269 lines
8.8 KiB
Rust
269 lines
8.8 KiB
Rust
use std::borrow::Cow;
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use std::collections::hash_map::{Entry, HashMap};
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use std::fmt;
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use std::mem::take;
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use std::result::Result as StdResult;
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use std::str::Utf8Error;
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use std::time::Instant;
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use distinct::{Distinct, DocIter, FacetDistinct, NoopDistinct};
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use fst::{IntoStreamer, Streamer};
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use levenshtein_automata::{LevenshteinAutomatonBuilder as LevBuilder, DFA};
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use log::debug;
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use meilisearch_tokenizer::{Analyzer, AnalyzerConfig};
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use once_cell::sync::Lazy;
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use roaring::bitmap::RoaringBitmap;
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pub(crate) use self::facet::ParserRule;
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pub use self::facet::{FacetDistribution, FacetIter, FilterCondition, Operator};
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pub use self::matching_words::MatchingWords;
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use self::query_tree::QueryTreeBuilder;
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use crate::error::FieldIdMapMissingEntry;
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use crate::search::criteria::r#final::{Final, FinalResult};
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use crate::{DocumentId, Index, Result};
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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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mod criteria;
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mod distinct;
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mod facet;
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mod matching_words;
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mod query_tree;
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pub struct Search<'a> {
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query: Option<String>,
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filter: Option<FilterCondition>,
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offset: usize,
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limit: usize,
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optional_words: bool,
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authorize_typos: bool,
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words_limit: usize,
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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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filter: None,
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offset: 0,
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limit: 20,
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optional_words: true,
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authorize_typos: true,
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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 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 optional_words(&mut self, value: bool) -> &mut Search<'a> {
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self.optional_words = value;
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self
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}
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pub fn authorize_typos(&mut self, value: bool) -> &mut Search<'a> {
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self.authorize_typos = 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: FilterCondition) -> &mut Search<'a> {
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self.filter = Some(condition);
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self
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}
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pub fn execute(&self) -> Result<SearchResult> {
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// We create the query tree by spliting the query into tokens.
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let before = Instant::now();
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let (query_tree, primitive_query) = match self.query.as_ref() {
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Some(query) => {
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let mut builder = QueryTreeBuilder::new(self.rtxn, self.index);
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builder.optional_words(self.optional_words);
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builder.authorize_typos(self.authorize_typos);
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builder.words_limit(self.words_limit);
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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 config = AnalyzerConfig::default();
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let stop_words = self.index.stop_words(self.rtxn)?;
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if let Some(ref stop_words) = stop_words {
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config.stop_words(stop_words);
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}
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let analyzer = Analyzer::new(config);
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let result = analyzer.analyze(query);
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let tokens = result.tokens();
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builder.build(tokens)?.map_or((None, None), |(qt, pq)| (Some(qt), Some(pq)))
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}
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None => (None, None),
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};
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debug!("query tree: {:?} took {:.02?}", query_tree, before.elapsed());
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// We create the original candidates with the facet conditions results.
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let before = Instant::now();
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let filtered_candidates = match &self.filter {
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Some(condition) => Some(condition.evaluate(self.rtxn, self.index)?),
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None => None,
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};
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debug!("facet candidates: {:?} took {:.02?}", filtered_candidates, before.elapsed());
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let matching_words = match query_tree.as_ref() {
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Some(query_tree) => MatchingWords::from_query_tree(&query_tree),
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None => MatchingWords::default(),
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};
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let criteria_builder = criteria::CriteriaBuilder::new(self.rtxn, self.index)?;
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let criteria = criteria_builder.build(query_tree, primitive_query, filtered_candidates)?;
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match self.index.distinct_field(self.rtxn)? {
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None => self.perform_sort(NoopDistinct, matching_words, criteria),
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Some(name) => {
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let field_ids_map = self.index.fields_ids_map(self.rtxn)?;
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let id =
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field_ids_map.id(name).ok_or_else(|| FieldIdMapMissingEntry::FieldName {
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field_name: name.to_string(),
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process: "distinct attribute",
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})?;
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let distinct = FacetDistinct::new(id, self.index, self.rtxn);
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self.perform_sort(distinct, matching_words, criteria)
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}
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}
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}
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fn perform_sort<D: Distinct>(
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&self,
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mut distinct: D,
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matching_words: MatchingWords,
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mut criteria: Final,
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) -> Result<SearchResult> {
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let mut offset = self.offset;
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let mut initial_candidates = RoaringBitmap::new();
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let mut excluded_candidates = RoaringBitmap::new();
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let mut documents_ids = Vec::with_capacity(self.limit);
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while let Some(FinalResult { candidates, bucket_candidates, .. }) =
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criteria.next(&excluded_candidates)?
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{
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debug!("Number of candidates found {}", candidates.len());
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let excluded = take(&mut excluded_candidates);
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let mut candidates = distinct.distinct(candidates, excluded);
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initial_candidates.union_with(&bucket_candidates);
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if offset != 0 {
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let discarded = candidates.by_ref().take(offset).count();
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offset = offset.saturating_sub(discarded);
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}
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for candidate in candidates.by_ref().take(self.limit - documents_ids.len()) {
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documents_ids.push(candidate?);
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}
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if documents_ids.len() == self.limit {
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break;
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}
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excluded_candidates = candidates.into_excluded();
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}
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Ok(SearchResult { matching_words, candidates: initial_candidates, 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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filter,
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offset,
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limit,
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optional_words,
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authorize_typos,
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words_limit,
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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("filter", filter)
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.field("offset", offset)
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.field("limit", limit)
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.field("optional_words", optional_words)
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.field("authorize_typos", authorize_typos)
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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)]
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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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// TODO those documents ids should be associated with their criteria scores.
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pub documents_ids: Vec<DocumentId>,
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}
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pub type WordDerivationsCache = HashMap<(String, bool, u8), Vec<(String, u8)>>;
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pub fn word_derivations<'c>(
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word: &str,
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is_prefix: bool,
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max_typo: u8,
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fst: &fst::Set<Cow<[u8]>>,
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cache: &'c mut WordDerivationsCache,
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) -> StdResult<&'c [(String, u8)], Utf8Error> {
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match cache.entry((word.to_string(), is_prefix, max_typo)) {
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Entry::Occupied(entry) => Ok(entry.into_mut()),
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Entry::Vacant(entry) => {
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let mut derived_words = Vec::new();
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let dfa = build_dfa(word, max_typo, is_prefix);
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let mut stream = fst.search_with_state(&dfa).into_stream();
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while let Some((word, state)) = stream.next() {
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let word = std::str::from_utf8(word)?;
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let distance = dfa.distance(state);
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derived_words.push((word.to_string(), distance.to_u8()));
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}
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Ok(entry.insert(derived_words))
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}
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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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