Merge #4466

4466: Implements the search cutoff r=irevoire a=irevoire

# Pull Request

## Related issue
Fixes https://github.com/meilisearch/meilisearch/issues/4488

## What does this PR do?
- Adds a cutoff to the bucket sort after 150ms has been spent
- Adds a new setting to customize the default value of 150ms
- When the time is exceeded, we exit early with what we had the time to sort
- If the cutoff has been reached, the search details are updated with a new `Skip` ranking details for the ranking rules that were skipped
- Adds analytics to measure the total number of degraded search requests
- Adds the number of degraded search requests to the Prometheus metrics and Grafana dashboard
- The cutoff **must not** skip the filters; otherwise, we would leak documents to people who don’t have the right to see them


Co-authored-by: Tamo <tamo@meilisearch.com>
Co-authored-by: Louis Dureuil <louis@meilisearch.com>

milli/examples/search.rs

@@ -6,7 +6,7 @@ use std::time::Instant;
 use heed::EnvOpenOptions;
 use milli::{
     execute_search, filtered_universe, DefaultSearchLogger, GeoSortStrategy, Index, SearchContext,
-    SearchLogger, TermsMatchingStrategy,
+    SearchLogger, TermsMatchingStrategy, TimeBudget,
 };
 
 #[global_allocator]
@@ -65,6 +65,7 @@ fn main() -> Result<(), Box<dyn Error>> {
                 None,
                 &mut DefaultSearchLogger,
                 logger,
+                TimeBudget::max(),
             )?;
             if let Some((logger, dir)) = detailed_logger {
                 logger.finish(&mut ctx, Path::new(dir))?;

milli/src/index.rs

@@ -67,6 +67,7 @@ pub mod main_key {
     pub const PAGINATION_MAX_TOTAL_HITS: &str = "pagination-max-total-hits";
     pub const PROXIMITY_PRECISION: &str = "proximity-precision";
     pub const EMBEDDING_CONFIGS: &str = "embedding_configs";
+    pub const SEARCH_CUTOFF: &str = "search_cutoff";
 }
 
 pub mod db_name {
@@ -1505,6 +1506,18 @@ impl Index {
             _ => "default".to_owned(),
         })
     }
+
+    pub(crate) fn put_search_cutoff(&self, wtxn: &mut RwTxn<'_>, cutoff: u64) -> heed::Result<()> {
+        self.main.remap_types::<Str, BEU64>().put(wtxn, main_key::SEARCH_CUTOFF, &cutoff)
+    }
+
+    pub fn search_cutoff(&self, rtxn: &RoTxn<'_>) -> Result<Option<u64>> {
+        Ok(self.main.remap_types::<Str, BEU64>().get(rtxn, main_key::SEARCH_CUTOFF)?)
+    }
+
+    pub(crate) fn delete_search_cutoff(&self, wtxn: &mut RwTxn<'_>) -> heed::Result<bool> {
+        self.main.remap_key_type::<Str>().delete(wtxn, main_key::SEARCH_CUTOFF)
+    }
 }
 
 #[cfg(test)]
@@ -2421,6 +2434,7 @@ pub(crate) mod tests {
             candidates: _,
             document_scores: _,
             mut documents_ids,
+            degraded: _,
         } = search.execute().unwrap();
         let primary_key_id = index.fields_ids_map(&rtxn).unwrap().id("primary_key").unwrap();
         documents_ids.sort_unstable();

milli/src/lib.rs

@@ -30,6 +30,7 @@ pub mod snapshot_tests;
 
 use std::collections::{BTreeMap, HashMap};
 use std::convert::{TryFrom, TryInto};
+use std::fmt;
 use std::hash::BuildHasherDefault;
 
 use charabia::normalizer::{CharNormalizer, CompatibilityDecompositionNormalizer};
@@ -104,6 +105,73 @@ pub const MAX_WORD_LENGTH: usize = MAX_LMDB_KEY_LENGTH / 2;
 
 pub const MAX_POSITION_PER_ATTRIBUTE: u32 = u16::MAX as u32 + 1;
 
