Reduce the maximum word proximity from 8 to 4

meilisearch-types/src/error.rs

@@ -240,8 +240,6 @@ InvalidSearchOffset                   , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchPage                     , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchQ                        , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchShowMatchesPosition      , InvalidRequest       , BAD_REQUEST ;
-InvalidSearchShowRankingScore         , InvalidRequest       , BAD_REQUEST ;
-InvalidSearchShowRankingScoreDetails  , InvalidRequest       , BAD_REQUEST ;
 InvalidSearchSort                     , InvalidRequest       , BAD_REQUEST ;
 InvalidSettingsDisplayedAttributes    , InvalidRequest       , BAD_REQUEST ;
 InvalidSettingsDistinctAttribute      , InvalidRequest       , BAD_REQUEST ;

meilisearch/src/routes/indexes/search.rs

@@ -56,10 +56,6 @@ pub struct SearchQueryGet {
     sort: Option<String>,
     #[deserr(default, error = DeserrQueryParamError<InvalidSearchShowMatchesPosition>)]
     show_matches_position: Param<bool>,
-    #[deserr(default, error = DeserrQueryParamError<InvalidSearchShowRankingScore>)]
-    show_ranking_score: Param<bool>,
-    #[deserr(default, error = DeserrQueryParamError<InvalidSearchShowRankingScoreDetails>)]
-    show_ranking_score_details: Param<bool>,
     #[deserr(default, error = DeserrQueryParamError<InvalidSearchFacets>)]
     facets: Option<CS<String>>,
     #[deserr( default = DEFAULT_HIGHLIGHT_PRE_TAG(), error = DeserrQueryParamError<InvalidSearchHighlightPreTag>)]
@@ -95,8 +91,6 @@ impl From<SearchQueryGet> for SearchQuery {
             filter,
             sort: other.sort.map(|attr| fix_sort_query_parameters(&attr)),
             show_matches_position: other.show_matches_position.0,
-            show_ranking_score: other.show_ranking_score.0,
-            show_ranking_score_details: other.show_ranking_score_details.0,
             facets: other.facets.map(|o| o.into_iter().collect()),
             highlight_pre_tag: other.highlight_pre_tag,
             highlight_post_tag: other.highlight_post_tag,

meilisearch/src/search.rs

@@ -9,7 +9,6 @@ use meilisearch_auth::IndexSearchRules;
 use meilisearch_types::deserr::DeserrJsonError;
 use meilisearch_types::error::deserr_codes::*;
 use meilisearch_types::index_uid::IndexUid;
-use meilisearch_types::milli::score_details::ScoreDetails;
 use meilisearch_types::settings::DEFAULT_PAGINATION_MAX_TOTAL_HITS;
 use meilisearch_types::{milli, Document};
 use milli::tokenizer::TokenizerBuilder;
@@ -55,10 +54,6 @@ pub struct SearchQuery {
     pub attributes_to_highlight: Option<HashSet<String>>,
     #[deserr(default, error = DeserrJsonError<InvalidSearchShowMatchesPosition>, default)]
     pub show_matches_position: bool,
-    #[deserr(default, error = DeserrJsonError<InvalidSearchShowRankingScore>, default)]
-    pub show_ranking_score: bool,
-    #[deserr(default, error = DeserrJsonError<InvalidSearchShowRankingScoreDetails>, default)]
-    pub show_ranking_score_details: bool,
     #[deserr(default, error = DeserrJsonError<InvalidSearchFilter>)]
     pub filter: Option<Value>,
     #[deserr(default, error = DeserrJsonError<InvalidSearchSort>)]
@@ -108,10 +103,6 @@ pub struct SearchQueryWithIndex {
     pub crop_length: usize,
     #[deserr(default, error = DeserrJsonError<InvalidSearchAttributesToHighlight>)]
     pub attributes_to_highlight: Option<HashSet<String>>,
-    #[deserr(default, error = DeserrJsonError<InvalidSearchShowRankingScore>, default)]
-    pub show_ranking_score: bool,
-    #[deserr(default, error = DeserrJsonError<InvalidSearchShowRankingScoreDetails>, default)]
-    pub show_ranking_score_details: bool,
     #[deserr(default, error = DeserrJsonError<InvalidSearchShowMatchesPosition>, default)]
     pub show_matches_position: bool,
     #[deserr(default, error = DeserrJsonError<InvalidSearchFilter>)]
@@ -143,8 +134,6 @@ impl SearchQueryWithIndex {
             attributes_to_crop,
             crop_length,
             attributes_to_highlight,
-            show_ranking_score,
-            show_ranking_score_details,
             show_matches_position,
             filter,
             sort,
@@ -166,8 +155,6 @@ impl SearchQueryWithIndex {
                 attributes_to_crop,
                 crop_length,
                 attributes_to_highlight,
-                show_ranking_score,
-                show_ranking_score_details,
                 show_matches_position,
                 filter,
                 sort,
@@ -207,7 +194,7 @@ impl From<MatchingStrategy> for TermsMatchingStrategy {
     }
 }
 
