Add exactness ranking rules

milli/src/search/new/exact_attribute.rs

@@ -0,0 +1,175 @@
+use heed::BytesDecode;
+use roaring::MultiOps;
+
+use super::query_graph::QueryGraph;
+use super::ranking_rules::{RankingRule, RankingRuleOutput};
+use crate::search::new::query_graph::QueryNodeData;
+use crate::search::new::query_term::ExactTerm;
+use crate::{CboRoaringBitmapCodec, Result, SearchContext, SearchLogger};
+
+/// FIXME:
+///
+/// - A lot of work done in next_bucket that start_iteration could do.
+/// - Consider calling the graph based rule directly from this one.
+/// - currently we did exact term, don't forget about prefix
+/// - some tests
+pub struct ExactAttribute {
+    query_graph: Option<QueryGraph>,
+}
+
+impl ExactAttribute {
+    pub fn new() -> Self {
+        Self { query_graph: None }
+    }
+}
+
+impl<'ctx> RankingRule<'ctx, QueryGraph> for ExactAttribute {
+    fn id(&self) -> String {
+        "exact_attribute".to_owned()
+    }
+
+    fn start_iteration(
+        &mut self,
+        _ctx: &mut SearchContext<'ctx>,
+        _logger: &mut dyn SearchLogger<QueryGraph>,
+        _universe: &roaring::RoaringBitmap,
+        query: &QueryGraph,
+    ) -> Result<()> {
+        self.query_graph = Some(query.clone());
+        Ok(())
+    }
+
+    fn next_bucket(
+        &mut self,
+        ctx: &mut SearchContext<'ctx>,
+        _logger: &mut dyn SearchLogger<QueryGraph>,
+        universe: &roaring::RoaringBitmap,
+    ) -> Result<Option<RankingRuleOutput<QueryGraph>>> {
+        // iterate on the nodes of the graph, retain LocatedQueryTermSubset
+        let query_graph = self.query_graph.as_ref().unwrap();
+        let mut exact_term_position_ids: Vec<(ExactTerm, u16, u8)> =
+            Vec::with_capacity(query_graph.nodes.len() as usize);
+        for (_, node) in query_graph.nodes.iter() {
+            match &node.data {
+                QueryNodeData::Term(term) => {
+                    let exact_term = if let Some(exact_term) = term.term_subset.exact_term(ctx) {
+                        exact_term
+                    } else {
+                        // FIXME: Use `None` or some function indicating that we're passing down the bucket to our child rules
+                        return Ok(Some(RankingRuleOutput {
+                            query: query_graph.clone(),
+                            candidates: universe.clone(),
+                        }));
+                    };
+                    exact_term_position_ids.push((
+                        exact_term,
+                        *term.positions.start(),
+                        *term.term_ids.start(),
+                    ))
+                }
+                QueryNodeData::Deleted | QueryNodeData::Start | QueryNodeData::End => continue,
+            }
+        }
+
+        exact_term_position_ids.sort_by_key(|(_, _, id)| *id);
+        // bail if there is a "hole" (missing word) in remaining query graph
+        let mut previous_id = 0;
+        for (_, _, id) in exact_term_position_ids.iter().copied() {
+            if id < previous_id || id - previous_id > 1 {
+                // FIXME: Use `None` or some function indicating that we're passing down the bucket to our child rules
+                return Ok(Some(RankingRuleOutput {
+                    query: query_graph.clone(),
+                    candidates: universe.clone(),
+                }));
+            } else {
+                previous_id = id;
+            }
+        }
+
+        // sample query: "sunflower are pretty"
+        // sunflower at pos 0 in attr A
+        // are at pos 1 in attr B
+        // pretty at pos 2 in attr C
+        // We want to eliminate such document
+
+        // first check that for each term, there exists some attribute that has this term at the correct position
+        //"word-position-docids";
+        let mut candidates = universe.clone();
+        let words_positions: Vec<(Vec<_>, _)> = exact_term_position_ids
+            .iter()
+            .copied()
+            .map(|(term, position, _)| (term.interned_words(ctx).collect(), position))
+            .collect();
+        for (words, position) in &words_positions {
+            if candidates.is_empty() {
+                // FIXME: Use `None` or some function indicating that we're passing down the bucket to our child rules
+                return Ok(Some(RankingRuleOutput {
+                    query: query_graph.clone(),
+                    candidates: universe.clone(),
+                }));
+            }
+
+            'words: for (offset, word) in words.iter().enumerate() {
+                let offset = offset as u16;
+                let word = if let Some(word) = word {
+                    word
+                } else {
+                    continue 'words;
+                };
+                let word_position_docids = CboRoaringBitmapCodec::bytes_decode(
+                    ctx.get_db_word_position_docids(*word, position + offset)?.unwrap_or_default(),
+                )
+                .unwrap_or_default();
+                candidates &= word_position_docids;
+            }
+        }
+
+        let candidates = candidates;
+
+        if candidates.is_empty() {
+            // FIXME: Use `None` or some function indicating that we're passing down the bucket to our child rules
+            return Ok(Some(RankingRuleOutput {
+                query: query_graph.clone(),
+                candidates: universe.clone(),
+            }));
+        }
+
+        let searchable_fields_ids = ctx.index.searchable_fields_ids(ctx.txn)?.unwrap_or_default();
+
+        let mut candidates_per_attributes = Vec::with_capacity(searchable_fields_ids.len());
+
+        // then check that there exists at least one attribute that has all of the terms
+        for fid in searchable_fields_ids {
+            let mut intersection = MultiOps::intersection(
+                words_positions
+                    .iter()
+                    .flat_map(|(words, ..)| words.iter())
+                    // ignore stop words words in phrases
+                    .flatten()
+                    .map(|word| -> Result<_> {
+                        Ok(ctx
+                            .get_db_word_fid_docids(*word, fid)?
+                            .map(CboRoaringBitmapCodec::bytes_decode)
+                            .unwrap_or_default()
+                            .unwrap_or_default())
+                    }),
+            )?;
+            intersection &= &candidates;
+            if !intersection.is_empty() {
+                candidates_per_attributes.push(intersection);
+            }
+        }
+        // note we could have "false positives" where there both exist different attributes that collectively
+        // have the terms in the correct order and a single attribute that have all the terms, but in the incorrect order.
+
+        let candidates = MultiOps::union(candidates_per_attributes.into_iter());
+        Ok(Some(RankingRuleOutput { query: query_graph.clone(), candidates }))
+    }
+
+    fn end_iteration(
+        &mut self,
+        _ctx: &mut SearchContext<'ctx>,
+        _logger: &mut dyn SearchLogger<QueryGraph>,
+    ) {
+    }
+}