Move the searchForFacetValues struct into a dedicated module
This commit is contained in:
Clément Renault
parent
9f7a4fbfeb
commit
306b25ad3a
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@ -57,10 +57,10 @@ pub use self::heed_codec::{
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UncheckedU8StrStrCodec,
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};
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pub use self::index::Index;
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pub use self::search::facet::{FacetValueHit, SearchForFacetValues};
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pub use self::search::{
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FacetDistribution, FacetValueHit, Filter, FormatOptions, MatchBounds, MatcherBuilder,
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MatchingWords, OrderBy, Search, SearchForFacetValues, SearchResult, TermsMatchingStrategy,
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DEFAULT_VALUES_PER_FACET,
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FacetDistribution, Filter, FormatOptions, MatchBounds, MatcherBuilder, MatchingWords, OrderBy,
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Search, SearchResult, TermsMatchingStrategy, DEFAULT_VALUES_PER_FACET,
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};
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pub type Result<T> = std::result::Result<T, error::Error>;
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@ -6,15 +6,18 @@ use roaring::RoaringBitmap;
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pub use self::facet_distribution::{FacetDistribution, OrderBy, DEFAULT_VALUES_PER_FACET};
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pub use self::filter::{BadGeoError, Filter};
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pub use self::search::{FacetValueHit, SearchForFacetValues};
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use crate::heed_codec::facet::{FacetGroupKeyCodec, FacetGroupValueCodec, OrderedF64Codec};
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use crate::heed_codec::BytesRefCodec;
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use crate::{Index, Result};
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mod facet_distribution;
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mod facet_distribution_iter;
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mod facet_range_search;
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mod facet_sort_ascending;
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mod facet_sort_descending;
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mod filter;
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mod search;
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fn facet_extreme_value<'t>(
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mut extreme_it: impl Iterator<Item = heed::Result<(RoaringBitmap, &'t [u8])>> + 't,
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@ -0,0 +1,300 @@
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use std::cmp::{Ordering, Reverse};
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use std::collections::BinaryHeap;
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use std::ops::ControlFlow;
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use charabia::normalizer::NormalizerOption;
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use charabia::Normalize;
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use fst::automaton::{Automaton, Str};
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use fst::{IntoStreamer, Streamer};
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use roaring::RoaringBitmap;
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use tracing::error;
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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::search::build_dfa;
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use crate::{DocumentId, FieldId, OrderBy, Result, Search};
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/// The maximum number of values per facet returned by the facet search route.
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const DEFAULT_MAX_NUMBER_OF_VALUES_PER_FACET: usize = 100;
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pub struct SearchForFacetValues<'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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max_values: usize,
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is_hybrid: bool,
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}
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impl<'a> SearchForFacetValues<'a> {
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pub fn new(
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facet: String,
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search_query: Search<'a>,
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is_hybrid: bool,
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) -> SearchForFacetValues<'a> {
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SearchForFacetValues {
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query: None,
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facet,
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search_query,
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max_values: DEFAULT_MAX_NUMBER_OF_VALUES_PER_FACET,
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is_hybrid,
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}
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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 max_values(&mut self, max: usize) -> &mut Self {
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self.max_values = max;
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self
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}
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fn one_original_value_of(
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&self,
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field_id: FieldId,
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facet_str: &str,
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any_docid: DocumentId,
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) -> Result<Option<String>> {
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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 key: (FieldId, _, &str) = (field_id, any_docid, facet_str);
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Ok(index.field_id_docid_facet_strings.get(rtxn, &key)?.map(|v| v.to_owned()))
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}
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pub fn execute(&self) -> Result<Vec<FacetValueHit>> {
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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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let (valid_fields, hidden_fields) =
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index.remove_hidden_fields(rtxn, filterable_fields)?;
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return Err(UserError::InvalidFacetSearchFacetName {
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field: self.facet.clone(),
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valid_fields,
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hidden_fields,
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}
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.into());
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}
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let fields_ids_map = index.fields_ids_map(rtxn)?;
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let fid = match fields_ids_map.id(&self.facet) {
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Some(fid) => fid,
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// we return an empty list of results when the attribute has been
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// set as filterable but no document contains this field (yet).
