Merge #3768

3768: Fix bugs in graph-based ranking rules + make `words` a graph-based ranking rule r=dureuill a=loiclec

This PR contains three changes:

## 1. Don't call the `words` ranking rule if the term matching strategy is `All`

This is because the purpose of `words` is only to remove nodes from the query graph. It would never do any useful work when the matching strategy was `All`. Remember that the universe was already computed before by computing all the docids corresponding to the "maximally reduced" query graph, which, in the case of `All`, is equal to the original graph.

## 2. The `words` ranking rule is replaced by a graph-based ranking rule. 

This is for three reasons:

1. **performance**: graph-based ranking rules benefit from a lot of optimisations by default, which ensures that they are never too slow. The previous implementation of `words` could call `compute_query_graph_docids` many times if some words had to be removed from the query, which would be quite expensive. I was especially worried about its performance in cases where it is placed right after the `sort` ranking rule. Furthermore, `compute_query_graph_docids` would clone a lot of bitmaps many times unnecessarily.

2. **consistency**: every other ranking rule (except `sort`) is graph-based. It makes sense to implement `words` like that as well. It will automatically benefit from all the features, optimisations, and bug fixes that all the other ranking rules get.

3. **surfacing bugs**: as the first ranking rule to be called (most of the time), I'd like `words` to behave the same as the other ranking rules so that we can quickly detect bugs in our graph algorithms. This actually already happened, which is why this PR also contains a bug fix.

## 3. Fix the `update_all_costs_before_nodes` function

It is a bit difficult to explain what was wrong, but I'll try. The bug happened when we had graphs like:
<img width="730" alt="Screenshot 2023-05-16 at 10 58 57" src="https://github.com/meilisearch/meilisearch/assets/6040237/40db1a68-d852-4e89-99d5-0d65757242a7">
and we gave the node `is` as argument.

Then, we'd walk backwards from the node breadth-first. We'd update the costs of:
1. `sun`
2. `thesun`
3. `start`
4. `the`

which is an incorrect order. The correct order is:

1. `sun`
2. `thesun`
3. `the`
4. `start`

That is, we can only update the cost of a node when all of its successors have either already been visited or were not affected by the update to the node passed as argument. To solve this bug, I factored out the graph-traversal logic into a `traverse_breadth_first_backward` function.


Co-authored-by: Loïc Lecrenier <loic.lecrenier@me.com>
Co-authored-by: Louis Dureuil <louis@meilisearch.com>

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

@@ -205,18 +205,12 @@ impl<G: RankingRuleGraphTrait> VisitorState<G> {
 impl<G: RankingRuleGraphTrait> RankingRuleGraph<G> {
     pub fn find_all_costs_to_end(&self) -> MappedInterner<QueryNode, Vec<u64>> {
         let mut costs_to_end = self.query_graph.nodes.map(|_| vec![]);
-        let mut enqueued = SmallBitmap::new(self.query_graph.nodes.len());
 
-        let mut node_stack = VecDeque::new();
-
-        *costs_to_end.get_mut(self.query_graph.end_node) = vec![0];
-
-        for prev_node in self.query_graph.nodes.get(self.query_graph.end_node).predecessors.iter() {
-            node_stack.push_back(prev_node);
-            enqueued.insert(prev_node);
-        }
-
-        while let Some(cur_node) = node_stack.pop_front() {
+        self.traverse_breadth_first_backward(self.query_graph.end_node, |cur_node| {
+            if cur_node == self.query_graph.end_node {
+                *costs_to_end.get_mut(self.query_graph.end_node) = vec![0];
+                return;
+            }
             let mut self_costs = Vec::<u64>::new();
 
             let cur_node_edges = &self.edges_of_node.get(cur_node);
@@ -232,13 +226,7 @@ impl<G: RankingRuleGraphTrait> RankingRuleGraph<G> {
             self_costs.dedup();
 