-#[derive(Debug, Clone, Serialize, PartialEq)]
+#[derive(Debug, Clone, Serialize, PartialEq, Eq)]
 pub struct SearchHit {
     #[serde(flatten)]
     pub document: Document,
@@ -215,10 +202,6 @@ pub struct SearchHit {
     pub formatted: Document,
     #[serde(rename = "_matchesPosition", skip_serializing_if = "Option::is_none")]
     pub matches_position: Option<MatchesPosition>,
-    #[serde(rename = "_rankingScore", skip_serializing_if = "Option::is_none")]
-    pub ranking_score: Option<u64>,
-    #[serde(rename = "_rankingScoreDetails", skip_serializing_if = "Option::is_none")]
-    pub ranking_score_details: Option<serde_json::Map<String, serde_json::Value>>,
 }
 
 #[derive(Serialize, Debug, Clone, PartialEq)]
@@ -337,8 +320,7 @@ pub fn perform_search(
         search.sort_criteria(sort);
     }
 
-    let milli::SearchResult { documents_ids, matching_words, candidates, document_scores, .. } =
-        search.execute()?;
+    let milli::SearchResult { documents_ids, matching_words, candidates, .. } = search.execute()?;
 
     let fields_ids_map = index.fields_ids_map(&rtxn).unwrap();
 
@@ -410,7 +392,7 @@ pub fn perform_search(
 
     let documents_iter = index.documents(&rtxn, documents_ids)?;
 
-    for ((_id, obkv), score) in documents_iter.into_iter().zip(document_scores.into_iter()) {
+    for (_id, obkv) in documents_iter {
         // First generate a document with all the displayed fields
         let displayed_document = make_document(&displayed_ids, &fields_ids_map, obkv)?;
 
@@ -434,18 +416,7 @@ pub fn perform_search(
             insert_geo_distance(sort, &mut document);
         }
 
-        let ranking_score =
-            query.show_ranking_score.then(|| ScoreDetails::global_score_linear_scale(score.iter()));
-        let ranking_score_details =
-            query.show_ranking_score_details.then(|| ScoreDetails::to_json_map(score.iter()));
-
-        let hit = SearchHit {
-            document,
-            formatted,
-            matches_position,
-            ranking_score_details,
-            ranking_score,
-        };
+        let hit = SearchHit { document, formatted, matches_position };
         documents.push(hit);
     }
 

meilisearch/tests/search/formatted.rs

@@ -1,4 +1,3 @@
-use insta::{allow_duplicates, assert_json_snapshot};
 use serde_json::json;
 