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None => return Ok(Vec::new()),
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};
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let fst = match self.search_query.index.facet_id_string_fst.get(rtxn, &fid)? {
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Some(fst) => fst,
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None => return Ok(vec![]),
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};
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let search_candidates = self
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.search_query
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.execute_for_candidates(self.is_hybrid || self.search_query.vector.is_some())?;
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let sort_by = index.sort_facet_values_by(rtxn)?.get(&self.facet);
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match self.query.as_ref() {
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Some(query) => {
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let options = NormalizerOption { lossy: true, ..Default::default() };
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let query = query.normalize(&options);
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let query = query.as_ref();
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let authorize_typos = self.search_query.index.authorize_typos(rtxn)?;
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let field_authorizes_typos =
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!self.search_query.index.exact_attributes_ids(rtxn)?.contains(&fid);
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if authorize_typos && field_authorizes_typos {
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let exact_words_fst = self.search_query.index.exact_words(rtxn)?;
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if exact_words_fst.map_or(false, |fst| fst.contains(query)) {
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let mut results = vec![];
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if fst.contains(query) {
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self.fetch_original_facets_using_normalized(
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fid,
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query,
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query,
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&search_candidates,
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&mut results,
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)?;
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}
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Ok(results)
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} else {
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let one_typo = self.search_query.index.min_word_len_one_typo(rtxn)?;
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let two_typos = self.search_query.index.min_word_len_two_typos(rtxn)?;
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let is_prefix = true;
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let automaton = if query.len() < one_typo as usize {
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build_dfa(query, 0, is_prefix)
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} else if query.len() < two_typos as usize {
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build_dfa(query, 1, is_prefix)
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} else {
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build_dfa(query, 2, is_prefix)
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};
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let mut stream = fst.search(automaton).into_stream();
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let mut results = vec![];
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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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if self
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.fetch_original_facets_using_normalized(
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fid,
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value,
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query,
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&search_candidates,
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&mut results,
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)?
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.is_break()
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{
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break;
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}
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}
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Ok(results)
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}
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} else {
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let automaton = Str::new(query).starts_with();
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let mut stream = fst.search(automaton).into_stream();
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let mut results = vec![];
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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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if self
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.fetch_original_facets_using_normalized(
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fid,
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value,
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query,
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&search_candidates,
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&mut results,
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)?
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.is_break()
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{
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break;
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}
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}
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Ok(results)
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}
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}
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None => {
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let prefix = FacetGroupKey { field_id: fid, level: 0, left_bound: "" };
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match sort_by {
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OrderBy::Lexicographic => {
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let mut results = vec![];
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for result in index.facet_id_string_docids.prefix_iter(rtxn, &prefix)? {
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let (FacetGroupKey { left_bound, .. }, FacetGroupValue { bitmap, .. }) =
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result?;
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let count = search_candidates.intersection_len(&bitmap);
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if count != 0 {
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let value = self
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.one_original_value_of(fid, left_bound, bitmap.min().unwrap())?
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.unwrap_or_else(|| left_bound.to_string());
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results.push(FacetValueHit { value, count });
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}
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if results.len() >= self.max_values {
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break;
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}
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}
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Ok(results)
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}
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OrderBy::Count => {
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let mut top_counts = BinaryHeap::new();
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for result in index.facet_id_string_docids.prefix_iter(rtxn, &prefix)? {
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let (FacetGroupKey { left_bound, .. }, FacetGroupValue { bitmap, .. }) =
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result?;
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let count = search_candidates.intersection_len(&bitmap);
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if count != 0 {
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let value = self
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.one_original_value_of(fid, left_bound, bitmap.min().unwrap())?
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.unwrap_or_else(|| left_bound.to_string());
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if top_counts.len() >= self.max_values {
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top_counts.pop();
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}
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// It is a max heap and we need to move the smallest counts at the
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// top to be able to pop them when we reach the max_values limit.
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top_counts.push(Reverse(FacetValueHit { value, count }));
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}
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}
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// Convert the heap into a vec of hits by removing the Reverse wrapper.
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// Hits are already in the right order as they were reversed and there
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// are output in ascending order.
