mirror of
https://github.com/meilisearch/MeiliSearch
synced 2024-11-24 05:44:25 +01:00
495 lines
16 KiB
Rust
495 lines
16 KiB
Rust
mod bucket_sort;
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mod db_cache;
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mod distinct;
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mod geo_sort;
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mod graph_based_ranking_rule;
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mod interner;
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mod limits;
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mod logger;
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pub mod matches;
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mod query_graph;
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mod query_term;
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mod ranking_rule_graph;
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mod ranking_rules;
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mod resolve_query_graph;
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mod small_bitmap;
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mod exact_attribute;
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// TODO: documentation + comments
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// implementation is currently an adaptation of the previous implementation to fit with the new model
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mod sort;
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// TODO: documentation + comments
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mod words;
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#[cfg(test)]
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mod tests;
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use std::collections::HashSet;
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use bucket_sort::{bucket_sort, BucketSortOutput};
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use charabia::TokenizerBuilder;
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use db_cache::DatabaseCache;
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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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use interner::{DedupInterner, Interner};
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pub use logger::visual::VisualSearchLogger;
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pub use logger::{DefaultSearchLogger, SearchLogger};
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use query_graph::{QueryGraph, QueryNode};
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use query_term::{located_query_terms_from_string, LocatedQueryTerm, Phrase, QueryTerm};
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use ranking_rules::{
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BoxRankingRule, PlaceholderQuery, RankingRule, RankingRuleOutput, RankingRuleQueryTrait,
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};
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use resolve_query_graph::{compute_query_graph_docids, PhraseDocIdsCache};
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use roaring::RoaringBitmap;
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use sort::Sort;
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use words::Words;
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use self::geo_sort::GeoSort;
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pub use self::geo_sort::Strategy as GeoSortStrategy;
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use self::interner::Interned;
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use crate::search::new::distinct::apply_distinct_rule;
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use crate::{AscDesc, DocumentId, Filter, Index, Member, Result, TermsMatchingStrategy, UserError};
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/// A structure used throughout the execution of a search query.
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pub struct SearchContext<'ctx> {
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pub index: &'ctx Index,
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pub txn: &'ctx RoTxn<'ctx>,
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pub db_cache: DatabaseCache<'ctx>,
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pub word_interner: DedupInterner<String>,
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pub phrase_interner: DedupInterner<Phrase>,
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pub term_interner: Interner<QueryTerm>,
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pub phrase_docids: PhraseDocIdsCache,
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}
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impl<'ctx> SearchContext<'ctx> {
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pub fn new(index: &'ctx Index, txn: &'ctx RoTxn<'ctx>) -> Self {
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Self {
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index,
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txn,
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db_cache: <_>::default(),
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word_interner: <_>::default(),
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phrase_interner: <_>::default(),
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term_interner: <_>::default(),
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phrase_docids: <_>::default(),
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}
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}
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}
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#[derive(Clone, Copy, PartialEq, PartialOrd, Ord, Eq)]
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pub enum Word {
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Original(Interned<String>),
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Derived(Interned<String>),
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}
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impl Word {
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pub fn interned(&self) -> Interned<String> {
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match self {
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Word::Original(word) => *word,
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Word::Derived(word) => *word,
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}
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}
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}
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/// Apply the [`TermsMatchingStrategy`] to the query graph and resolve it.
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#[allow(clippy::too_many_arguments)]
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fn resolve_maximally_reduced_query_graph(
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ctx: &mut SearchContext,
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universe: &RoaringBitmap,
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query_graph: &QueryGraph,
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matching_strategy: TermsMatchingStrategy,
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logger: &mut dyn SearchLogger<QueryGraph>,
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) -> Result<RoaringBitmap> {
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let mut graph = query_graph.clone();
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let nodes_to_remove = match matching_strategy {
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TermsMatchingStrategy::Last => query_graph
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.removal_order_for_terms_matching_strategy_last(ctx)
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.iter()
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.flat_map(|x| x.iter())
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.collect(),
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TermsMatchingStrategy::All => vec![],
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};
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graph.remove_nodes_keep_edges(&nodes_to_remove);
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logger.query_for_initial_universe(&graph);
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let docids = compute_query_graph_docids(ctx, &graph, universe)?;
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Ok(docids)
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}
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fn resolve_universe(
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ctx: &mut SearchContext,
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initial_universe: &RoaringBitmap,
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query_graph: &QueryGraph,
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matching_strategy: TermsMatchingStrategy,
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logger: &mut dyn SearchLogger<QueryGraph>,
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) -> Result<RoaringBitmap> {
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resolve_maximally_reduced_query_graph(
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ctx,
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initial_universe,
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query_graph,
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matching_strategy,
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logger,
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)
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}
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/// Return the list of initialised ranking rules to be used for a placeholder search.