 use super::*;
@@ -19,43 +18,30 @@ async fn formatted_contain_wildcard() {
         |response, code|
         {
             assert_eq!(code, 200, "{}", response);
-            allow_duplicates! {
-              assert_json_snapshot!(response["hits"][0],
-                    { "._rankingScore" => "[score]" },
-                    @r###"
-              {
-                "_formatted": {
-                  "id": "852",
-                  "cattos": "<em>pésti</em>"
-                },
-                "_matchesPosition": {
-                  "cattos": [
-                    {
-                      "start": 0,
-                      "length": 5
-                    }
-                  ]
-                }
-              }
-              "###);
-            }
-    }
+            assert_eq!(
+                response["hits"][0],
+                json!({
+                    "_formatted": {
+                        "id": "852",
+                        "cattos": "<em>pésti</em>",
+                    },
+                    "_matchesPosition": {"cattos": [{"start": 0, "length": 5}]},
+                })
+            );
+        }
     )
     .await;
 
     index
         .search(json!({ "q": "pésti", "attributesToRetrieve": ["*"] }), |response, code| {
             assert_eq!(code, 200, "{}", response);
-            allow_duplicates! {
-                assert_json_snapshot!(response["hits"][0],
-                { "._rankingScore" => "[score]" },
-                @r###"
-                {
-                  "id": 852,
-                  "cattos": "pésti"
-                }
-                "###)
-            }
+            assert_eq!(
+                response["hits"][0],
+                json!({
+                    "id": 852,
+                    "cattos": "pésti",
+                })
+            );
         })
         .await;
 
@@ -64,29 +50,20 @@ async fn formatted_contain_wildcard() {
             json!({ "q": "pésti", "attributesToRetrieve": ["*"], "attributesToHighlight": ["id"], "showMatchesPosition": true }),
             |response, code| {
                 assert_eq!(code, 200, "{}", response);
-                allow_duplicates! {
-                  assert_json_snapshot!(response["hits"][0],
-                 { "._rankingScore" => "[score]" },
-                 @r###"
-                  {
-                    "id": 852,
-                    "cattos": "pésti",
-                    "_formatted": {
-                      "id": "852",
-                      "cattos": "pésti"
-                    },
-                    "_matchesPosition": {
-                      "cattos": [
-                        {
-                          "start": 0,
-                          "length": 5
-                        }
-                      ]
-                    }
-                  }
-                  "###)
-             }
-        })
+                assert_eq!(
+                    response["hits"][0],
+                    json!({
+                        "id": 852,
+                        "cattos": "pésti",
+                        "_formatted": {
+                            "id": "852",
+                            "cattos": "pésti",
+                        },
+                        "_matchesPosition": {"cattos": [{"start": 0, "length": 5}]},
+                    })
+                );
+            }
+        )
         .await;
 
     index
@@ -94,20 +71,17 @@ async fn formatted_contain_wildcard() {
             json!({ "q": "pésti", "attributesToRetrieve": ["*"], "attributesToCrop": ["*"] }),
             |response, code| {
                 assert_eq!(code, 200, "{}", response);
-                allow_duplicates! {
-                    assert_json_snapshot!(response["hits"][0],
-                    { "._rankingScore" => "[score]" },
-                    @r###"
-                    {
-                      "id": 852,
-                      "cattos": "pésti",
-                      "_formatted": {
-                        "id": "852",
-                        "cattos": "pésti"
-                      }
-                    }
-                    "###);
-                }
+                assert_eq!(
+                    response["hits"][0],
+                    json!({
+                        "id": 852,
+                        "cattos": "pésti",
+                        "_formatted": {
+                            "id": "852",
+                            "cattos": "pésti",
+                        }
+                    })
+                );
             },
         )
         .await;
@@ -115,20 +89,17 @@ async fn formatted_contain_wildcard() {
     index
         .search(json!({ "q": "pésti", "attributesToCrop": ["*"] }), |response, code| {
             assert_eq!(code, 200, "{}", response);
-            allow_duplicates! {
-                assert_json_snapshot!(response["hits"][0],
-                { "._rankingScore" => "[score]" },
-                @r###"
-                {
-                  "id": 852,
-                  "cattos": "pésti",
-                  "_formatted": {
-                    "id": "852",
-                    "cattos": "pésti"
-                  }
-                }
-                "###)
-            }
+            assert_eq!(
+                response["hits"][0],
+                json!({
+                    "id": 852,
+                    "cattos": "pésti",
+                    "_formatted": {
+                        "id": "852",
+                        "cattos": "pésti",
+                    }
+                })
+            );
         })
         .await;
 }
@@ -145,24 +116,21 @@ async fn format_nested() {
     index
         .search(json!({ "q": "pésti", "attributesToRetrieve": ["doggos"] }), |response, code| {
             assert_eq!(code, 200, "{}", response);
-            allow_duplicates! {
-                assert_json_snapshot!(response["hits"][0],
-                { "._rankingScore" => "[score]" },
-                @r###"
-                {
-                  "doggos": [
-                    {
-                      "name": "bobby",
-                      "age": 2
-                    },
-                    {
-                      "name": "buddy",
-                      "age": 4
-                    }
-                  ]
-                }
-                "###)
-            }
+            assert_eq!(
+                response["hits"][0],
+                json!({
+                    "doggos": [
+                        {
+                            "name": "bobby",
+                            "age": 2,
+                        },
+                        {
+                            "name": "buddy",
+                            "age": 4,
+                        },
+                    ],
+                })
+            );
         })
         .await;
 