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Ok(top_counts
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.into_sorted_vec()
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.into_iter()
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.map(|Reverse(hit)| hit)
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.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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fn fetch_original_facets_using_normalized(
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&self,
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fid: FieldId,
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value: &str,
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query: &str,
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search_candidates: &RoaringBitmap,
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results: &mut Vec<FacetValueHit>,
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) -> Result<ControlFlow<()>> {
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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 database = index.facet_id_normalized_string_strings;
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let key = (fid, value);
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let original_strings = match database.get(rtxn, &key)? {
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Some(original_strings) => original_strings,
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None => {
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error!("the facet value is missing from the facet database: {key:?}");
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return Ok(ControlFlow::Continue(()));
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}
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};
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for original in original_strings {
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let key = FacetGroupKey { field_id: fid, level: 0, left_bound: original.as_str() };
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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 => {
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error!("the facet value is missing from the facet database: {key:?}");
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return Ok(ControlFlow::Continue(()));
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}
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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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let value = self
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.one_original_value_of(fid, &original, docids.min().unwrap())?
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.unwrap_or_else(|| query.to_string());
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results.push(FacetValueHit { value, count });
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}
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if results.len() >= self.max_values {
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return Ok(ControlFlow::Break(()));
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}
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}
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Ok(ControlFlow::Continue(()))
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}
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}
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#[derive(Debug, Clone, serde::Serialize, PartialEq)]
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pub struct FacetValueHit {
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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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impl PartialOrd for FacetValueHit {
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fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
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Some(self.cmp(other))
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}
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}
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impl Ord for FacetValueHit {
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fn cmp(&self, other: &Self) -> Ordering {
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self.count.cmp(&other.count).then_with(|| self.value.cmp(&other.value))
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}
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}
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impl Eq for FacetValueHit {}
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@ -1,27 +1,17 @@
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use std::cmp::{Ordering, Reverse};
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use std::collections::BinaryHeap;
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use std::fmt;
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use std::ops::ControlFlow;
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use charabia::normalizer::NormalizerOption;
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use charabia::Normalize;
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use fst::automaton::{Automaton, Str};
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use fst::{IntoStreamer, 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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use tracing::error;
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pub use self::facet::{FacetDistribution, Filter, OrderBy, DEFAULT_VALUES_PER_FACET};
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pub use self::new::matches::{FormatOptions, MatchBounds, MatcherBuilder, MatchingWords};
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use self::new::{execute_vector_search, 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::vector::DistributionShift;
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use crate::{
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execute_search, filtered_universe, AscDesc, DefaultSearchLogger, DocumentId, FieldId, Index,
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Result, SearchContext,
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execute_search, filtered_universe, AscDesc, DefaultSearchLogger, DocumentId, Index, Result,
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SearchContext,
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};
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// Building these factories is not free.
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@ -29,9 +19,6 @@ 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 values per facet returned by the facet search route.
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const DEFAULT_MAX_NUMBER_OF_VALUES_PER_FACET: usize = 100;
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pub mod facet;
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mod fst_utils;
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pub mod hybrid;
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@ -304,289 +291,6 @@ pub fn build_dfa(word: &str, typos: u8, is_prefix: bool) -> DFA {
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}
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}
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pub struct SearchForFacetValues<'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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max_values: usize,
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is_hybrid: bool,
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}
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impl<'a> SearchForFacetValues<'a> {
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pub fn new(
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facet: String,
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search_query: Search<'a>,
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is_hybrid: bool,
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) -> SearchForFacetValues<'a> {
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SearchForFacetValues {
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query: None,
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facet,
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search_query,
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max_values: DEFAULT_MAX_NUMBER_OF_VALUES_PER_FACET,
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is_hybrid,
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}
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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 max_values(&mut self, max: usize) -> &mut Self {
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self.max_values = max;
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self
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}
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fn one_original_value_of(
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&self,
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field_id: FieldId,
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facet_str: &str,
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any_docid: DocumentId,
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) -> Result<Option<String>> {
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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 key: (FieldId, _, &str) = (field_id, any_docid, facet_str);
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Ok(index.field_id_docid_facet_strings.get(rtxn, &key)?.map(|v| v.to_owned()))
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}
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pub fn execute(&self) -> Result<Vec<FacetValueHit>> {
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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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let (valid_fields, hidden_fields) =
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index.remove_hidden_fields(rtxn, filterable_fields)?;
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return Err(UserError::InvalidFacetSearchFacetName {
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field: self.facet.clone(),
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valid_fields,
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hidden_fields,
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}
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.into());
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}
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let fields_ids_map = index.fields_ids_map(rtxn)?;
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let fid = match fields_ids_map.id(&self.facet) {
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Some(fid) => fid,
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// we return an empty list of results when the attribute has been
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// set as filterable but no document contains this field (yet).
