Compute score for the ranking rules

milli/src/search/new/exact_attribute.rs

@@ -2,6 +2,7 @@ use roaring::{MultiOps, RoaringBitmap};
 
 use super::query_graph::QueryGraph;
 use super::ranking_rules::{RankingRule, RankingRuleOutput};
+use crate::score_details::{self, ScoreDetails};
 use crate::search::new::query_graph::QueryNodeData;
 use crate::search::new::query_term::ExactTerm;
 use crate::{Result, SearchContext, SearchLogger};
@@ -244,7 +245,13 @@ impl State {
                 candidates &= universe;
                 (
                     State::AttributeStarts(query_graph.clone(), candidates_per_attribute),
-                    Some(RankingRuleOutput { query: query_graph, candidates }),
+                    Some(RankingRuleOutput {
+                        query: query_graph,
+                        candidates,
+                        score: ScoreDetails::ExactAttribute(
+                            score_details::ExactAttribute::MatchesFull,
+                        ),
+                    }),
                 )
             }
             State::AttributeStarts(query_graph, candidates_per_attribute) => {
@@ -257,12 +264,24 @@ impl State {
                 candidates &= universe;
                 (
                     State::Empty(query_graph.clone()),
-                    Some(RankingRuleOutput { query: query_graph, candidates }),
+                    Some(RankingRuleOutput {
+                        query: query_graph,
+                        candidates,
+                        score: ScoreDetails::ExactAttribute(
+                            score_details::ExactAttribute::MatchesStart,
+                        ),
+                    }),
                 )
             }
             State::Empty(query_graph) => (
                 State::Empty(query_graph.clone()),
-                Some(RankingRuleOutput { query: query_graph, candidates: universe.clone() }),
+                Some(RankingRuleOutput {
+                    query: query_graph,
+                    candidates: universe.clone(),
+                    score: ScoreDetails::ExactAttribute(
+                        score_details::ExactAttribute::NoExactMatch,
+                    ),
+                }),
             ),
         };
         (state, output)

milli/src/search/new/geo_sort.rs

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

milli/src/search/new/graph_based_ranking_rule.rs

@@ -50,6 +50,7 @@ use super::ranking_rule_graph::{
 };
 use super::small_bitmap::SmallBitmap;
 use super::{QueryGraph, RankingRule, RankingRuleOutput, SearchContext};
+use crate::score_details::Rank;
 use crate::search::new::query_term::LocatedQueryTermSubset;
 use crate::search::new::ranking_rule_graph::PathVisitor;
 use crate::{Result, TermsMatchingStrategy};
@@ -118,6 +119,8 @@ pub struct GraphBasedRankingRuleState<G: RankingRuleGraphTrait> {
     all_costs: MappedInterner<QueryNode, Vec<u64>>,
     /// An index in the first element of `all_distances`, giving the cost of the next bucket
     cur_cost: u64,
+    /// One above the highest possible cost for this rule
+    next_max_cost: u64,
 }
 
 impl<'ctx, G: RankingRuleGraphTrait> RankingRule<'ctx, QueryGraph> for GraphBasedRankingRule<G> {
@@ -161,12 +164,16 @@ impl<'ctx, G: RankingRuleGraphTrait> RankingRule<'ctx, QueryGraph> for GraphBase
         // Then pre-compute the cost of all paths from each node to the end node
         let all_costs = graph.find_all_costs_to_end();
 
+        let next_max_cost =
+            all_costs.get(graph.query_graph.root_node).iter().copied().max().unwrap_or(0) + 1;
+
         let state = GraphBasedRankingRuleState {
             graph,
             conditions_cache: condition_docids_cache,
             dead_ends_cache,
             all_costs,
             cur_cost: 0,
+            next_max_cost,
         };
 
         self.state = Some(state);
@@ -180,17 +187,13 @@ impl<'ctx, G: RankingRuleGraphTrait> RankingRule<'ctx, QueryGraph> for GraphBase
         logger: &mut dyn SearchLogger<QueryGraph>,
         universe: &RoaringBitmap,
     ) -> Result<Option<RankingRuleOutput<QueryGraph>>> {
-        // If universe.len() <= 1, the bucket sort algorithm
-        // should not have called this function.
-        assert!(universe.len() > 1);
         // Will crash if `next_bucket` is called before `start_iteration` or after `end_iteration`,
         // should never happen
         let mut state = self.state.take().unwrap();
 
