mirror of
https://github.com/meilisearch/meilisearch.git
synced 2024-11-24 02:55:06 +08:00
381 lines
12 KiB
Rust
381 lines
12 KiB
Rust
use std::fmt;
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use fst::automaton::{Complement, Intersection, StartsWith, Str, Union};
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use fst::Streamer;
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use levenshtein_automata::{LevenshteinAutomatonBuilder as LevBuilder, DFA};
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use once_cell::sync::Lazy;
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use roaring::bitmap::RoaringBitmap;
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pub use self::facet::{FacetDistribution, Filter, DEFAULT_VALUES_PER_FACET};
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pub use self::new::matches::{FormatOptions, MatchBounds, Matcher, MatcherBuilder, MatchingWords};
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use self::new::PartialSearchResult;
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use crate::error::UserError;
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use crate::heed_codec::facet::{FacetGroupKey, FacetGroupValue};
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use crate::score_details::{ScoreDetails, ScoringStrategy};
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use crate::{
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execute_search, AscDesc, DefaultSearchLogger, DocumentId, Index, Result, SearchContext, BEU16,
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};
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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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static LEVDIST1: Lazy<LevBuilder> = Lazy::new(|| LevBuilder::new(1, true));
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static LEVDIST2: Lazy<LevBuilder> = Lazy::new(|| LevBuilder::new(2, true));
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/// The maximum number of facets returned by the facet search route.
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const MAX_NUMBER_OF_FACETS: usize = 1000;
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pub mod facet;
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mod fst_utils;
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pub mod new;
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pub struct Search<'a> {
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query: Option<String>,
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vector: Option<Vec<f32>>,
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// this should be linked to the String in the query
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filter: Option<Filter<'a>>,
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offset: usize,
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limit: usize,
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sort_criteria: Option<Vec<AscDesc>>,
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searchable_attributes: Option<&'a [String]>,
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geo_strategy: new::GeoSortStrategy,
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terms_matching_strategy: TermsMatchingStrategy,
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scoring_strategy: ScoringStrategy,
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words_limit: usize,
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exhaustive_number_hits: bool,
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rtxn: &'a heed::RoTxn<'a>,
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index: &'a Index,
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}
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impl<'a> Search<'a> {
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pub fn new(rtxn: &'a heed::RoTxn, index: &'a Index) -> Search<'a> {
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Search {
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query: None,
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vector: None,
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filter: None,
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offset: 0,
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limit: 20,
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sort_criteria: None,
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searchable_attributes: None,
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geo_strategy: new::GeoSortStrategy::default(),
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terms_matching_strategy: TermsMatchingStrategy::default(),
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scoring_strategy: Default::default(),
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exhaustive_number_hits: false,
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words_limit: 10,
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rtxn,
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index,
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}
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}
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pub fn query(&mut self, query: impl Into<String>) -> &mut Search<'a> {
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self.query = Some(query.into());
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self
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}
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pub fn vector(&mut self, vector: impl Into<Vec<f32>>) -> &mut Search<'a> {
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self.vector = Some(vector.into());
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self
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}
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pub fn offset(&mut self, offset: usize) -> &mut Search<'a> {
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self.offset = offset;
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self
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}
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pub fn limit(&mut self, limit: usize) -> &mut Search<'a> {
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self.limit = limit;
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self
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}
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pub fn sort_criteria(&mut self, criteria: Vec<AscDesc>) -> &mut Search<'a> {
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self.sort_criteria = Some(criteria);
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self
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}
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pub fn searchable_attributes(&mut self, searchable: &'a [String]) -> &mut Search<'a> {
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self.searchable_attributes = Some(searchable);
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self
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}
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pub fn terms_matching_strategy(&mut self, value: TermsMatchingStrategy) -> &mut Search<'a> {
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self.terms_matching_strategy = value;
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self
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}
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pub fn scoring_strategy(&mut self, value: ScoringStrategy) -> &mut Search<'a> {
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self.scoring_strategy = value;
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self
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}
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pub fn words_limit(&mut self, value: usize) -> &mut Search<'a> {
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self.words_limit = value;
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self
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}
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pub fn filter(&mut self, condition: Filter<'a>) -> &mut Search<'a> {
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self.filter = Some(condition);
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self
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}
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#[cfg(test)]
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pub fn geo_sort_strategy(&mut self, strategy: new::GeoSortStrategy) -> &mut Search<'a> {
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self.geo_strategy = strategy;
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self
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}
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/// Forces the search to exhaustively compute the number of candidates,
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/// this will increase the search time but allows finite pagination.