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None => return Ok(Vec::new()),
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};
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let fst = match self.search_query.index.facet_id_string_fst.get(rtxn, &fid)? {
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Some(fst) => fst,
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None => return Ok(vec![]),
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};
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let search_candidates = self
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.search_query
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.execute_for_candidates(self.is_hybrid || self.search_query.vector.is_some())?;
|
||||
|
||||
let sort_by = index.sort_facet_values_by(rtxn)?.get(&self.facet);
|
||||
|
||||
match self.query.as_ref() {
|
||||
Some(query) => {
|
||||
let options = NormalizerOption { lossy: true, ..Default::default() };
|
||||
let query = query.normalize(&options);
|
||||
let query = query.as_ref();
|
||||
|
||||
let authorize_typos = self.search_query.index.authorize_typos(rtxn)?;
|
||||
let field_authorizes_typos =
|
||||
!self.search_query.index.exact_attributes_ids(rtxn)?.contains(&fid);
|
||||
|
||||
if authorize_typos && field_authorizes_typos {
|
||||
let exact_words_fst = self.search_query.index.exact_words(rtxn)?;
|
||||
if exact_words_fst.map_or(false, |fst| fst.contains(query)) {
|
||||
let mut results = vec![];
|
||||
if fst.contains(query) {
|
||||
self.fetch_original_facets_using_normalized(
|
||||
fid,
|
||||
query,
|
||||
query,
|
||||
&search_candidates,
|
||||
&mut results,
|
||||
)?;
|
||||
}
|
||||
Ok(results)
|
||||
} else {
|
||||
let one_typo = self.search_query.index.min_word_len_one_typo(rtxn)?;
|
||||
let two_typos = self.search_query.index.min_word_len_two_typos(rtxn)?;
|
||||
|
||||
let is_prefix = true;
|
||||
let automaton = if query.len() < one_typo as usize {
|
||||
build_dfa(query, 0, is_prefix)
|
||||
} else if query.len() < two_typos as usize {
|
||||
build_dfa(query, 1, is_prefix)
|
||||
} else {
|
||||
build_dfa(query, 2, is_prefix)
|
||||
};
|
||||
|
||||
let mut stream = fst.search(automaton).into_stream();
|
||||
let mut results = vec![];
|
||||
while let Some(facet_value) = stream.next() {
|
||||
let value = std::str::from_utf8(facet_value)?;
|
||||
if self
|
||||
.fetch_original_facets_using_normalized(
|
||||
fid,
|
||||
value,
|
||||
query,
|
||||
&search_candidates,
|
||||
&mut results,
|
||||
)?
|
||||
.is_break()
|
||||
{
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
Ok(results)
|
||||
}
|
||||
} else {
|
||||
let automaton = Str::new(query).starts_with();
|
||||
let mut stream = fst.search(automaton).into_stream();
|
||||
let mut results = vec![];
|
||||
while let Some(facet_value) = stream.next() {
|
||||
let value = std::str::from_utf8(facet_value)?;
|
||||
if self
|
||||
.fetch_original_facets_using_normalized(
|
||||
fid,
|
||||
value,
|
||||
query,
|
||||
&search_candidates,
|
||||
&mut results,
|
||||
)?
|
||||
.is_break()
|
||||
{
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
Ok(results)
|
||||
}
|
||||
}
|
||||
None => {
|
||||
let prefix = FacetGroupKey { field_id: fid, level: 0, left_bound: "" };
|
||||
|
||||
match sort_by {
|
||||
OrderBy::Lexicographic => {
|
||||
let mut results = vec![];
|
||||
for result in index.facet_id_string_docids.prefix_iter(rtxn, &prefix)? {
|
||||
let (FacetGroupKey { left_bound, .. }, FacetGroupValue { bitmap, .. }) =
|
||||
result?;
|
||||
let count = search_candidates.intersection_len(&bitmap);
|
||||
if count != 0 {
|
||||
let value = self
|
||||
.one_original_value_of(fid, left_bound, bitmap.min().unwrap())?