+        let all_costs = state.all_costs.get(state.graph.query_graph.root_node);
         // Retrieve the cost of the paths to compute
-        let Some(&cost) = state
+        let Some(&cost) = all_costs
-            .all_costs
-            .get(state.graph.query_graph.root_node)
             .iter()
             .find(|c| **c >= state.cur_cost) else {
                 self.state = None;
@@ -206,8 +209,12 @@ impl<'ctx, G: RankingRuleGraphTrait> RankingRule<'ctx, QueryGraph> for GraphBase
             dead_ends_cache,
             all_costs,
             cur_cost: _,
+            next_max_cost,
         } = &mut state;
 
+        let rank = *next_max_cost - cost;
+        let score = G::rank_to_score(Rank { rank: rank as u32, max_rank: *next_max_cost as u32 });
+
         let mut universe = universe.clone();
 
         let mut used_conditions = SmallBitmap::for_interned_values_in(&graph.conditions_interner);
@@ -324,7 +331,7 @@ impl<'ctx, G: RankingRuleGraphTrait> RankingRule<'ctx, QueryGraph> for GraphBase
 
         self.state = Some(state);
 
-        Ok(Some(RankingRuleOutput { query: next_query_graph, candidates: bucket }))
+        Ok(Some(RankingRuleOutput { query: next_query_graph, candidates: bucket, score }))
     }
 
     fn end_iteration(

milli/src/search/new/mod.rs

@@ -44,6 +44,7 @@ use self::geo_sort::GeoSort;
 pub use self::geo_sort::Strategy as GeoSortStrategy;
 use self::graph_based_ranking_rule::Words;
 use self::interner::Interned;
+use crate::score_details::ScoreDetails;
 use crate::search::new::distinct::apply_distinct_rule;
 use crate::{AscDesc, DocumentId, Filter, Index, Member, Result, TermsMatchingStrategy, UserError};
 

milli/src/search/new/ranking_rule_graph/exactness/mod.rs

@@ -1,6 +1,7 @@
 use roaring::RoaringBitmap;
 
 use super::{ComputedCondition, RankingRuleGraphTrait};
+use crate::score_details::{Rank, ScoreDetails};
 use crate::search::new::interner::{DedupInterner, Interned};
 use crate::search::new::query_term::{ExactTerm, LocatedQueryTermSubset};
 use crate::search::new::resolve_query_graph::compute_query_term_subset_docids;
@@ -84,4 +85,8 @@ impl RankingRuleGraphTrait for ExactnessGraph {
 
         Ok(vec![(0, exact_condition), (dest_node.term_ids.len() as u32, skip_condition)])
     }
+
+    fn rank_to_score(rank: Rank) -> ScoreDetails {
+        ScoreDetails::Exactness(rank)
+    }
 }

milli/src/search/new/ranking_rule_graph/fid/mod.rs

@@ -2,6 +2,7 @@ use fxhash::FxHashSet;
 use roaring::RoaringBitmap;
 
 use super::{ComputedCondition, RankingRuleGraphTrait};
+use crate::score_details::{Rank, ScoreDetails};
 use crate::search::new::interner::{DedupInterner, Interned};
 use crate::search::new::query_term::LocatedQueryTermSubset;
 use crate::search::new::resolve_query_graph::compute_query_term_subset_docids_within_field_id;
@@ -107,4 +108,8 @@ impl RankingRuleGraphTrait for FidGraph {
 