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pub fn exhaustive_number_hits(&mut self, exhaustive_number_hits: bool) -> &mut Search<'a> {
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self.exhaustive_number_hits = exhaustive_number_hits;
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self
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}
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pub fn execute(&self) -> Result<SearchResult> {
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let mut ctx = SearchContext::new(self.index, self.rtxn);
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if let Some(searchable_attributes) = self.searchable_attributes {
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ctx.searchable_attributes(searchable_attributes)?;
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}
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let PartialSearchResult { located_query_terms, candidates, documents_ids, document_scores } =
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execute_search(
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&mut ctx,
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&self.query,
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&self.vector,
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self.terms_matching_strategy,
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self.scoring_strategy,
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self.exhaustive_number_hits,
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&self.filter,
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&self.sort_criteria,
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self.geo_strategy,
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self.offset,
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self.limit,
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Some(self.words_limit),
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&mut DefaultSearchLogger,
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&mut DefaultSearchLogger,
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)?;
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// consume context and located_query_terms to build MatchingWords.
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let matching_words = match located_query_terms {
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Some(located_query_terms) => MatchingWords::new(ctx, located_query_terms),
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None => MatchingWords::default(),
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};
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Ok(SearchResult { matching_words, candidates, document_scores, documents_ids })
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}
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}
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impl fmt::Debug for Search<'_> {
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fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
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let Search {
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query,
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vector: _,
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filter,
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offset,
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limit,
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sort_criteria,
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searchable_attributes,
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geo_strategy: _,
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terms_matching_strategy,
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scoring_strategy,
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words_limit,
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exhaustive_number_hits,
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rtxn: _,
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index: _,
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} = self;
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f.debug_struct("Search")
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.field("query", query)
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.field("vector", &"[...]")
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.field("filter", filter)
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.field("offset", offset)
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.field("limit", limit)
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.field("sort_criteria", sort_criteria)
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.field("searchable_attributes", searchable_attributes)
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.field("terms_matching_strategy", terms_matching_strategy)
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.field("scoring_strategy", scoring_strategy)
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.field("exhaustive_number_hits", exhaustive_number_hits)
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.field("words_limit", words_limit)
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.finish()
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}
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}
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#[derive(Default, Debug)]
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pub struct SearchResult {
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pub matching_words: MatchingWords,
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pub candidates: RoaringBitmap,
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pub documents_ids: Vec<DocumentId>,
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pub document_scores: Vec<Vec<ScoreDetails>>,
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}
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#[derive(Debug, Clone, Copy, PartialEq, Eq)]
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pub enum TermsMatchingStrategy {
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// remove last word first
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Last,
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// all words are mandatory
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All,
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}
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impl Default for TermsMatchingStrategy {
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fn default() -> Self {
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Self::Last
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}
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}
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fn get_first(s: &str) -> &str {
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match s.chars().next() {
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Some(c) => &s[..c.len_utf8()],
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None => panic!("unexpected empty query"),
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}
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}
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pub fn build_dfa(word: &str, typos: u8, is_prefix: bool) -> DFA {
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let lev = match typos {
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0 => &LEVDIST0,
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1 => &LEVDIST1,
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_ => &LEVDIST2,
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};
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if is_prefix {
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lev.build_prefix_dfa(word)
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} else {
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lev.build_dfa(word)
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}
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}
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pub struct SearchForFacetValue<'a> {
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query: Option<String>,
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facet: String,
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search_query: Search<'a>,
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}
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impl<'a> SearchForFacetValue<'a> {
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pub fn new(facet: String, search_query: Search<'a>) -> SearchForFacetValue<'a> {
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SearchForFacetValue { query: None, facet, search_query }
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}
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pub fn query(&mut self, query: impl Into<String>) -> &mut Self {
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self.query = Some(query.into());