|
||||
.unwrap_or_else(|| left_bound.to_string());
|
||||
results.push(FacetValueHit { value, count });
|
||||
}
|
||||
if results.len() >= self.max_values {
|
||||
break;
|
||||
}
|
||||
}
|
||||
Ok(results)
|
||||
}
|
||||
OrderBy::Count => {
|
||||
let mut top_counts = BinaryHeap::new();
|
||||
for result in index.facet_id_string_docids.prefix_iter(rtxn, &prefix)? {
|
||||
let (FacetGroupKey { left_bound, .. }, FacetGroupValue { bitmap, .. }) =
|
||||
result?;
|
||||
let count = search_candidates.intersection_len(&bitmap);
|
||||
if count != 0 {
|
||||
let value = self
|
||||
.one_original_value_of(fid, left_bound, bitmap.min().unwrap())?
|
||||
.unwrap_or_else(|| left_bound.to_string());
|
||||
if top_counts.len() >= self.max_values {
|
||||
top_counts.pop();
|
||||
}
|
||||
// It is a max heap and we need to move the smallest counts at the
|
||||
// top to be able to pop them when we reach the max_values limit.
|
||||
top_counts.push(Reverse(FacetValueHit { value, count }));
|
||||
}
|
||||
}
|
||||
|
||||
// Convert the heap into a vec of hits by removing the Reverse wrapper.
|
||||
// Hits are already in the right order as they were reversed and there
|
||||
// are output in ascending order.
|
||||
Ok(top_counts
|
||||
.into_sorted_vec()
|
||||
.into_iter()
|
||||
.map(|Reverse(hit)| hit)
|
||||
.collect())
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
fn fetch_original_facets_using_normalized(
|
||||
&self,
|
||||
fid: FieldId,
|
||||
value: &str,
|
||||
query: &str,
|
||||
search_candidates: &RoaringBitmap,
|
||||
results: &mut Vec<FacetValueHit>,
|
||||
) -> Result<ControlFlow<()>> {
|
||||
let index = self.search_query.index;
|
||||
let rtxn = self.search_query.rtxn;
|
||||
|
||||
let database = index.facet_id_normalized_string_strings;
|
||||
let key = (fid, value);
|
||||
let original_strings = match database.get(rtxn, &key)? {
|
||||
Some(original_strings) => original_strings,
|
||||
None => {
|
||||
error!("the facet value is missing from the facet database: {key:?}");
|
||||
return Ok(ControlFlow::Continue(()));
|
||||
}
|
||||
};
|
||||
for original in original_strings {
|
||||
let key = FacetGroupKey { field_id: fid, level: 0, left_bound: original.as_str() };
|
||||
let docids = match index.facet_id_string_docids.get(rtxn, &key)? {
|
||||
Some(FacetGroupValue { bitmap, .. }) => bitmap,
|
||||
None => {
|
||||
error!("the facet value is missing from the facet database: {key:?}");
|
||||
return Ok(ControlFlow::Continue(()));
|
||||
}
|
||||
};
|
||||
let count = search_candidates.intersection_len(&docids);
|
||||
if count != 0 {
|
||||
let value = self
|
||||
.one_original_value_of(fid, &original, docids.min().unwrap())?
|
||||
.unwrap_or_else(|| query.to_string());
|
||||
results.push(FacetValueHit { value, count });
|
||||
}
|
||||
if results.len() >= self.max_values {
|
||||
return Ok(ControlFlow::Break(()));
|
||||
}
|
||||
}
|
||||
|
||||
Ok(ControlFlow::Continue(()))
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, serde::Serialize, PartialEq)]
|
||||
pub struct FacetValueHit {
|
||||
/// The original facet value
|
||||
pub value: String,
|
||||
/// The number of documents associated to this facet
|
||||
pub count: u64,
|
||||
}
|
||||
|
||||
impl PartialOrd for FacetValueHit {
|
||||
fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
|
||||
Some(self.cmp(other))
|
||||
}
|
||||
}
|
||||
|
||||
impl Ord for FacetValueHit {
|
||||
fn cmp(&self, other: &Self) -> Ordering {
|
||||
self.count.cmp(&other.count).then_with(|| self.value.cmp(&other.value))
|
||||
}
|
||||
}
|
||||
|
||||
impl Eq for FacetValueHit {}
|
||||
|
||||
#[cfg(test)]
|
||||
mod test {
|
||||
#[allow(unused_imports)]
|
||||
|
|
|
|||
Loading…
Reference in New Issue