+#[derive(Clone)]
+pub struct TimeBudget {
+    started_at: std::time::Instant,
+    budget: std::time::Duration,
+
+    /// When testing the time budget, ensuring we did more than iteration of the bucket sort can be useful.
+    /// But to avoid being flaky, the only option is to add the ability to stop after a specific number of calls instead of a `Duration`.
+    #[cfg(test)]
+    stop_after: Option<(std::sync::Arc<std::sync::atomic::AtomicUsize>, usize)>,
+}
+
+impl fmt::Debug for TimeBudget {
+    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+        f.debug_struct("TimeBudget")
+            .field("started_at", &self.started_at)
+            .field("budget", &self.budget)
+            .field("left", &(self.budget - self.started_at.elapsed()))
+            .finish()
+    }
+}
+
+impl Default for TimeBudget {
+    fn default() -> Self {
+        Self::new(std::time::Duration::from_millis(150))
+    }
+}
+
+impl TimeBudget {
+    pub fn new(budget: std::time::Duration) -> Self {
+        Self {
+            started_at: std::time::Instant::now(),
+            budget,
+
+            #[cfg(test)]
+            stop_after: None,
+        }
+    }
+
+    pub fn max() -> Self {
+        Self::new(std::time::Duration::from_secs(u64::MAX))
+    }
+
+    #[cfg(test)]
+    pub fn with_stop_after(mut self, stop_after: usize) -> Self {
+        use std::sync::atomic::AtomicUsize;
+        use std::sync::Arc;
+
+        self.stop_after = Some((Arc::new(AtomicUsize::new(0)), stop_after));
+        self
+    }
+
+    pub fn exceeded(&self) -> bool {
+        #[cfg(test)]
+        if let Some((current, stop_after)) = &self.stop_after {
+            let current = current.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
+            if current >= *stop_after {
+                return true;
+            } else {
+                // if a number has been specified then we ignore entirely the time budget
+                return false;
+            }
+        }
+
+        self.started_at.elapsed() > self.budget
+    }
+}
+
 // Convert an absolute word position into a relative position.
 // Return the field id of the attribute related to the absolute position
 // and the relative position in the attribute.

milli/src/score_details.rs

@@ -17,6 +17,9 @@ pub enum ScoreDetails {
     Sort(Sort),
     Vector(Vector),
     GeoSort(GeoSort),
+
+    /// Returned when we don't have the time to finish applying all the subsequent ranking-rules
+    Skipped,
 }
 
 #[derive(Clone, Copy)]
@@ -50,6 +53,7 @@ impl ScoreDetails {
             ScoreDetails::Sort(_) => None,
             ScoreDetails::GeoSort(_) => None,
             ScoreDetails::Vector(_) => None,
+            ScoreDetails::Skipped => Some(Rank { rank: 0, max_rank: 1 }),
         }
     }
 
@@ -97,6 +101,7 @@ impl ScoreDetails {
             ScoreDetails::Vector(vector) => RankOrValue::Score(
                 vector.value_similarity.as_ref().map(|(_, s)| *s as f64).unwrap_or(0.0f64),
             ),
+            ScoreDetails::Skipped => RankOrValue::Rank(Rank { rank: 0, max_rank: 1 }),
         }
     }
 
@@ -256,6 +261,11 @@ impl ScoreDetails {
                     details_map.insert(vector, details);
                     order += 1;
                 }
+                ScoreDetails::Skipped => {
+                    details_map
+                        .insert("skipped".to_string(), serde_json::json!({ "order": order }));
+                    order += 1;
+                }
             }
         }
         details_map

milli/src/search/hybrid.rs

@@ -10,6 +10,7 @@ struct ScoreWithRatioResult {
     matching_words: MatchingWords,
     candidates: RoaringBitmap,
     document_scores: Vec<(u32, ScoreWithRatio)>,
+    degraded: bool,
 }
 
 type ScoreWithRatio = (Vec<ScoreDetails>, f32);
@@ -49,8 +50,12 @@ fn compare_scores(
                     order => return order,
                 }
             }
-            (Some(ScoreValue::Score(_)), Some(_)) => return Ordering::Greater,
-            (Some(_), Some(ScoreValue::Score(_))) => return Ordering::Less,
+            (Some(ScoreValue::Score(x)), Some(_)) => {
+                return if x == 0. { Ordering::Less } else { Ordering::Greater }
+            }
+            (Some(_), Some(ScoreValue::Score(x))) => {
+                return if x == 0. { Ordering::Greater } else { Ordering::Less }
+            }
             // if we have this, we're bad
             (Some(ScoreValue::GeoSort(_)), Some(ScoreValue::Sort(_)))
             | (Some(ScoreValue::Sort(_)), Some(ScoreValue::GeoSort(_))) => {
@@ -72,6 +77,7 @@ impl ScoreWithRatioResult {
             matching_words: results.matching_words,
             candidates: results.candidates,
             document_scores,
+            degraded: results.degraded,
         }
     }
 