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fn get_ranking_rules_for_placeholder_search<'ctx>(
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ctx: &SearchContext<'ctx>,
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sort_criteria: &Option<Vec<AscDesc>>,
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geo_strategy: geo_sort::Strategy,
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) -> Result<Vec<BoxRankingRule<'ctx, PlaceholderQuery>>> {
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let mut sort = false;
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let mut sorted_fields = HashSet::new();
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let mut geo_sorted = false;
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let mut ranking_rules: Vec<BoxRankingRule<PlaceholderQuery>> = vec![];
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let settings_ranking_rules = ctx.index.criteria(ctx.txn)?;
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for rr in settings_ranking_rules {
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match rr {
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// These rules need a query to have an effect; ignore them in placeholder search
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crate::Criterion::Words
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| crate::Criterion::Typo
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| crate::Criterion::Attribute
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| crate::Criterion::Proximity
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| crate::Criterion::Exactness => continue,
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crate::Criterion::Sort => {
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if sort {
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continue;
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}
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resolve_sort_criteria(
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sort_criteria,
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ctx,
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&mut ranking_rules,
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&mut sorted_fields,
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&mut geo_sorted,
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geo_strategy,
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)?;
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sort = true;
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}
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crate::Criterion::Asc(field_name) => {
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if sorted_fields.contains(&field_name) {
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continue;
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}
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sorted_fields.insert(field_name.clone());
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ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, true)?));
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}
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crate::Criterion::Desc(field_name) => {
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if sorted_fields.contains(&field_name) {
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continue;
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}
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sorted_fields.insert(field_name.clone());
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ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, false)?));
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}
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}
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}
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Ok(ranking_rules)
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}
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/// Return the list of initialised ranking rules to be used for a query graph search.
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fn get_ranking_rules_for_query_graph_search<'ctx>(
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ctx: &SearchContext<'ctx>,
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sort_criteria: &Option<Vec<AscDesc>>,
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geo_strategy: geo_sort::Strategy,
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terms_matching_strategy: TermsMatchingStrategy,
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) -> Result<Vec<BoxRankingRule<'ctx, QueryGraph>>> {
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// query graph search
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let mut words = false;
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let mut typo = false;
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let mut proximity = false;
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let mut sort = false;
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let mut attribute = false;
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let mut exactness = false;
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let mut sorted_fields = HashSet::new();
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let mut geo_sorted = false;
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let mut ranking_rules: Vec<BoxRankingRule<QueryGraph>> = vec![];
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let settings_ranking_rules = ctx.index.criteria(ctx.txn)?;
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for rr in settings_ranking_rules {
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// Add Words before any of: typo, proximity, attribute
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match rr {
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crate::Criterion::Typo
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| crate::Criterion::Attribute
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| crate::Criterion::Proximity
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| crate::Criterion::Exactness => {
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if !words {
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ranking_rules.push(Box::new(Words::new(terms_matching_strategy)));
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words = true;
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}
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}
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_ => {}
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}
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match rr {
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crate::Criterion::Words => {
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if words {
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continue;
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}
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ranking_rules.push(Box::new(Words::new(terms_matching_strategy)));
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words = true;
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}
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crate::Criterion::Typo => {
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if typo {
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continue;
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}
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typo = true;
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ranking_rules.push(Box::new(Typo::new(None)));
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}
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crate::Criterion::Proximity => {
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if proximity {
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continue;
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}
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proximity = true;
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ranking_rules.push(Box::new(Proximity::new(None)));
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}
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crate::Criterion::Attribute => {
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if attribute {
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continue;
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}
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attribute = true;
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ranking_rules.push(Box::new(Fid::new(None)));
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ranking_rules.push(Box::new(Position::new(None)));
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}
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crate::Criterion::Sort => {
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if sort {
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continue;
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}
