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https://github.com/meilisearch/MeiliSearch
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Score for geosort
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parent
2ea8194c18
commit
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@ -8,6 +8,7 @@ use rstar::RTree;
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use super::ranking_rules::{RankingRule, RankingRuleOutput, RankingRuleQueryTrait};
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use crate::heed_codec::facet::{FieldDocIdFacetCodec, OrderedF64Codec};
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use crate::score_details::{self, ScoreDetails};
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use crate::{
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distance_between_two_points, lat_lng_to_xyz, GeoPoint, Index, Result, SearchContext,
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SearchLogger,
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@ -80,7 +81,7 @@ pub struct GeoSort<Q: RankingRuleQueryTrait> {
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field_ids: Option<[u16; 2]>,
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rtree: Option<RTree<GeoPoint>>,
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cached_sorted_docids: VecDeque<u32>,
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cached_sorted_docids: VecDeque<(u32, [f64; 2])>,
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geo_candidates: RoaringBitmap,
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}
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@ -130,7 +131,7 @@ impl<Q: RankingRuleQueryTrait> GeoSort<Q> {
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let point = lat_lng_to_xyz(&self.point);
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for point in rtree.nearest_neighbor_iter(&point) {
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if self.geo_candidates.contains(point.data.0) {
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self.cached_sorted_docids.push_back(point.data.0);
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self.cached_sorted_docids.push_back(point.data);
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if self.cached_sorted_docids.len() >= cache_size {
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break;
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}
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@ -142,7 +143,7 @@ impl<Q: RankingRuleQueryTrait> GeoSort<Q> {
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let point = lat_lng_to_xyz(&opposite_of(self.point));
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for point in rtree.nearest_neighbor_iter(&point) {
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if self.geo_candidates.contains(point.data.0) {
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self.cached_sorted_docids.push_front(point.data.0);
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self.cached_sorted_docids.push_front(point.data);
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if self.cached_sorted_docids.len() >= cache_size {
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break;
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}
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@ -177,7 +178,7 @@ impl<Q: RankingRuleQueryTrait> GeoSort<Q> {
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// computing the distance between two points is expensive thus we cache the result
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documents
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.sort_by_cached_key(|(_, p)| distance_between_two_points(&self.point, p) as usize);
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self.cached_sorted_docids.extend(documents.into_iter().map(|(doc_id, _)| doc_id));
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self.cached_sorted_docids.extend(documents.into_iter());
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};
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Ok(())
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@ -220,12 +221,19 @@ impl<'ctx, Q: RankingRuleQueryTrait> RankingRule<'ctx, Q> for GeoSort<Q> {
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logger: &mut dyn SearchLogger<Q>,
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universe: &RoaringBitmap,
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) -> Result<Option<RankingRuleOutput<Q>>> {
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assert!(universe.len() > 1);
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let query = self.query.as_ref().unwrap().clone();
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self.geo_candidates &= universe;
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if self.geo_candidates.is_empty() {
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return Ok(Some(RankingRuleOutput { query, candidates: universe.clone() }));
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return Ok(Some(RankingRuleOutput {
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query,
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candidates: universe.clone(),
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score: ScoreDetails::GeoSort(score_details::GeoSort {
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target_point: self.point,
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ascending: self.ascending,
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value: None,
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}),
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}));
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}
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let ascending = self.ascending;
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@ -236,11 +244,16 @@ impl<'ctx, Q: RankingRuleQueryTrait> RankingRule<'ctx, Q> for GeoSort<Q> {
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cache.pop_back()
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}
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};
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while let Some(id) = next(&mut self.cached_sorted_docids) {
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while let Some((id, point)) = next(&mut self.cached_sorted_docids) {
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if self.geo_candidates.contains(id) {
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return Ok(Some(RankingRuleOutput {
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query,
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candidates: RoaringBitmap::from_iter([id]),
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score: ScoreDetails::GeoSort(score_details::GeoSort {
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target_point: self.point,
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ascending: self.ascending,
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value: Some(point),
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}),
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}));
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}
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}
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