         Ok(edges)
     }
+
+    fn rank_to_score(rank: Rank) -> ScoreDetails {
+        ScoreDetails::Fid(rank)
+    }
 }

milli/src/search/new/ranking_rule_graph/mod.rs

@@ -41,6 +41,7 @@ use super::interner::{DedupInterner, FixedSizeInterner, Interned, MappedInterner
 use super::query_term::LocatedQueryTermSubset;
 use super::small_bitmap::SmallBitmap;
 use super::{QueryGraph, QueryNode, SearchContext};
+use crate::score_details::{Rank, ScoreDetails};
 use crate::Result;
 
 pub struct ComputedCondition {
@@ -110,6 +111,9 @@ pub trait RankingRuleGraphTrait: Sized + 'static {
         source_node: Option<&LocatedQueryTermSubset>,
         dest_node: &LocatedQueryTermSubset,
     ) -> Result<Vec<(u32, Interned<Self::Condition>)>>;
+
+    /// Convert the rank of a path to its corresponding score for the ranking rule
+    fn rank_to_score(rank: Rank) -> ScoreDetails;
 }
 
 /// The graph used by graph-based ranking rules.

milli/src/search/new/ranking_rule_graph/position/mod.rs

@@ -2,6 +2,7 @@ use fxhash::{FxHashMap, FxHashSet};
 use roaring::RoaringBitmap;
 
 use super::{ComputedCondition, RankingRuleGraphTrait};
+use crate::score_details::{Rank, ScoreDetails};
 use crate::search::new::interner::{DedupInterner, Interned};
 use crate::search::new::query_term::LocatedQueryTermSubset;
 use crate::search::new::resolve_query_graph::compute_query_term_subset_docids_within_position;
@@ -115,6 +116,10 @@ impl RankingRuleGraphTrait for PositionGraph {
 
         Ok(edges)
     }
+
+    fn rank_to_score(rank: Rank) -> ScoreDetails {
+        ScoreDetails::Position(rank)
+    }
 }
 
 fn cost_from_position(sum_positions: u32) -> u32 {

milli/src/search/new/ranking_rule_graph/proximity/mod.rs

@@ -4,6 +4,7 @@ pub mod compute_docids;
 use roaring::RoaringBitmap;
 
 use super::{ComputedCondition, RankingRuleGraphTrait};
+use crate::score_details::{Rank, ScoreDetails};
 use crate::search::new::interner::{DedupInterner, Interned};
 use crate::search::new::query_term::LocatedQueryTermSubset;
 use crate::search::new::SearchContext;
@@ -36,4 +37,8 @@ impl RankingRuleGraphTrait for ProximityGraph {
     ) -> Result<Vec<(u32, Interned<Self::Condition>)>> {
         build::build_edges(ctx, conditions_interner, source_term, dest_term)
     }
+
+    fn rank_to_score(rank: Rank) -> ScoreDetails {
+        ScoreDetails::Proximity(rank)
+    }
 }

milli/src/search/new/ranking_rule_graph/typo/mod.rs

@@ -1,6 +1,7 @@
 use roaring::RoaringBitmap;
 
 use super::{ComputedCondition, RankingRuleGraphTrait};
+use crate::score_details::{self, Rank, ScoreDetails};
 use crate::search::new::interner::{DedupInterner, Interned};
 use crate::search::new::query_term::LocatedQueryTermSubset;
 use crate::search::new::resolve_query_graph::compute_query_term_subset_docids;
@@ -75,4 +76,8 @@ impl RankingRuleGraphTrait for TypoGraph {
         }
         Ok(edges)
     }
+
+    fn rank_to_score(rank: Rank) -> ScoreDetails {
+        ScoreDetails::Typo(score_details::Typo::from_rank(rank))
+    }
 }

milli/src/search/new/ranking_rule_graph/words/mod.rs

@@ -1,6 +1,7 @@
 use roaring::RoaringBitmap;
 
 use super::{ComputedCondition, RankingRuleGraphTrait};
+use crate::score_details::{self, Rank, ScoreDetails};
 use crate::search::new::interner::{DedupInterner, Interned};
 use crate::search::new::query_term::LocatedQueryTermSubset;
 use crate::search::new::resolve_query_graph::compute_query_term_subset_docids;
@@ -43,4 +44,8 @@ impl RankingRuleGraphTrait for WordsGraph {
     ) -> Result<Vec<(u32, Interned<Self::Condition>)>> {
         Ok(vec![(0, conditions_interner.insert(WordsCondition { term: to_term.clone() }))])
     }
+
+    fn rank_to_score(rank: Rank) -> ScoreDetails {
+        ScoreDetails::Words(score_details::Words::from_rank(rank))
+    }
 }

milli/src/search/new/ranking_rules.rs

@@ -2,6 +2,7 @@ use roaring::RoaringBitmap;
 
 use super::logger::SearchLogger;
 use super::{QueryGraph, SearchContext};
+use crate::score_details::ScoreDetails;
 use crate::Result;
 