@@ -171,22 +139,19 @@ async fn format_nested() {
             json!({ "q": "pésti", "attributesToRetrieve": ["doggos.name"] }),
             |response, code| {
                 assert_eq!(code, 200, "{}", response);
-                allow_duplicates! {
-                    assert_json_snapshot!(response["hits"][0],
-                    { "._rankingScore" => "[score]" },
-                    @r###"
-                    {
-                      "doggos": [
-                        {
-                          "name": "bobby"
-                        },
-                        {
-                          "name": "buddy"
-                        }
-                      ]
-                    }
-                    "###)
-                }
+                assert_eq!(
+                    response["hits"][0],
+                    json!({
+                        "doggos": [
+                            {
+                                "name": "bobby",
+                            },
+                            {
+                                "name": "buddy",
+                            },
+                        ],
+                    })
+                );
             },
         )
         .await;
@@ -196,30 +161,20 @@ async fn format_nested() {
             json!({ "q": "bobby", "attributesToRetrieve": ["doggos.name"], "showMatchesPosition": true }),
             |response, code| {
                 assert_eq!(code, 200, "{}", response);
-                allow_duplicates! {
-                    assert_json_snapshot!(response["hits"][0],
-                    { "._rankingScore" => "[score]" },
-                    @r###"
-                    {
-                      "doggos": [
-                        {
-                          "name": "bobby"
-                        },
-                        {
-                          "name": "buddy"
-                        }
-                      ],
-                      "_matchesPosition": {
-                        "doggos.name": [
-                          {
-                            "start": 0,
-                            "length": 5
-                          }
-                        ]
-                      }
-                    }
-                    "###)
-                }
+                assert_eq!(
+                    response["hits"][0],
+                    json!({
+                        "doggos": [
+                            {
+                                "name": "bobby",
+                            },
+                            {
+                                "name": "buddy",
+                            },
+                        ],
+                        "_matchesPosition": {"doggos.name": [{"start": 0, "length": 5}]},
+                    })
+                );
             }
         )
         .await;
@@ -228,24 +183,21 @@ async fn format_nested() {
         .search(json!({ "q": "pésti", "attributesToRetrieve": [], "attributesToHighlight": ["doggos.name"] }),
         |response, code| {
             assert_eq!(code, 200, "{}", response);
-            allow_duplicates! {
-                assert_json_snapshot!(response["hits"][0],
-                { "._rankingScore" => "[score]" },
-                @r###"
-                {
-                  "_formatted": {
-                    "doggos": [
-                      {
-                        "name": "bobby"
-                      },
-                      {
-                        "name": "buddy"
-                      }
-                    ]
-                  }
-                }
-                "###)
-            }
+            assert_eq!(
+                response["hits"][0],
+                json!({
+                    "_formatted": {
+                        "doggos": [
+                            {
+                                "name": "bobby",
+                            },
+                            {
+                                "name": "buddy",
+                            },
+                        ],
+                    },
+                })
+            );
         })
         .await;
 