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self
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}
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pub fn execute(&self) -> Result<Vec<FacetSearchResult>> {
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let index = self.search_query.index;
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let rtxn = self.search_query.rtxn;
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let filterable_fields = index.filterable_fields(rtxn)?;
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if !filterable_fields.contains(&self.facet) {
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// TODO create a new type of error
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return Err(UserError::InvalidSortableAttribute {
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field: self.facet.clone(),
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valid_fields: filterable_fields.into_iter().collect(),
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})?;
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}
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let fields_ids_map = index.fields_ids_map(rtxn)?;
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let (field_id, fst) = match fields_ids_map.id(&self.facet) {
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Some(fid) => {
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match self.search_query.index.facet_id_string_fst.get(rtxn, &BEU16::new(fid))? {
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Some(fst) => (fid, fst),
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None => todo!("return an error, is the user trying to search in numbers?"),
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}
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}
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None => todo!("return an internal error bug"),
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};
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let search_candidates = self.search_query.execute()?.candidates;
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match self.query.as_ref() {
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Some(query) => {
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let is_prefix = true;
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let starts = StartsWith(Str::new(get_first(query)));
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let first = Intersection(build_dfa(query, 1, is_prefix), Complement(&starts));
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let second_dfa = build_dfa(query, 2, is_prefix);
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let second = Intersection(&second_dfa, &starts);
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let automaton = Union(first, &second);
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let mut stream = fst.search(automaton).into_stream();
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let mut result = vec![];
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let mut length = 0;
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while let Some(facet_value) = stream.next() {
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let value = std::str::from_utf8(facet_value)?;
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let key = FacetGroupKey { field_id, level: 0, left_bound: value };
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let docids = match index.facet_id_string_docids.get(rtxn, &key)? {
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Some(FacetGroupValue { bitmap, .. }) => bitmap,
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None => todo!("return an internal error"),
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};
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let count = search_candidates.intersection_len(&docids);
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if count != 0 {
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result.push(FacetSearchResult { value: value.to_string(), count });
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length += 1;
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}
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if length >= MAX_NUMBER_OF_FACETS {
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break;
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}
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}
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Ok(result)
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}
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None => {
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let mut stream = fst.stream();
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let mut result = vec![];
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let mut length = 0;
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while let Some(facet_value) = stream.next() {
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let value = std::str::from_utf8(facet_value)?;
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let key = FacetGroupKey { field_id, level: 0, left_bound: value };
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let docids = match index.facet_id_string_docids.get(rtxn, &key)? {
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Some(FacetGroupValue { bitmap, .. }) => bitmap,
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None => todo!("return an internal error"),
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};
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let count = search_candidates.intersection_len(&docids);
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if count != 0 {
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result.push(FacetSearchResult { value: value.to_string(), count });
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length += 1;
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}
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if length >= MAX_NUMBER_OF_FACETS {
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break;
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}
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}
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Ok(result)
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}
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}
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}
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}
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#[derive(Debug, serde::Serialize)]
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pub struct FacetSearchResult {
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/// The original facet value
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pub value: String,
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/// The number of documents associated to this facet
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pub count: u64,
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}
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#[cfg(test)]
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mod test {
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#[allow(unused_imports)]
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use super::*;
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#[cfg(feature = "japanese")]
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#[test]
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fn test_kanji_language_detection() {
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use crate::index::tests::TempIndex;
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let index = TempIndex::new();
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index
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.add_documents(documents!([
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{ "id": 0, "title": "The quick (\"brown\") fox can't jump 32.3 feet, right? Brr, it's 29.3°F!" },
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{ "id": 1, "title": "東京のお寿司。" },
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{ "id": 2, "title": "הַשּׁוּעָל הַמָּהִיר (״הַחוּם״) לֹא יָכוֹל לִקְפֹּץ 9.94 מֶטְרִים, נָכוֹן? ברר, 1.5°C- בַּחוּץ!" }
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]))
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.unwrap();
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let txn = index.write_txn().unwrap();
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let mut search = Search::new(&txn, &index);
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search.query("東京");
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let SearchResult { documents_ids, .. } = search.execute().unwrap();
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assert_eq!(documents_ids, vec![1]);
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}
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}
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