 /// An internal trait implemented by only [`PlaceholderQuery`] and [`QueryGraph`]
@@ -66,4 +67,6 @@ pub struct RankingRuleOutput<Q> {
     pub query: Q,
     /// The allowed candidates for the child ranking rule
     pub candidates: RoaringBitmap,
+    /// The score for the candidates of the current bucket
+    pub score: ScoreDetails,
 }

milli/src/search/new/sort.rs

@@ -1,9 +1,11 @@
+use heed::BytesDecode;
 use roaring::RoaringBitmap;
 
 use super::logger::SearchLogger;
 use super::{RankingRule, RankingRuleOutput, RankingRuleQueryTrait, SearchContext};
-use crate::heed_codec::facet::FacetGroupKeyCodec;
+use crate::heed_codec::facet::{FacetGroupKeyCodec, OrderedF64Codec};
-use crate::heed_codec::ByteSliceRefCodec;
+use crate::heed_codec::{ByteSliceRefCodec, StrRefCodec};
+use crate::score_details::{self, ScoreDetails};
 use crate::search::facet::{ascending_facet_sort, descending_facet_sort};
 use crate::{FieldId, Index, Result};
 
@@ -118,12 +120,43 @@ impl<'ctx, Query: RankingRuleQueryTrait> RankingRule<'ctx, Query> for Sort<'ctx,
 
                     (itertools::Either::Right(number_iter), itertools::Either::Right(string_iter))
                 };
+                let number_iter = number_iter.map(|r| -> Result<_> {
+                    let (docids, bytes) = r?;
+                    Ok((
+                        docids,
+                        serde_json::Value::Number(
+                            serde_json::Number::from_f64(
+                                OrderedF64Codec::bytes_decode(bytes).expect("some number"),
+                            )
+                            .expect("too big float"),
+                        ),
+                    ))
+                });
+                let string_iter = string_iter.map(|r| -> Result<_> {
+                    let (docids, bytes) = r?;
+                    Ok((
+                        docids,
+                        serde_json::Value::String(
+                            StrRefCodec::bytes_decode(bytes).expect("some string").to_owned(),
+                        ),
+                    ))
+                });
 
                 let query_graph = parent_query.clone();
+                let ascending = self.is_ascending;
+                let field_name = self.field_name.clone();
                 RankingRuleOutputIterWrapper::new(Box::new(number_iter.chain(string_iter).map(
                     move |r| {
-                        let (docids, _) = r?;
+                        let (docids, value) = r?;
-                        Ok(RankingRuleOutput { query: query_graph.clone(), candidates: docids })
+                        Ok(RankingRuleOutput {
+                            query: query_graph.clone(),
+                            candidates: docids,
+                            score: ScoreDetails::Sort(score_details::Sort {
+                                field_name: field_name.clone(),
+                                ascending,
+                                value,
+                            }),
+                        })
                     },
                 )))
             }
@@ -150,7 +183,15 @@ impl<'ctx, Query: RankingRuleQueryTrait> RankingRule<'ctx, Query> for Sort<'ctx,
             Ok(Some(bucket))
         } else {
             let query = self.original_query.as_ref().unwrap().clone();
-            Ok(Some(RankingRuleOutput { query, candidates: universe.clone() }))
+            Ok(Some(RankingRuleOutput {
+                query,
+                candidates: universe.clone(),
+                score: ScoreDetails::Sort(score_details::Sort {
+                    field_name: self.field_name.clone(),
+                    ascending: self.is_ascending,
+                    value: serde_json::Value::Null,
+                }),
+            }))
         }
     }