@@ -106,6 +112,7 @@ impl ScoreWithRatioResult {
             candidates: left.candidates | right.candidates,
             documents_ids,
             document_scores,
+            degraded: left.degraded | right.degraded,
         }
     }
 }
@@ -131,6 +138,7 @@ impl<'a> Search<'a> {
             index: self.index,
             distribution_shift: self.distribution_shift,
             embedder_name: self.embedder_name.clone(),
+            time_budget: self.time_budget.clone(),
         };
 
         let vector_query = search.vector.take();

milli/src/search/mod.rs

@@ -11,7 +11,7 @@ use crate::score_details::{ScoreDetails, ScoringStrategy};
 use crate::vector::DistributionShift;
 use crate::{
     execute_search, filtered_universe, AscDesc, DefaultSearchLogger, DocumentId, Index, Result,
-    SearchContext,
+    SearchContext, TimeBudget,
 };
 
 // Building these factories is not free.
@@ -43,6 +43,8 @@ pub struct Search<'a> {
     index: &'a Index,
     distribution_shift: Option<DistributionShift>,
     embedder_name: Option<String>,
+
+    time_budget: TimeBudget,
 }
 
 impl<'a> Search<'a> {
@@ -64,6 +66,7 @@ impl<'a> Search<'a> {
             index,
             distribution_shift: None,
             embedder_name: None,
+            time_budget: TimeBudget::max(),
         }
     }
 
@@ -143,6 +146,11 @@ impl<'a> Search<'a> {
         self
     }
 
+    pub fn time_budget(&mut self, time_budget: TimeBudget) -> &mut Search<'a> {
+        self.time_budget = time_budget;
+        self
+    }
+
     pub fn execute_for_candidates(&self, has_vector_search: bool) -> Result<RoaringBitmap> {
         if has_vector_search {
             let ctx = SearchContext::new(self.index, self.rtxn);
@@ -169,36 +177,43 @@ impl<'a> Search<'a> {
         }
 
         let universe = filtered_universe(&ctx, &self.filter)?;
-        let PartialSearchResult { located_query_terms, candidates, documents_ids, document_scores } =
-            match self.vector.as_ref() {
-                Some(vector) => execute_vector_search(
-                    &mut ctx,
-                    vector,
-                    self.scoring_strategy,
-                    universe,
-                    &self.sort_criteria,
-                    self.geo_strategy,
-                    self.offset,
-                    self.limit,
-                    self.distribution_shift,
-                    embedder_name,
-                )?,
-                None => execute_search(
-                    &mut ctx,
-                    self.query.as_deref(),
-                    self.terms_matching_strategy,
-                    self.scoring_strategy,
-                    self.exhaustive_number_hits,
-                    universe,
-                    &self.sort_criteria,
-                    self.geo_strategy,
-                    self.offset,
-                    self.limit,
-                    Some(self.words_limit),
-                    &mut DefaultSearchLogger,
-                    &mut DefaultSearchLogger,
-                )?,
-            };
+        let PartialSearchResult {
+            located_query_terms,
+            candidates,
+            documents_ids,
+            document_scores,
+            degraded,
+        } = match self.vector.as_ref() {
+            Some(vector) => execute_vector_search(
+                &mut ctx,
+                vector,
+                self.scoring_strategy,
+                universe,
+                &self.sort_criteria,
+                self.geo_strategy,
+                self.offset,
+                self.limit,
+                self.distribution_shift,
+                embedder_name,
+                self.time_budget.clone(),
+            )?,
+            None => execute_search(
+                &mut ctx,
+                self.query.as_deref(),
+                self.terms_matching_strategy,
+                self.scoring_strategy,
+                self.exhaustive_number_hits,
+                universe,
+                &self.sort_criteria,
+                self.geo_strategy,
+                self.offset,
+                self.limit,
+                Some(self.words_limit),
+                &mut DefaultSearchLogger,
+                &mut DefaultSearchLogger,
+                self.time_budget.clone(),
+            )?,
+        };
 