@@ -253,24 +205,21 @@ async fn format_nested() {
         .search(json!({ "q": "pésti", "attributesToRetrieve": [], "attributesToCrop": ["doggos.name"] }),
         |response, code| {
             assert_eq!(code, 200, "{}", response);
-            allow_duplicates! {
-                assert_json_snapshot!(response["hits"][0],
-                { "._rankingScore" => "[score]" },
-                @r###"
-                {
-                  "_formatted": {
-                    "doggos": [
-                      {
-                        "name": "bobby"
-                      },
-                      {
-                        "name": "buddy"
-                      }
-                    ]
-                  }
-                }
-                "###)
-            }
+            assert_eq!(
+                response["hits"][0],
+                json!({
+                    "_formatted": {
+                        "doggos": [
+                            {
+                                "name": "bobby",
+                            },
+                            {
+                                "name": "buddy",
+                            },
+                        ],
+                    },
+                })
+            );
         })
         .await;
 
@@ -278,61 +227,55 @@ async fn format_nested() {
         .search(json!({ "q": "pésti", "attributesToRetrieve": ["doggos.name"], "attributesToHighlight": ["doggos.age"] }),
         |response, code| {
     assert_eq!(code, 200, "{}", response);
-    allow_duplicates! {
-        assert_json_snapshot!(response["hits"][0],
-        { "._rankingScore" => "[score]" },
-        @r###"
-        {
-          "doggos": [
-            {
-              "name": "bobby"
-            },
-            {
-              "name": "buddy"
-            }
-          ],
-          "_formatted": {
+    assert_eq!(
+        response["hits"][0],
+        json!({
             "doggos": [
-              {
-                "name": "bobby",
-                "age": "2"
-              },
-              {
-                "name": "buddy",
-                "age": "4"
-              }
-            ]
-          }
-        }
-        "###)
-    }
-    })
+                {
+                    "name": "bobby",
+                },
+                {
+                    "name": "buddy",
+                },
+            ],
+            "_formatted": {
+                "doggos": [
+                    {
+                        "name": "bobby",
+                        "age": "2",
+                    },
+                    {
+                        "name": "buddy",
+                        "age": "4",
+                    },
+                ],
+            },
+        })
+    );
+        })
         .await;
 
     index
         .search(json!({ "q": "pésti", "attributesToRetrieve": [], "attributesToHighlight": ["doggos.age"], "attributesToCrop": ["doggos.name"] }),
         |response, code| {
                 assert_eq!(code, 200, "{}", response);
-                allow_duplicates! {
-                    assert_json_snapshot!(response["hits"][0],
-                    { "._rankingScore" => "[score]" },
-                    @r###"
+    assert_eq!(
+        response["hits"][0],
+        json!({
+            "_formatted": {
+                "doggos": [
                     {
-                      "_formatted": {
-                        "doggos": [
-                          {
-                            "name": "bobby",
-                            "age": "2"
-                          },
-                          {
-                            "name": "buddy",
-                            "age": "4"
-                          }
-                        ]
-                      }
-                    }
-                    "###)
-                }
+                        "name": "bobby",
+                        "age": "2",
+                    },
+                    {
+                        "name": "buddy",
+                        "age": "4",
+                    },
+                ],
+            },
+        })
+    );
             }
         )
         .await;
@@ -354,66 +297,54 @@ async fn displayedattr_2_smol() {
         .search(json!({ "attributesToRetrieve": ["father", "id"], "attributesToHighlight": ["mother"], "attributesToCrop": ["cattos"] }),
         |response, code| {
     assert_eq!(code, 200, "{}", response);
-    allow_duplicates! {
-        assert_json_snapshot!(response["hits"][0],
-        { "._rankingScore" => "[score]" },
-        @r###"
-        {
-          "id": 852
-        }
-        "###)
-    }
+    assert_eq!(
+        response["hits"][0],
+        json!({
+            "id": 852,
+        })
+    );
         })
         .await;
 