             *costs_to_end.get_mut(cur_node) = self_costs;
-            for prev_node in self.query_graph.nodes.get(cur_node).predecessors.iter() {
-                if !enqueued.contains(prev_node) {
-                    node_stack.push_back(prev_node);
-                    enqueued.insert(prev_node);
-                }
-            }
-        }
+        });
         costs_to_end
     }
 
@@ -247,17 +235,12 @@ impl<G: RankingRuleGraphTrait> RankingRuleGraph<G> {
         node_with_removed_outgoing_conditions: Interned<QueryNode>,
         costs: &mut MappedInterner<QueryNode, Vec<u64>>,
     ) {
-        let mut enqueued = SmallBitmap::new(self.query_graph.nodes.len());
-        let mut node_stack = VecDeque::new();
-
-        enqueued.insert(node_with_removed_outgoing_conditions);
-        node_stack.push_back(node_with_removed_outgoing_conditions);
-
-        'main_loop: while let Some(cur_node) = node_stack.pop_front() {
+        // Traverse the graph backward from the target node, recomputing the cost for each of its predecessors.
+        // We first check that no other node is contributing the same total cost to a predecessor before removing
+        // the cost from the predecessor.
+        self.traverse_breadth_first_backward(node_with_removed_outgoing_conditions, |cur_node| {
             let mut costs_to_remove = FxHashSet::default();
-            for c in costs.get(cur_node) {
-                costs_to_remove.insert(*c);
-            }
+            costs_to_remove.extend(costs.get(cur_node).iter().copied());
 
             let cur_node_edges = &self.edges_of_node.get(cur_node);
             for edge_idx in cur_node_edges.iter() {
@@ -265,22 +248,75 @@ impl<G: RankingRuleGraphTrait> RankingRuleGraph<G> {
                 for cost in costs.get(edge.dest_node).iter() {
                     costs_to_remove.remove(&(*cost + edge.cost as u64));
                     if costs_to_remove.is_empty() {
-                        continue 'main_loop;
+                        return;
                     }
                 }
             }
             if costs_to_remove.is_empty() {
-                continue 'main_loop;
+                return;
             }
             let mut new_costs = BTreeSet::from_iter(costs.get(cur_node).iter().copied());
             for c in costs_to_remove {
                 new_costs.remove(&c);
             }
             *costs.get_mut(cur_node) = new_costs.into_iter().collect();
+        });
+    }
 
+    /// Traverse the graph backwards from the given node such that every time
+    /// a node is visited, we are guaranteed that all its successors either:
+    /// 1. have already been visited; OR
+    /// 2. were not reachable from the given node
+    pub fn traverse_breadth_first_backward(
+        &self,
+        from: Interned<QueryNode>,
+        mut visit: impl FnMut(Interned<QueryNode>),
+    ) {
+        let mut reachable = SmallBitmap::for_interned_values_in(&self.query_graph.nodes);
+        {
+            // go backward to get the set of all reachable nodes from the given node
+            // the nodes that are not reachable will be set as `visited`
+            let mut stack = VecDeque::new();
+            let mut enqueued = SmallBitmap::for_interned_values_in(&self.query_graph.nodes);
+            enqueued.insert(from);
+            stack.push_back(from);
+            while let Some(n) = stack.pop_front() {
+                if reachable.contains(n) {
+                    continue;
+                }
+                reachable.insert(n);
+                for prev_node in self.query_graph.nodes.get(n).predecessors.iter() {
+                    if !enqueued.contains(prev_node) && !reachable.contains(prev_node) {
+                        stack.push_back(prev_node);
+                        enqueued.insert(prev_node);
+                    }
+                }
+            }
+        };
+        let mut unreachable_or_visited =
+            SmallBitmap::for_interned_values_in(&self.query_graph.nodes);
+        for (n, _) in self.query_graph.nodes.iter() {
+            if !reachable.contains(n) {
+                unreachable_or_visited.insert(n);
+            }
+        }
+
+        let mut enqueued = SmallBitmap::for_interned_values_in(&self.query_graph.nodes);
+        let mut stack = VecDeque::new();
+
+        enqueued.insert(from);
+        stack.push_back(from);
+
+        while let Some(cur_node) = stack.pop_front() {
+            if !self.query_graph.nodes.get(cur_node).successors.is_subset(&unreachable_or_visited) {
+                stack.push_back(cur_node);
+                continue;
+            }
+            unreachable_or_visited.insert(cur_node);
+            visit(cur_node);
             for prev_node in self.query_graph.nodes.get(cur_node).predecessors.iter() {
-                if !enqueued.contains(prev_node) {
-                    node_stack.push_back(prev_node);
+                if !enqueued.contains(prev_node) && !unreachable_or_visited.contains(prev_node) {
+                    stack.push_back(prev_node);
                     enqueued.insert(prev_node);
                 }
             }