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resolve_sort_criteria(
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sort_criteria,
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ctx,
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&mut ranking_rules,
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&mut sorted_fields,
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&mut geo_sorted,
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geo_strategy,
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)?;
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sort = true;
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}
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crate::Criterion::Exactness => {
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if exactness {
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continue;
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}
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ranking_rules.push(Box::new(ExactAttribute::new()));
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ranking_rules.push(Box::new(Exactness::new()));
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exactness = true;
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}
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crate::Criterion::Asc(field_name) => {
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if sorted_fields.contains(&field_name) {
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continue;
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}
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sorted_fields.insert(field_name.clone());
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ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, true)?));
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}
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crate::Criterion::Desc(field_name) => {
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if sorted_fields.contains(&field_name) {
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continue;
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}
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sorted_fields.insert(field_name.clone());
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ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, false)?));
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}
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}
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}
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Ok(ranking_rules)
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}
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fn resolve_sort_criteria<'ctx, Query: RankingRuleQueryTrait>(
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sort_criteria: &Option<Vec<AscDesc>>,
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ctx: &SearchContext<'ctx>,
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ranking_rules: &mut Vec<BoxRankingRule<'ctx, Query>>,
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sorted_fields: &mut HashSet<String>,
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geo_sorted: &mut bool,
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geo_strategy: geo_sort::Strategy,
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) -> Result<()> {
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let sort_criteria = sort_criteria.clone().unwrap_or_default();
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ranking_rules.reserve(sort_criteria.len());
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for criterion in sort_criteria {
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match criterion {
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AscDesc::Asc(Member::Field(field_name)) => {
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if sorted_fields.contains(&field_name) {
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continue;
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}
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sorted_fields.insert(field_name.clone());
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ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, true)?));
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}
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AscDesc::Desc(Member::Field(field_name)) => {
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if sorted_fields.contains(&field_name) {
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continue;
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}
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sorted_fields.insert(field_name.clone());
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ranking_rules.push(Box::new(Sort::new(ctx.index, ctx.txn, field_name, false)?));
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}
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AscDesc::Asc(Member::Geo(point)) => {
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if *geo_sorted {
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continue;
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}
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let geo_faceted_docids = ctx.index.geo_faceted_documents_ids(ctx.txn)?;
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ranking_rules.push(Box::new(GeoSort::new(
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geo_strategy,
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geo_faceted_docids,
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point,
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true,
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)?));
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}
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AscDesc::Desc(Member::Geo(point)) => {
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if *geo_sorted {
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continue;
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}
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let geo_faceted_docids = ctx.index.geo_faceted_documents_ids(ctx.txn)?;
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ranking_rules.push(Box::new(GeoSort::new(
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geo_strategy,
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geo_faceted_docids,
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point,
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false,
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)?));
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}
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};
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}
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Ok(())
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}
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#[allow(clippy::too_many_arguments)]
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pub fn execute_search(
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ctx: &mut SearchContext,
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query: &Option<String>,
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terms_matching_strategy: TermsMatchingStrategy,
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exhaustive_number_hits: bool,
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filters: &Option<Filter>,
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sort_criteria: &Option<Vec<AscDesc>>,
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geo_strategy: geo_sort::Strategy,
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from: usize,
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length: usize,
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words_limit: Option<usize>,
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placeholder_search_logger: &mut dyn SearchLogger<PlaceholderQuery>,
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query_graph_logger: &mut dyn SearchLogger<QueryGraph>,
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) -> Result<PartialSearchResult> {
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let mut universe = if let Some(filters) = filters {
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filters.evaluate(ctx.txn, ctx.index)?
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} else {
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ctx.index.documents_ids(ctx.txn)?
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};
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check_sort_criteria(ctx, sort_criteria.as_ref())?;
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let mut located_query_terms = None;
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let query_terms = if let Some(query) = query {
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// We make sure that the analyzer is aware of the stop words
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// this ensures that the query builder is able to properly remove them.