     index
         .search(json!({ "attributesToRetrieve": ["id"] }), |response, code| {
             assert_eq!(code, 200, "{}", response);
-            allow_duplicates! {
-                assert_json_snapshot!(response["hits"][0],
-                { "._rankingScore" => "[score]" },
-                @r###"
-                {
-                  "id": 852
-                }
-                "###)
-            }
+            assert_eq!(
+                response["hits"][0],
+                json!({
+                    "id": 852,
+                })
+            );
         })
         .await;
 
     index
         .search(json!({ "attributesToHighlight": ["id"] }), |response, code| {
             assert_eq!(code, 200, "{}", response);
-            allow_duplicates! {
-                assert_json_snapshot!(response["hits"][0],
-                { "._rankingScore" => "[score]" },
-                @r###"
-                {
-                  "id": 852,
-                  "_formatted": {
-                    "id": "852"
-                  }
-                }
-                "###)
-            }
+            assert_eq!(
+                response["hits"][0],
+                json!({
+                    "id": 852,
+                    "_formatted": {
+                        "id": "852",
+                    }
+                })
+            );
         })
         .await;
 
     index
         .search(json!({ "attributesToCrop": ["id"] }), |response, code| {
             assert_eq!(code, 200, "{}", response);
-            allow_duplicates! {
-                assert_json_snapshot!(response["hits"][0],
-                { "._rankingScore" => "[score]" },
-                @r###"
-                {
-                  "id": 852,
-                  "_formatted": {
-                    "id": "852"
-                  }
-                }
-                "###)
-            }
+            assert_eq!(
+                response["hits"][0],
+                json!({
+                    "id": 852,
+                    "_formatted": {
+                        "id": "852",
+                    }
+                })
+            );
         })
         .await;
 
@@ -422,18 +353,15 @@ async fn displayedattr_2_smol() {
             json!({ "attributesToHighlight": ["id"], "attributesToCrop": ["id"] }),
             |response, code| {
                 assert_eq!(code, 200, "{}", response);
-                allow_duplicates! {
-                    assert_json_snapshot!(response["hits"][0],
-                    { "._rankingScore" => "[score]" },
-                    @r###"
-                    {
-                      "id": 852,
-                      "_formatted": {
-                        "id": "852"
-                      }
-                    }
-                    "###)
-                }
+                assert_eq!(
+                    response["hits"][0],
+                    json!({
+                        "id": 852,
+                        "_formatted": {
+                            "id": "852",
+                        }
+                    })
+                );
             },
         )
         .await;
@@ -441,41 +369,31 @@ async fn displayedattr_2_smol() {
     index
         .search(json!({ "attributesToHighlight": ["cattos"] }), |response, code| {
             assert_eq!(code, 200, "{}", response);
-            allow_duplicates! {
-                assert_json_snapshot!(response["hits"][0],
-                { "._rankingScore" => "[score]" },
-                @r###"
-                {
-                  "id": 852
-                }
-                "###)
-            }
+            assert_eq!(
+                response["hits"][0],
+                json!({
+                    "id": 852,
+                })
+            );
         })
         .await;
 
     index
         .search(json!({ "attributesToCrop": ["cattos"] }), |response, code| {
             assert_eq!(code, 200, "{}", response);
-            allow_duplicates! {
-                assert_json_snapshot!(response["hits"][0],
-                { "._rankingScore" => "[score]" },
-                @r###"
-                {
-                  "id": 852
-                }
-                "###)
-            }
+            assert_eq!(
+                response["hits"][0],
+                json!({
+                    "id": 852,
+                })
+            );
         })
         .await;
 
     index
         .search(json!({ "attributesToRetrieve": ["cattos"] }), |response, code| {
             assert_eq!(code, 200, "{}", response);
-            allow_duplicates! {
-                assert_json_snapshot!(response["hits"][0],
-                { "._rankingScore" => "[score]" },
-                @"{}")
-            }
+            assert_eq!(response["hits"][0], json!({}));
         })
         .await;
 
