mod bucket_sort; mod db_cache; mod distinct; mod geo_sort; mod graph_based_ranking_rule; mod interner; mod limits; mod logger; pub mod matches; mod query_graph; mod query_term; mod ranking_rule_graph; mod ranking_rules; mod resolve_query_graph; mod small_bitmap; mod exact_attribute; mod sort; #[cfg(test)] mod tests; use std::collections::{BTreeSet, HashSet}; use bucket_sort::{bucket_sort, BucketSortOutput}; use charabia::TokenizerBuilder; use db_cache::DatabaseCache; use exact_attribute::ExactAttribute; use graph_based_ranking_rule::{Exactness, Fid, Position, Proximity, Typo}; use heed::RoTxn; use hnsw::Searcher; use interner::{DedupInterner, Interner}; pub use logger::visual::VisualSearchLogger; pub use logger::{DefaultSearchLogger, SearchLogger}; use query_graph::{QueryGraph, QueryNode}; use query_term::{located_query_terms_from_tokens, LocatedQueryTerm, Phrase, QueryTerm}; use ranking_rules::{ BoxRankingRule, PlaceholderQuery, RankingRule, RankingRuleOutput, RankingRuleQueryTrait, }; use resolve_query_graph::{compute_query_graph_docids, PhraseDocIdsCache}; use roaring::RoaringBitmap; use sort::Sort; use space::Neighbor; use self::geo_sort::GeoSort; pub use self::geo_sort::Strategy as GeoSortStrategy; use self::graph_based_ranking_rule::Words; use self::interner::Interned; use crate::error::FieldIdMapMissingEntry; use crate::score_details::{ScoreDetails, ScoringStrategy}; use crate::search::new::distinct::apply_distinct_rule; use crate::{ normalize_vector, AscDesc, DocumentId, Filter, Index, Member, Result, TermsMatchingStrategy, UserError, BEU32, }; /// A structure used throughout the execution of a search query. pub struct SearchContext<'ctx> { pub index: &'ctx Index, pub txn: &'ctx RoTxn<'ctx>, pub db_cache: DatabaseCache<'ctx>, pub word_interner: DedupInterner, pub phrase_interner: DedupInterner, pub term_interner: Interner, pub phrase_docids: PhraseDocIdsCache, pub restricted_fids: Option>, } impl<'ctx> SearchContext<'ctx> { pub fn new(index: &'ctx Index, txn: &'ctx RoTxn<'ctx>) -> Self { Self { index, txn, db_cache: <_>::default(), word_interner: <_>::default(), phrase_interner: <_>::default(), term_interner: <_>::default(), phrase_docids: <_>::default(), restricted_fids: None, } } pub fn searchable_attributes(&mut self, searchable_attributes: &'ctx [String]) -> Result<()> { let fids_map = self.index.fields_ids_map(self.txn)?; let searchable_names = self.index.searchable_fields(self.txn)?; let mut restricted_fids = Vec::new(); for field_name in searchable_attributes { let searchable_contains_name = searchable_names.as_ref().map(|sn| sn.iter().any(|name| name == field_name)); let fid = match (fids_map.id(field_name), searchable_contains_name) { // The Field id exist and the field is searchable (Some(fid), Some(true)) | (Some(fid), None) => fid, // The field is searchable but the Field id doesn't exist => Internal Error (None, Some(true)) => { return Err(FieldIdMapMissingEntry::FieldName { field_name: field_name.to_string(), process: "search", } .into()) } // The field is not searchable => User error _otherwise => { let mut valid_fields: BTreeSet<_> = fids_map.names().map(String::from).collect(); // Filter by the searchable names if let Some(sn) = searchable_names { let searchable_names = sn.iter().map(|s| s.to_string()).collect(); valid_fields = &valid_fields & &searchable_names; } let searchable_count = valid_fields.len(); // Remove hidden fields if let Some(dn) = self.index.displayed_fields(self.txn)? { let displayable_names = dn.iter().map(|s| s.to_string()).collect(); valid_fields = &valid_fields & &displayable_names; } let hidden_fields = searchable_count > valid_fields.len(); let field = field_name.to_string(); return Err(UserError::InvalidSearchableAttribute { field, valid_fields, hidden_fields, } .into()); } }; restricted_fids.push(fid); } self.restricted_fids = Some(restricted_fids); Ok(()) } } #[derive(Clone, Copy, PartialEq, PartialOrd, Ord, Eq)] pub enum Word { Original(Interned), Derived(Interned), } impl Word { pub fn interned(&self) -> Interned { match self { Word::Original(word) => *word, Word::Derived(word) => *word, } } } /// Apply the [`TermsMatchingStrategy`] to the query graph and resolve it. fn resolve_maximally_reduced_query_graph( ctx: &mut SearchContext, universe: &RoaringBitmap, query_graph: &QueryGraph, matching_strategy: TermsMatchingStrategy, logger: &mut dyn SearchLogger, ) -> Result { let mut graph = query_graph.clone(); let nodes_to_remove = match matching_strategy { TermsMatchingStrategy::Last => query_graph .removal_order_for_terms_matching_strategy_last(ctx) .iter() .flat_map(|x| x.iter()) .collect(), TermsMatchingStrategy::All => vec![], }; graph.remove_nodes_keep_edges(&nodes_to_remove); logger.query_for_initial_universe(&graph); let docids = compute_query_graph_docids(ctx, &graph, universe)?; Ok(docids) } fn resolve_universe( ctx: &mut SearchContext, initial_universe: &RoaringBitmap, query_graph: &QueryGraph, matching_strategy: TermsMatchingStrategy, logger: &mut dyn SearchLogger, ) -> Result { resolve_maximally_reduced_query_graph( ctx, initial_universe, query_graph, matching_strategy, logger, ) } /// Return the list of initialised ranking rules to be used for a placeholder search. fn get_ranking_rules_for_placeholder_search<'ctx>( ctx: &SearchContext<'ctx>, sort_criteria: &Option>, geo_strategy: geo_sort::Strategy, ) -> Result>> { let mut sort = false; let mut sorted_fields = HashSet::new(); let mut geo_sorted = false; let mut ranking_rules: Vec> = vec![]; let settings_ranking_rules = ctx.index.criteria(ctx.txn)?; for rr in settings_ranking_rules { match rr { // These rules need a query to have an effect; ignore them in placeholder search crate::Criterion::Words | crate::Criterion::Typo | crate::Criterion::Attribute | crate::Criterion::Proximity | crate::Criterion::Exactness => continue, crate::Criterion::Sort => { if sort { continue; } resolve_sort_criteria( sort_criteria, ctx, &mut ranking_rules, &mut sorted_fields, &mut geo_sorted, geo_strategy, )?; sort = true; } crate::Criterion::Asc(field_name) => { if sorted_fields.contains(&field_name) { continue; } sorted_fields.insert(field_name.clone()); ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, true)?)); } crate::Criterion::Desc(field_name) => { if sorted_fields.contains(&field_name) { continue; } sorted_fields.insert(field_name.clone()); ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, false)?)); } } } Ok(ranking_rules) } /// Return the list of initialised ranking rules to be used for a query graph search. fn get_ranking_rules_for_query_graph_search<'ctx>( ctx: &SearchContext<'ctx>, sort_criteria: &Option>, geo_strategy: geo_sort::Strategy, terms_matching_strategy: TermsMatchingStrategy, ) -> Result>> { // query graph search let mut words = false; let mut typo = false; let mut proximity = false; let mut sort = false; let mut attribute = false; let mut exactness = false; let mut sorted_fields = HashSet::new(); let mut geo_sorted = false; // Don't add the `words` ranking rule if the term matching strategy is `All` if matches!(terms_matching_strategy, TermsMatchingStrategy::All) { words = true; } let mut ranking_rules: Vec> = vec![]; let settings_ranking_rules = ctx.index.criteria(ctx.txn)?; for rr in settings_ranking_rules { // Add Words before any of: typo, proximity, attribute match rr { crate::Criterion::Typo | crate::Criterion::Attribute | crate::Criterion::Proximity | crate::Criterion::Exactness => { if !words { ranking_rules.push(Box::new(Words::new(terms_matching_strategy))); words = true; } } _ => {} } match rr { crate::Criterion::Words => { if words { continue; } ranking_rules.push(Box::new(Words::new(terms_matching_strategy))); words = true; } crate::Criterion::Typo => { if typo { continue; } typo = true; ranking_rules.push(Box::new(Typo::new(None))); } crate::Criterion::Proximity => { if proximity { continue; } proximity = true; ranking_rules.push(Box::new(Proximity::new(None))); } crate::Criterion::Attribute => { if attribute { continue; } attribute = true; ranking_rules.push(Box::new(Fid::new(None))); ranking_rules.push(Box::new(Position::new(None))); } crate::Criterion::Sort => { if sort { continue; } resolve_sort_criteria( sort_criteria, ctx, &mut ranking_rules, &mut sorted_fields, &mut geo_sorted, geo_strategy, )?; sort = true; } crate::Criterion::Exactness => { if exactness { continue; } ranking_rules.push(Box::new(ExactAttribute::new())); ranking_rules.push(Box::new(Exactness::new())); exactness = true; } crate::Criterion::Asc(field_name) => { if sorted_fields.contains(&field_name) { continue; } sorted_fields.insert(field_name.clone()); ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, true)?)); } crate::Criterion::Desc(field_name) => { if sorted_fields.contains(&field_name) { continue; } sorted_fields.insert(field_name.clone()); ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, false)?)); } } } Ok(ranking_rules) } fn resolve_sort_criteria<'ctx, Query: RankingRuleQueryTrait>( sort_criteria: &Option>, ctx: &SearchContext<'ctx>, ranking_rules: &mut Vec>, sorted_fields: &mut HashSet, geo_sorted: &mut bool, geo_strategy: geo_sort::Strategy, ) -> Result<()> { let sort_criteria = sort_criteria.clone().unwrap_or_default(); ranking_rules.reserve(sort_criteria.len()); for criterion in sort_criteria { match criterion { AscDesc::Asc(Member::Field(field_name)) => { if sorted_fields.contains(&field_name) { continue; } sorted_fields.insert(field_name.clone()); ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, true)?)); } AscDesc::Desc(Member::Field(field_name)) => { if sorted_fields.contains(&field_name) { continue; } sorted_fields.insert(field_name.clone()); ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, false)?)); } AscDesc::Asc(Member::Geo(point)) => { if *geo_sorted { continue; } let geo_faceted_docids = ctx.index.geo_faceted_documents_ids(ctx.txn)?; ranking_rules.push(Box::new(GeoSort::new( geo_strategy, geo_faceted_docids, point, true, )?)); } AscDesc::Desc(Member::Geo(point)) => { if *geo_sorted { continue; } let geo_faceted_docids = ctx.index.geo_faceted_documents_ids(ctx.txn)?; ranking_rules.push(Box::new(GeoSort::new( geo_strategy, geo_faceted_docids, point, false, )?)); } }; } Ok(()) } #[allow(clippy::too_many_arguments)] pub fn execute_search( ctx: &mut SearchContext, query: &Option, vector: &Option>, terms_matching_strategy: TermsMatchingStrategy, scoring_strategy: ScoringStrategy, exhaustive_number_hits: bool, filters: &Option, sort_criteria: &Option>, geo_strategy: geo_sort::Strategy, from: usize, length: usize, words_limit: Option, placeholder_search_logger: &mut dyn SearchLogger, query_graph_logger: &mut dyn SearchLogger, ) -> Result { let mut universe = if let Some(filters) = filters { filters.evaluate(ctx.txn, ctx.index)? } else { ctx.index.documents_ids(ctx.txn)? }; check_sort_criteria(ctx, sort_criteria.as_ref())?; if let Some(vector) = vector { let mut searcher = Searcher::new(); let hnsw = ctx.index.vector_hnsw(ctx.txn)?.unwrap_or_default(); let ef = hnsw.len().min(100); let mut dest = vec![Neighbor { index: 0, distance: 0 }; ef]; let vector = normalize_vector(vector.clone()); let neighbors = hnsw.nearest(&vector, ef, &mut searcher, &mut dest[..]); let mut docids = Vec::new(); let mut uniq_docids = RoaringBitmap::new(); for Neighbor { index, distance: _ } in neighbors.iter() { let index = BEU32::new(*index as u32); let docid = ctx.index.vector_id_docid.get(ctx.txn, &index)?.unwrap().get(); if universe.contains(docid) && uniq_docids.insert(docid) { docids.push(docid); if docids.len() == (from + length) { break; } } } // return the