         // consume context and located_query_terms to build MatchingWords.
         let matching_words = match located_query_terms {
@@ -206,7 +221,7 @@ impl<'a> Search<'a> {
             None => MatchingWords::default(),
         };
 
-        Ok(SearchResult { matching_words, candidates, document_scores, documents_ids })
+        Ok(SearchResult { matching_words, candidates, document_scores, documents_ids, degraded })
     }
 }
 
@@ -229,6 +244,7 @@ impl fmt::Debug for Search<'_> {
             index: _,
             distribution_shift,
             embedder_name,
+            time_budget,
         } = self;
         f.debug_struct("Search")
             .field("query", query)
@@ -244,6 +260,7 @@ impl fmt::Debug for Search<'_> {
             .field("words_limit", words_limit)
             .field("distribution_shift", distribution_shift)
             .field("embedder_name", embedder_name)
+            .field("time_budget", time_budget)
             .finish()
     }
 }
@@ -254,6 +271,7 @@ pub struct SearchResult {
     pub candidates: RoaringBitmap,
     pub documents_ids: Vec<DocumentId>,
     pub document_scores: Vec<Vec<ScoreDetails>>,
+    pub degraded: bool,
 }
 
 #[derive(Debug, Clone, Copy, PartialEq, Eq)]

milli/src/search/new/bucket_sort.rs

@@ -5,12 +5,14 @@ use super::ranking_rules::{BoxRankingRule, RankingRuleQueryTrait};
 use super::SearchContext;
 use crate::score_details::{ScoreDetails, ScoringStrategy};
 use crate::search::new::distinct::{apply_distinct_rule, distinct_single_docid, DistinctOutput};
-use crate::Result;
+use crate::{Result, TimeBudget};
 
 pub struct BucketSortOutput {
     pub docids: Vec<u32>,
     pub scores: Vec<Vec<ScoreDetails>>,
     pub all_candidates: RoaringBitmap,
+
+    pub degraded: bool,
 }
 
 // TODO: would probably be good to regroup some of these inside of a struct?
@@ -25,6 +27,7 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
     length: usize,
     scoring_strategy: ScoringStrategy,
     logger: &mut dyn SearchLogger<Q>,
+    time_budget: TimeBudget,
 ) -> Result<BucketSortOutput> {
     logger.initial_query(query);
     logger.ranking_rules(&ranking_rules);
@@ -41,6 +44,7 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
             docids: vec![],
             scores: vec![],
             all_candidates: universe.clone(),
+            degraded: false,
         });
     }
     if ranking_rules.is_empty() {
@@ -74,6 +78,7 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
                 scores: vec![Default::default(); results.len()],
                 docids: results,
                 all_candidates,
+                degraded: false,
             });
         } else {
             let docids: Vec<u32> = universe.iter().skip(from).take(length).collect();
@@ -81,6 +86,7 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
                 scores: vec![Default::default(); docids.len()],
                 docids,
                 all_candidates: universe.clone(),
+                degraded: false,
             });
         };
     }
@@ -154,6 +160,28 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
     }
 
     while valid_docids.len() < length {
+        if time_budget.exceeded() {
+            loop {
+                let bucket = std::mem::take(&mut ranking_rule_universes[cur_ranking_rule_index]);
+                ranking_rule_scores.push(ScoreDetails::Skipped);
+                maybe_add_to_results!(bucket);
+                ranking_rule_scores.pop();
+
+                if cur_ranking_rule_index == 0 {
+                    break;
+                }
+
+                back!();
+            }
+
+            return Ok(BucketSortOutput {
+                scores: valid_scores,
+                docids: valid_docids,
+                all_candidates,
+                degraded: true,
+            });
+        }
+
         // The universe for this bucket is zero, so we don't need to sort
         // anything, just go back to the parent ranking rule.
         if ranking_rule_universes[cur_ranking_rule_index].is_empty()
@@ -219,7 +247,12 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
         )?;
     }
 
-    Ok(BucketSortOutput { docids: valid_docids, scores: valid_scores, all_candidates })
+    Ok(BucketSortOutput {
+        docids: valid_docids,
+        scores: valid_scores,
+        all_candidates,
+        degraded: false,
+    })
 }
 
 /// Add the candidates to the results. Take `distinct`, `from`, `length`, and `cur_offset`