@@ -484,11 +402,7 @@ async fn displayedattr_2_smol() {
             json!({ "attributesToRetrieve": ["cattos"], "attributesToHighlight": ["cattos"], "attributesToCrop": ["cattos"] }),
             |response, code| {
     assert_eq!(code, 200, "{}", response);
-    allow_duplicates! {
-        assert_json_snapshot!(response["hits"][0],
-        { "._rankingScore" => "[score]" },
-        @"{}")
-    }
+    assert_eq!(response["hits"][0], json!({}));
 
             }
         )
@@ -499,17 +413,14 @@ async fn displayedattr_2_smol() {
             json!({ "attributesToRetrieve": ["cattos"], "attributesToHighlight": ["id"] }),
             |response, code| {
                 assert_eq!(code, 200, "{}", response);
-                allow_duplicates! {
-                    assert_json_snapshot!(response["hits"][0],
-                    { "._rankingScore" => "[score]" },
-                    @r###"
-                    {
-                      "_formatted": {
-                        "id": "852"
-                      }
-                    }
-                    "###)
-                }
+                assert_eq!(
+                    response["hits"][0],
+                    json!({
+                        "_formatted": {
+                            "id": "852",
+                        }
+                    })
+                );
             },
         )
         .await;
@@ -519,17 +430,14 @@ async fn displayedattr_2_smol() {
             json!({ "attributesToRetrieve": ["cattos"], "attributesToCrop": ["id"] }),
             |response, code| {
                 assert_eq!(code, 200, "{}", response);
-                allow_duplicates! {
-                    assert_json_snapshot!(response["hits"][0],
-                    { "._rankingScore" => "[score]" },
-                    @r###"
-                    {
-                      "_formatted": {
-                        "id": "852"
-                      }
-                    }
-                    "###)
-                }
+                assert_eq!(
+                    response["hits"][0],
+                    json!({
+                        "_formatted": {
+                            "id": "852",
+                        }
+                    })
+                );
             },
         )
         .await;

meilisearch/tests/search/multi.rs

@@ -65,7 +65,7 @@ async fn simple_search_single_index() {
         ]}))
         .await;
     snapshot!(code, @"200 OK");
-    insta::assert_json_snapshot!(response["results"], { "[].processingTimeMs" => "[time]", ".**._rankingScore" => "[score]" }, @r###"
+    insta::assert_json_snapshot!(response["results"], { "[].processingTimeMs" => "[time]" }, @r###"
     [
       {
         "indexUid": "test",
@@ -170,7 +170,7 @@ async fn simple_search_two_indexes() {
         ]}))
         .await;
     snapshot!(code, @"200 OK");
-    insta::assert_json_snapshot!(response["results"], { "[].processingTimeMs" => "[time]", ".**._rankingScore" => "[score]" }, @r###"
+    insta::assert_json_snapshot!(response["results"], { "[].processingTimeMs" => "[time]" }, @r###"
     [
       {
         "indexUid": "test",

milli/src/index.rs

@@ -2488,12 +2488,8 @@ pub(crate) mod tests {
 
         let rtxn = index.read_txn().unwrap();
         let search = Search::new(&rtxn, &index);
-        let SearchResult {
-            matching_words: _,
-            candidates: _,
-            document_scores: _,
-            mut documents_ids,
-        } = search.execute().unwrap();
+        let SearchResult { matching_words: _, candidates: _, mut documents_ids } =
+            search.execute().unwrap();
         let primary_key_id = index.fields_ids_map(&rtxn).unwrap().id("primary_key").unwrap();
         documents_ids.sort_unstable();
         let docs = index.documents(&rtxn, documents_ids).unwrap();

milli/src/lib.rs

@@ -17,7 +17,6 @@ mod fields_ids_map;
 pub mod heed_codec;
 pub mod index;
 pub mod proximity;
-pub mod score_details;
 mod search;
 pub mod update;
 

milli/src/proximity.rs

@@ -2,7 +2,7 @@ use std::cmp;
 
 use crate::{relative_from_absolute_position, Position};
 
