SearchContext};
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use crate::{FieldId, Index, Result, SearchContext};
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pub struct DistinctOutput {
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pub remaining: RoaringBitmap,
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@ -121,3 +121,18 @@ pub fn facet_string_values<'a>(
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fn facet_values_prefix_key(distinct: u16, id: u32) -> [u8; FID_SIZE + DOCID_SIZE] {
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concat_arrays::concat_arrays!(distinct.to_be_bytes(), id.to_be_bytes())
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}
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pub fn distinct_fid(
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query_distinct_field: Option<&str>,
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index: &Index,
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rtxn: &RoTxn<'_>,
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) -> Result<Option<FieldId>> {
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let distinct_field = match query_distinct_field {
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Some(distinct) => Some(distinct),
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None => index.distinct_field(rtxn)?,
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};
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let distinct_fid =
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if let Some(field) = distinct_field { index.fields_ids_map(rtxn)?.id(field) } else { None };
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Ok(distinct_fid)
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}
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@ -28,6 +28,7 @@ use std::time::Duration;
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use bucket_sort::{bucket_sort, BucketSortOutput};
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use charabia::{Language, TokenizerBuilder};
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use db_cache::DatabaseCache;
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pub use distinct::{distinct_fid, distinct_single_docid};
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use exact_attribute::ExactAttribute;
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use graph_based_ranking_rule::{Exactness, Fid, Position, Proximity, Typo};
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use heed::RoTxn;
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@ -51,6 +52,7 @@ pub use self::geo_sort::{Parameter as GeoSortParameter, Strategy as GeoSortStrat
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use self::graph_based_ranking_rule::Words;
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use self::interner::Interned;
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use self::vector_sort::VectorSort;
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use crate::attribute_patterns::{match_pattern, PatternMatch};
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use crate::constants::RESERVED_GEO_FIELD_NAME;
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use crate::index::PrefixSearch;
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use crate::localized_attributes_rules::LocalizedFieldIds;
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@ -119,17 +121,37 @@ impl<'ctx> SearchContext<'ctx> {
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let searchable_fields_weights = self.index.searchable_fields_and_weights(self.txn)?;
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let exact_attributes_ids = self.index.exact_attributes_ids(self.txn)?;
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let mut wildcard = false;
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let mut universal_wildcard = false;
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let mut restricted_fids = RestrictedFids::default();
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for field_name in attributes_to_search_on {
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if field_name == "*" {
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wildcard = true;
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universal_wildcard = true;
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// we cannot early exit as we want to returns error in case of unknown fields
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continue;
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}
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let searchable_weight =
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searchable_fields_weights.iter().find(|(name, _, _)| name == field_name);
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// The field is not searchable but may contain a wildcard pattern
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if searchable_weight.is_none() && field_name.contains("*") {
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let matching_searchable_weights: Vec<_> = searchable_fields_weights
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.iter()
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.filter(|(name, _, _)| match_pattern(field_name, name) == PatternMatch::Match)
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.collect();
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if !matching_searchable_weights.is_empty() {
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for (_name, fid, weight) in matching_searchable_weights {
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if exact_attributes_ids.contains(fid) {
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restricted_fids.exact.push((*fid, *weight));
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} else {
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restricted_fids.tolerant.push((*fid, *weight));
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}
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}
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continue;
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}
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}
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let (fid, weight) = match searchable_weight {
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// The Field id exist and the field is searchable
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Some((_name, fid, weight)) => (*fid, *weight),
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@ -159,7 +181,7 @@ impl<'ctx> SearchContext<'ctx> {
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};
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}
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if wildcard {
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if universal_wildcard {
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self.restricted_fids = None;
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} else {
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self.restricted_fids = Some(restricted_fids);
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@ -72,7 +72,7 @@ fn test_2gram_simple() {
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let index = create_index();
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index
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.update_settings(|s| {
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s.set_autorize_typos(false);
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s.set_authorize_typos(false);
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})
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.unwrap();
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@ -103,7 +103,7 @@ fn test_3gram_simple() {
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let index = create_index();
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index
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.update_settings(|s| {
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s.set_autorize_typos(false);
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s.set_authorize_typos(false);
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})
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.unwrap();
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@ -153,7 +153,7 @@ fn test_no_disable_ngrams() {
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let index = create_index();
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index
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.update_settings(|s| {
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s.set_autorize_typos(false);
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s.set_authorize_typos(false);
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})
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.unwrap();
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@ -179,7 +179,7 @@ fn test_2gram_prefix() {
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let index = create_index();
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index
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.update_settings(|s| {
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s.set_autorize_typos(false);
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s.set_authorize_typos(false);
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})
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.unwrap();
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@ -208,7 +208,7 @@ fn test_3gram_prefix() {
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let index = create_index();
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index
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.update_settings(|s| {
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s.set_autorize_typos(false);
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s.set_authorize_typos(false);
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})
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.unwrap();
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@ -260,7 +260,7 @@ fn test_disable_split_words() {
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let index = create_index();
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index
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.update_settings(|s| {
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s.set_autorize_typos(false);
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s.set_authorize_typos(false);
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})
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.unwrap();
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@ -151,7 +151,7 @@ fn test_no_typo() {
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let index = create_index();
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index
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.update_settings(|s| {
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s.set_autorize_typos(false);
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s.set_authorize_typos(false);
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})
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.unwrap();
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