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

@@ -502,7 +502,7 @@ mod tests {
 
     use super::*;
     use crate::index::tests::TempIndex;
-    use crate::{execute_search, filtered_universe, SearchContext};
+    use crate::{execute_search, filtered_universe, SearchContext, TimeBudget};
 
     impl<'a> MatcherBuilder<'a> {
         fn new_test(rtxn: &'a heed::RoTxn, index: &'a TempIndex, query: &str) -> Self {
@@ -522,6 +522,7 @@ mod tests {
                 Some(10),
                 &mut crate::DefaultSearchLogger,
                 &mut crate::DefaultSearchLogger,
+                TimeBudget::max(),
             )
             .unwrap();
 

milli/src/search/new/mod.rs

@@ -52,7 +52,8 @@ use crate::score_details::{ScoreDetails, ScoringStrategy};
 use crate::search::new::distinct::apply_distinct_rule;
 use crate::vector::DistributionShift;
 use crate::{
-    AscDesc, DocumentId, FieldId, Filter, Index, Member, Result, TermsMatchingStrategy, UserError,
+    AscDesc, DocumentId, FieldId, Filter, Index, Member, Result, TermsMatchingStrategy, TimeBudget,
+    UserError,
 };
 
 /// A structure used throughout the execution of a search query.
@@ -518,6 +519,7 @@ pub fn execute_vector_search(
     length: usize,
     distribution_shift: Option<DistributionShift>,
     embedder_name: &str,
+    time_budget: TimeBudget,
 ) -> Result<PartialSearchResult> {
     check_sort_criteria(ctx, sort_criteria.as_ref())?;
 
@@ -537,7 +539,7 @@ pub fn execute_vector_search(
     let placeholder_search_logger: &mut dyn SearchLogger<PlaceholderQuery> =
         &mut placeholder_search_logger;
 
-    let BucketSortOutput { docids, scores, all_candidates } = bucket_sort(
+    let BucketSortOutput { docids, scores, all_candidates, degraded } = bucket_sort(
         ctx,
         ranking_rules,
         &PlaceholderQuery,
@@ -546,6 +548,7 @@ pub fn execute_vector_search(
         length,
         scoring_strategy,
         placeholder_search_logger,
+        time_budget,
     )?;
 
     Ok(PartialSearchResult {
@@ -553,6 +556,7 @@ pub fn execute_vector_search(
         document_scores: scores,
         documents_ids: docids,
         located_query_terms: None,
+        degraded,
     })
 }
 
@@ -572,6 +576,7 @@ pub fn execute_search(
     words_limit: Option<usize>,
     placeholder_search_logger: &mut dyn SearchLogger<PlaceholderQuery>,
     query_graph_logger: &mut dyn SearchLogger<QueryGraph>,
+    time_budget: TimeBudget,
 ) -> Result<PartialSearchResult> {
     check_sort_criteria(ctx, sort_criteria.as_ref())?;
 
@@ -648,6 +653,7 @@ pub fn execute_search(
             length,
             scoring_strategy,
             query_graph_logger,
+            time_budget,
         )?
     } else {
         let ranking_rules =
@@ -661,10 +667,11 @@ pub fn execute_search(
             length,
             scoring_strategy,
             placeholder_search_logger,
+            time_budget,
         )?
     };
 
-    let BucketSortOutput { docids, scores, mut all_candidates } = bucket_sort_output;
+    let BucketSortOutput { docids, scores, mut all_candidates, degraded } = bucket_sort_output;
     let fields_ids_map = ctx.index.fields_ids_map(ctx.txn)?;
 
     // The candidates is the universe unless the exhaustive number of hits
@@ -682,6 +689,7 @@ pub fn execute_search(
         document_scores: scores,
         documents_ids: docids,
         located_query_terms,
+        degraded,
     })
 }
 