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

@@ -20,6 +20,8 @@ mod position;
 mod proximity;
 /// Implementation of the `typo` ranking rule
 mod typo;
+/// Implementation of the `words` ranking rule
+mod words;
 
 use std::collections::BTreeSet;
 use std::hash::Hash;
@@ -33,6 +35,7 @@ pub use position::{PositionCondition, PositionGraph};
 pub use proximity::{ProximityCondition, ProximityGraph};
 use roaring::RoaringBitmap;
 pub use typo::{TypoCondition, TypoGraph};
+pub use words::{WordsCondition, WordsGraph};
 
 use super::interner::{DedupInterner, FixedSizeInterner, Interned, MappedInterner};
 use super::query_term::LocatedQueryTermSubset;

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

@@ -50,7 +50,7 @@ impl RankingRuleGraphTrait for TypoGraph {
         // 3-gram -> equivalent to 2 typos
         let base_cost = if term.term_ids.len() == 1 { 0 } else { term.term_ids.len() as u32 };
 
-        for nbr_typos in 0..=term.term_subset.max_nbr_typos(ctx) {
+        for nbr_typos in 0..=term.term_subset.max_typo_cost(ctx) {
             let mut term = term.clone();
             match nbr_typos {
                 0 => {

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

@@ -0,0 +1,49 @@
+use roaring::RoaringBitmap;
+
+use super::{ComputedCondition, RankingRuleGraphTrait};
+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;
+use crate::search::new::SearchContext;
+use crate::Result;
+
+#[derive(Clone, PartialEq, Eq, Hash)]
+pub struct WordsCondition {
+    term: LocatedQueryTermSubset,
+}
+
+pub enum WordsGraph {}
+
+impl RankingRuleGraphTrait for WordsGraph {
+    type Condition = WordsCondition;
+
+    fn resolve_condition(
+        ctx: &mut SearchContext,
+        condition: &Self::Condition,
+        universe: &RoaringBitmap,
+    ) -> Result<ComputedCondition> {
+        let WordsCondition { term, .. } = condition;
+        // maybe compute_query_term_subset_docids should accept a universe as argument
+        let mut docids = compute_query_term_subset_docids(ctx, &term.term_subset)?;
+        docids &= universe;
+
+        Ok(ComputedCondition {
+            docids,
+            universe_len: universe.len(),
+            start_term_subset: None,
+            end_term_subset: term.clone(),
+        })
+    }
+
+    fn build_edges(
+        _ctx: &mut SearchContext,
+        conditions_interner: &mut DedupInterner<Self::Condition>,
+        _from: Option<&LocatedQueryTermSubset>,
+        to_term: &LocatedQueryTermSubset,
+    ) -> Result<Vec<(u32, Interned<Self::Condition>)>> {
+        Ok(vec![(
+            to_term.term_ids.len() as u32,
+            conditions_interner.insert(WordsCondition { term: to_term.clone() }),
+        )])
+    }
+}