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let mut tokbuilder = TokenizerBuilder::new();
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let stop_words = ctx.index.stop_words(ctx.txn)?;
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if let Some(ref stop_words) = stop_words {
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tokbuilder.stop_words(stop_words);
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}
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let script_lang_map = ctx.index.script_language(ctx.txn)?;
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if !script_lang_map.is_empty() {
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tokbuilder.allow_list(&script_lang_map);
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}
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let tokenizer = tokbuilder.build();
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let tokens = tokenizer.tokenize(query);
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let query_terms = located_query_terms_from_string(ctx, tokens, words_limit)?;
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if query_terms.is_empty() {
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// Do a placeholder search instead
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None
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} else {
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Some(query_terms)
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}
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} else {
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None
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};
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let bucket_sort_output = if let Some(query_terms) = query_terms {
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let graph = QueryGraph::from_query(ctx, &query_terms)?;
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located_query_terms = Some(query_terms);
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let ranking_rules = get_ranking_rules_for_query_graph_search(
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ctx,
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sort_criteria,
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geo_strategy,
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terms_matching_strategy,
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)?;
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universe =
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resolve_universe(ctx, &universe, &graph, terms_matching_strategy, query_graph_logger)?;
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bucket_sort(ctx, ranking_rules, &graph, &universe, from, length, query_graph_logger)?
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} else {
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let ranking_rules =
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get_ranking_rules_for_placeholder_search(ctx, sort_criteria, geo_strategy)?;
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bucket_sort(
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ctx,
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ranking_rules,
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&PlaceholderQuery,
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&universe,
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from,
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length,
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placeholder_search_logger,
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)?
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};
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let BucketSortOutput { docids, mut all_candidates } = bucket_sort_output;
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// The candidates is the universe unless the exhaustive number of hits
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// is requested and a distinct attribute is set.
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if exhaustive_number_hits {
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if let Some(f) = ctx.index.distinct_field(ctx.txn)? {
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if let Some(distinct_fid) = ctx.index.fields_ids_map(ctx.txn)?.id(f) {
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all_candidates = apply_distinct_rule(ctx, distinct_fid, &all_candidates)?.remaining;
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}
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}
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}
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Ok(PartialSearchResult {
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candidates: all_candidates,
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documents_ids: docids,
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located_query_terms,
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})
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}
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fn check_sort_criteria(ctx: &SearchContext, sort_criteria: Option<&Vec<AscDesc>>) -> Result<()> {
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let sort_criteria = if let Some(sort_criteria) = sort_criteria {
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sort_criteria
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} else {
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return Ok(());
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};
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if sort_criteria.is_empty() {
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return Ok(());
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}
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// We check that the sort ranking rule exists and throw an
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// error if we try to use it and that it doesn't.
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let sort_ranking_rule_missing = !ctx.index.criteria(ctx.txn)?.contains(&crate::Criterion::Sort);
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if sort_ranking_rule_missing {
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return Err(UserError::SortRankingRuleMissing.into());
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}
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// We check that we are allowed to use the sort criteria, we check
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// that they are declared in the sortable fields.
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let sortable_fields = ctx.index.sortable_fields(ctx.txn)?;
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for asc_desc in sort_criteria {
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match asc_desc.member() {
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Member::Field(ref field) if !crate::is_faceted(field, &sortable_fields) => {
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return Err(UserError::InvalidSortableAttribute {
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field: field.to_string(),
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valid_fields: sortable_fields.into_iter().collect(),
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})?
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}
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Member::Geo(_) if !sortable_fields.contains("_geo") => {
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return Err(UserError::InvalidSortableAttribute {
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field: "_geo".to_string(),
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valid_fields: sortable_fields.into_iter().collect(),
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})?
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}
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_ => (),
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}
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}
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Ok(())
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}
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pub struct PartialSearchResult {
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pub located_query_terms: Option<Vec<LocatedQueryTerm>>,
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pub candidates: RoaringBitmap,
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pub documents_ids: Vec<DocumentId>,
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}
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