@@ -742,4 +750,6 @@ pub struct PartialSearchResult {
     pub candidates: RoaringBitmap,
     pub documents_ids: Vec<DocumentId>,
     pub document_scores: Vec<Vec<ScoreDetails>>,
+
+    pub degraded: bool,
 }

milli/src/search/new/tests/cutoff.rs

@@ -0,0 +1,429 @@
+//! This module test the search cutoff and ensure a few things:
+//! 1. A basic test works and mark the search as degraded
+//! 2. A test that ensure the filters are affectively applied even with a cutoff of 0
+//! 3. A test that ensure the cutoff works well with the ranking scores
+
+use std::time::Duration;
+
+use big_s::S;
+use maplit::hashset;
+use meili_snap::snapshot;
+
+use crate::index::tests::TempIndex;
+use crate::score_details::{ScoreDetails, ScoringStrategy};
+use crate::{Criterion, Filter, Search, TimeBudget};
+
+fn create_index() -> TempIndex {
+    let index = TempIndex::new();
+
+    index
+        .update_settings(|s| {
+            s.set_primary_key("id".to_owned());
+            s.set_searchable_fields(vec!["text".to_owned()]);
+            s.set_filterable_fields(hashset! { S("id") });
+            s.set_criteria(vec![Criterion::Words, Criterion::Typo]);
+        })
+        .unwrap();
+
+    // reverse the ID / insertion order so we see better what was sorted from what got the insertion order ordering
+    index
+        .add_documents(documents!([
+            {
+                "id": 4,
+                "text": "hella puppo kefir",
+            },
+            {
+                "id": 3,
+                "text": "hella puppy kefir",
+            },
+            {
+                "id": 2,
+                "text": "hello",
+            },
+            {
+                "id": 1,
+                "text": "hello puppy",
+            },
+            {
+                "id": 0,
+                "text": "hello puppy kefir",
+            },
+        ]))
+        .unwrap();
+    index
+}
+
+#[test]
+fn basic_degraded_search() {
+    let index = create_index();
+    let rtxn = index.read_txn().unwrap();
+
+    let mut search = Search::new(&rtxn, &index);
+    search.query("hello puppy kefir");
+    search.limit(3);
+    search.time_budget(TimeBudget::new(Duration::from_millis(0)));
+
+    let result = search.execute().unwrap();
+    assert!(result.degraded);
+}
+
+#[test]
+fn degraded_search_cannot_skip_filter() {
+    let index = create_index();
+    let rtxn = index.read_txn().unwrap();
+
+    let mut search = Search::new(&rtxn, &index);
+    search.query("hello puppy kefir");
+    search.limit(100);
+    search.time_budget(TimeBudget::new(Duration::from_millis(0)));
+    let filter_condition = Filter::from_str("id > 2").unwrap().unwrap();
+    search.filter(filter_condition);
+
+    let result = search.execute().unwrap();
+    assert!(result.degraded);
+    snapshot!(format!("{:?}\n{:?}", result.candidates, result.documents_ids), @r###"
+    RoaringBitmap<[0, 1]>
+    [0, 1]
+    "###);
+}
+
+#[test]
+#[allow(clippy::format_collect)] // the test is already quite big
+fn degraded_search_and_score_details() {
+    let index = create_index();
+    let rtxn = index.read_txn().unwrap();
+
+    let mut search = Search::new(&rtxn, &index);
+    search.query("hello puppy kefir");
+    search.limit(4);
+    search.scoring_strategy(ScoringStrategy::Detailed);
+    search.time_budget(TimeBudget::max());
+
+    let result = search.execute().unwrap();
+    snapshot!(format!("IDs: {:?}\nScores: {}\nScore Details:\n{:#?}", result.documents_ids, result.document_scores.iter().map(|scores| format!("{:.4} ", ScoreDetails::global_score(scores.iter()))).collect::<String>(), result.document_scores), @r###"
+    IDs: [4, 1, 0, 3]
+    Scores: 1.0000 0.9167 0.8333 0.6667 
+    Score Details:
+    [
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Typo(
+                Typo {
+                    typo_count: 0,
+                    max_typo_count: 3,
+                },
+            ),
+        ],
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Typo(
+                Typo {
+                    typo_count: 1,
+                    max_typo_count: 3,
+                },
+            ),
+        ],
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Typo(
+                Typo {
+                    typo_count: 2,
+                    max_typo_count: 3,
+                },
+            ),
+        ],
+        [
+            Words(
+                Words {
+                    matching_words: 2,
+                    max_matching_words: 3,
+                },
+            ),
+            Typo(
+                Typo {
+                    typo_count: 0,
+                    max_typo_count: 2,
+                },
+            ),
+        ],
+    ]
+    "###);
+
+    // Do ONE loop iteration. Not much can be deduced, almost everyone matched the words first bucket.
+    search.time_budget(TimeBudget::max().with_stop_after(1));
+
+    let result = search.execute().unwrap();
+    snapshot!(format!("IDs: {:?}\nScores: {}\nScore Details:\n{:#?}", result.documents_ids, result.document_scores.iter().map(|scores| format!("{:.4} ", ScoreDetails::global_score(scores.iter()))).collect::<String>(), result.document_scores), @r###"
+    IDs: [0, 1, 4, 2]
+    Scores: 0.6667 0.6667 0.6667 0.0000 
+    Score Details:
+    [