nearest documents that are also part of the candidates // along with a dummy list of scores that are useless in this context. let docids: Vec<_> = docids.into_iter().skip(from).take(length).collect(); return Ok(PartialSearchResult { candidates: universe, document_scores: vec![Vec::new(); docids.len()], documents_ids: docids, located_query_terms: None, }); } let mut located_query_terms = None; let query_terms = if let Some(query) = query { // We make sure that the analyzer is aware of the stop words // this ensures that the query builder is able to properly remove them. let mut tokbuilder = TokenizerBuilder::new(); let stop_words = ctx.index.stop_words(ctx.txn)?; if let Some(ref stop_words) = stop_words { tokbuilder.stop_words(stop_words); } let script_lang_map = ctx.index.script_language(ctx.txn)?; if !script_lang_map.is_empty() { tokbuilder.allow_list(&script_lang_map); } let tokenizer = tokbuilder.build(); let tokens = tokenizer.tokenize(query); let query_terms = located_query_terms_from_tokens(ctx, tokens, words_limit)?; if query_terms.is_empty() { // Do a placeholder search instead None } else { Some(query_terms) } } else { None }; let bucket_sort_output = if let Some(query_terms) = query_terms { let (graph, new_located_query_terms) = QueryGraph::from_query(ctx, &query_terms)?; located_query_terms = Some(new_located_query_terms); let ranking_rules = get_ranking_rules_for_query_graph_search( ctx, sort_criteria, geo_strategy, terms_matching_strategy, )?; universe = resolve_universe(ctx, &universe, &graph, terms_matching_strategy, query_graph_logger)?; bucket_sort( ctx, ranking_rules, &graph, &universe, from, length, scoring_strategy, query_graph_logger, )? } else { let ranking_rules = get_ranking_rules_for_placeholder_search(ctx, sort_criteria, geo_strategy)?; bucket_sort( ctx, ranking_rules, &PlaceholderQuery, &universe, from, length, scoring_strategy, placeholder_search_logger, )? }; let BucketSortOutput { docids, scores, mut all_candidates } = bucket_sort_output; let fields_ids_map = ctx.index.fields_ids_map(ctx.txn)?; // The candidates is the universe unless the exhaustive number of hits // is requested and a distinct attribute is set. if exhaustive_number_hits { if let Some(f) = ctx.index.distinct_field(ctx.txn)? { if let Some(distinct_fid) = fields_ids_map.id(f) { all_candidates = apply_distinct_rule(ctx, distinct_fid, &all_candidates)?.remaining; } } } Ok(PartialSearchResult { candidates: all_candidates, document_scores: scores, documents_ids: docids, located_query_terms, }) } fn check_sort_criteria(ctx: &SearchContext, sort_criteria: Option<&Vec>) -> Result<()> { let sort_criteria = if let Some(sort_criteria) = sort_criteria { sort_criteria } else { return Ok(()); }; if sort_criteria.is_empty() { return Ok(()); } // We check that the sort ranking rule exists and throw an // error if we try to use it and that it doesn't. let sort_ranking_rule_missing = !ctx.index.criteria(ctx.txn)?.contains(&crate::Criterion::Sort); if sort_ranking_rule_missing { return Err(UserError::SortRankingRuleMissing.into()); } // We check that we are allowed to use the sort criteria, we check // that they are declared in the sortable fields. let sortable_fields = ctx.index.sortable_fields(ctx.txn)?; for asc_desc in sort_criteria { match asc_desc.member() { Member::Field(ref field) if !crate::is_faceted(field, &sortable_fields) => { return Err(UserError::InvalidSortableAttribute { field: field.to_string(), valid_fields: sortable_fields.into_iter().collect(), })? } Member::Geo(_) if !sortable_fields.contains("_geo") => { return Err(UserError::InvalidSortableAttribute { field: "_geo".to_string(), valid_fields: sortable_fields.into_iter().collect(), })? } _ => (), } } Ok(()) } pub struct PartialSearchResult { pub located_query_terms: Option>, pub candidates: RoaringBitmap, pub documents_ids: Vec, pub document_scores: Vec>, }