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Skipped,
+        ],
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Skipped,
+        ],
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Skipped,
+        ],
+        [
+            Skipped,
+        ],
+    ]
+    "###);
+
+    // Do TWO loop iterations. The first document should be entirely sorted
+    search.time_budget(TimeBudget::max().with_stop_after(2));
+
+    let result = search.execute().unwrap();
+    snapshot!(format!("IDs: {:?}\nScores: {}\nScore Details:\n{:#?}", result.documents_ids, result.document_scores.iter().map(|scores| format!("{:.4} ", ScoreDetails::global_score(scores.iter()))).collect::<String>(), result.document_scores), @r###"
+    IDs: [4, 0, 1, 2]
+    Scores: 1.0000 0.6667 0.6667 0.0000 
+    Score Details:
+    [
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Typo(
+                Typo {
+                    typo_count: 0,
+                    max_typo_count: 3,
+                },
+            ),
+        ],
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Skipped,
+        ],
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Skipped,
+        ],
+        [
+            Skipped,
+        ],
+    ]
+    "###);
+
+    // Do THREE loop iterations. The second document should be entirely sorted as well
+    search.time_budget(TimeBudget::max().with_stop_after(3));
+
+    let result = search.execute().unwrap();
+    snapshot!(format!("IDs: {:?}\nScores: {}\nScore Details:\n{:#?}", result.documents_ids, result.document_scores.iter().map(|scores| format!("{:.4} ", ScoreDetails::global_score(scores.iter()))).collect::<String>(), result.document_scores), @r###"
+    IDs: [4, 1, 0, 2]
+    Scores: 1.0000 0.9167 0.6667 0.0000 
+    Score Details:
+    [
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Typo(
+                Typo {
+                    typo_count: 0,
+                    max_typo_count: 3,
+                },
+            ),
+        ],
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Typo(
+                Typo {
+                    typo_count: 1,
+                    max_typo_count: 3,
+                },
+            ),
+        ],
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Skipped,
+        ],
+        [
+            Skipped,
+        ],
+    ]
+    "###);
+
+    // Do FOUR loop iterations. The third document should be entirely sorted as well
+    // The words bucket have still not progressed thus the last document doesn't have any info yet.
+    search.time_budget(TimeBudget::max().with_stop_after(4));
+
+    let result = search.execute().unwrap();
+    snapshot!(format!("IDs: {:?}\nScores: {}\nScore Details:\n{:#?}", result.documents_ids, result.document_scores.iter().map(|scores| format!("{:.4} ", ScoreDetails::global_score(scores.iter()))).collect::<String>(), result.document_scores), @r###"
+    IDs: [4, 1, 0, 2]
+    Scores: 1.0000 0.9167 0.8333 0.0000 
+    Score Details:
+    [
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Typo(
+                Typo {
+                    typo_count: 0,
+                    max_typo_count: 3,
+                },
+            ),
+        ],
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Typo(
+                Typo {
+                    typo_count: 1,
+                    max_typo_count: 3,
+                },
+            ),
+        ],
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Typo(
+                Typo {
+                    typo_count: 2,
+                    max_typo_count: 3,
+                },
+            ),
+        ],
+        [
+            Skipped,
+        ],
+    ]
+    "###);
+
+    // After SIX loop iteration. The words ranking rule gave us a new bucket.
+    // Since we reached the limit we were able to early exit without checking the typo ranking rule.
+    search.time_budget(TimeBudget::max().with_stop_after(6));
+
+    let result = search.execute().unwrap();
+    snapshot!(format!("IDs: {:?}\nScores: {}\nScore Details:\n{:#?}", result.documents_ids, result.document_scores.iter().map(|scores| format!("{:.4} ", ScoreDetails::global_score(scores.iter()))).collect::<String>(), result.document_scores), @r###"
+    IDs: [4, 1, 0, 3]
+    Scores: 1.0000 0.9167 0.8333 0.3333 
+    Score Details:
+    [
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Typo(
+                Typo {
+                    typo_count: 0,
+                    max_typo_count: 3,
+                },
+            ),
+        ],
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Typo(
+                Typo {
+                    typo_count: 1,
+                    max_typo_count: 3,
+                },
+            ),
+        ],
+        [
+            Words(
+                Words {
+                    matching_words: 3,
+                    max_matching_words: 3,
+                },
+            ),
+            Typo(
+                Typo {
+                    typo_count: 2,
+                    max_typo_count: 3,
+                },
+            ),
+        ],
+        [
+            Words(
+                Words {
+                    matching_words: 2,
+                    max_matching_words: 3,
+                },
+            ),
+            Skipped,
+        ],
+    ]
+    "###);
+}

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

@@ -1,5 +1,6 @@
 pub mod attribute_fid;
 pub mod attribute_position;
+pub mod cutoff;
 pub mod distinct;
 pub mod exactness;
 pub mod geo_sort;

milli/src/update/settings.rs

@@ -150,6 +150,7 @@ pub struct Settings<'a, 't, 'i> {
     pagination_max_total_hits: Setting<usize>,
     proximity_precision: Setting<ProximityPrecision>,
     embedder_settings: Setting<BTreeMap<String, Setting<EmbeddingSettings>>>,
+    search_cutoff: Setting<u64>,
 }
 
 impl<'a, 't, 'i> Settings<'a, 't, 'i> {
@@ -183,6 +184,7 @@ impl<'a, 't, 'i> Settings<'a, 't, 'i> {
             pagination_max_total_hits: Setting::NotSet,
             proximity_precision: Setting::NotSet,
             embedder_settings: Setting::NotSet,
+            search_cutoff: Setting::NotSet,
             indexer_config,
         }
     }
@@ -373,6 +375,14 @@ impl<'a, 't, 'i> Settings<'a, 't, 'i> {
         self.embedder_settings = Setting::Reset;
     }
 
+    pub fn set_search_cutoff(&mut self, value: u64) {
+        self.search_cutoff = Setting::Set(value);
+    }
+
+    pub fn reset_search_cutoff(&mut self) {
+        self.search_cutoff = Setting::Reset;
+    }
+
     #[tracing::instrument(
         level = "trace"
         skip(self, progress_callback, should_abort, old_fields_ids_map),
@@ -1026,6 +1036,24 @@ impl<'a, 't, 'i> Settings<'a, 't, 'i> {
         Ok(update)
     }
 
+    fn update_search_cutoff(&mut self) -> Result<bool> {
+        let changed = match self.search_cutoff {
+            Setting::Set(new) => {
+                let old = self.index.search_cutoff(self.wtxn)?;
+                if old == Some(new) {
+                    false
+                } else {
+                    self.index.put_search_cutoff(self.wtxn, new)?;
+                    true
+                }
+            }
+            Setting::Reset => self.index.delete_search_cutoff(self.wtxn)?,
+            Setting::NotSet => false,
+        };
+
+        Ok(changed)
+    }
+
     pub fn execute<FP, FA>(mut self, progress_callback: FP, should_abort: FA) -> Result<()>
     where
         FP: Fn(UpdateIndexingStep) + Sync,
@@ -1079,6 +1107,9 @@ impl<'a, 't, 'i> Settings<'a, 't, 'i> {
         // 3. Keep the old vectors but reattempt indexing on a prompt change: only actually changed prompt will need embedding + storage
         let embedding_configs_updated = self.update_embedding_configs()?;
 
+        // never trigger re-indexing
+        self.update_search_cutoff()?;
+
         if stop_words_updated
             || non_separator_tokens_updated
             || separator_tokens_updated
@@ -2035,6 +2066,7 @@ mod tests {
                     pagination_max_total_hits,
                     proximity_precision,
                     embedder_settings,
+                    search_cutoff,
                 } = settings;
                 assert!(matches!(searchable_fields, Setting::NotSet));
                 assert!(matches!(displayed_fields, Setting::NotSet));
@@ -2058,6 +2090,7 @@ mod tests {
                 assert!(matches!(pagination_max_total_hits, Setting::NotSet));
                 assert!(matches!(proximity_precision, Setting::NotSet));
                 assert!(matches!(embedder_settings, Setting::NotSet));
+                assert!(matches!(search_cutoff, Setting::NotSet));
             })
             .unwrap();
     }