-pub const MAX_DISTANCE: u32 = 8;
+pub const MAX_DISTANCE: u32 = 4;
 
 pub fn index_proximity(lhs: u32, rhs: u32) -> u32 {
     if lhs <= rhs {

milli/src/score_details.rs

@@ -1,295 +0,0 @@
-use serde::Serialize;
-
-use crate::distance_between_two_points;
-
-#[derive(Debug, Clone, PartialEq)]
-pub enum ScoreDetails {
-    Words(Words),
-    Typo(Typo),
-    Proximity(Rank),
-    Fid(Rank),
-    Position(Rank),
-    ExactAttribute(ExactAttribute),
-    Exactness(Rank),
-    Sort(Sort),
-    GeoSort(GeoSort),
-}
-
-impl ScoreDetails {
-    pub fn local_score(&self) -> Option<f64> {
-        self.rank().map(Rank::local_score)
-    }
-
-    pub fn rank(&self) -> Option<Rank> {
-        match self {
-            ScoreDetails::Words(details) => Some(details.rank()),
-            ScoreDetails::Typo(details) => Some(details.rank()),
-            ScoreDetails::Proximity(details) => Some(*details),
-            ScoreDetails::Fid(details) => Some(*details),
-            ScoreDetails::Position(details) => Some(*details),
-            ScoreDetails::ExactAttribute(details) => Some(details.rank()),
-            ScoreDetails::Exactness(details) => Some(*details),
-            ScoreDetails::Sort(_) => None,
-            ScoreDetails::GeoSort(_) => None,
-        }
-    }
-
-    pub fn global_score<'a>(details: impl Iterator<Item = &'a Self>) -> f64 {
-        Rank::global_score(details.filter_map(Self::rank))
-    }
-
-    pub fn global_score_linear_scale<'a>(details: impl Iterator<Item = &'a Self>) -> u64 {
-        (Self::global_score(details) * LINEAR_SCALE_FACTOR).round() as u64
-    }
-
-    /// Panics
-    ///
-    /// - If Position is not preceded by Fid
-    /// - If Exactness is not preceded by ExactAttribute
-    /// - If a sort fid is not contained in the passed `fields_ids_map`.
-    pub fn to_json_map<'a>(
-        details: impl Iterator<Item = &'a Self>,
-    ) -> serde_json::Map<String, serde_json::Value> {
-        let mut order = 0;
-        let mut details_map = serde_json::Map::default();
-        for details in details {
-            match details {
-                ScoreDetails::Words(words) => {
-                    let words_details = serde_json::json!({
-                            "order": order,
-                            "matchingWords": words.matching_words,
-                            "maxMatchingWords": words.max_matching_words,
-                            "score": words.rank().local_score_linear_scale(),
-                    });
-                    details_map.insert("words".into(), words_details);
-                    order += 1;
-                }
-                ScoreDetails::Typo(typo) => {
-                    let typo_details = serde_json::json!({
-                        "order": order,
-                        "typoCount": typo.typo_count,
-                        "maxTypoCount": typo.max_typo_count,
-                        "score": typo.rank().local_score_linear_scale(),
-                    });
-                    details_map.insert("typo".into(), typo_details);
-                    order += 1;
-                }
-                ScoreDetails::Proximity(proximity) => {
-                    let proximity_details = serde_json::json!({
-                        "order": order,
-                        "score": proximity.local_score_linear_scale(),
-                    });
-                    details_map.insert("proximity".into(), proximity_details);
-                    order += 1;
-                }
-                ScoreDetails::Fid(fid) => {
-                    // For now, fid is a virtual rule always followed by the "position" rule
-                    let fid_details = serde_json::json!({
-                        "order": order,
-                        "attributes_ranking_order": fid.local_score_linear_scale(),
-                    });
-                    details_map.insert("attribute".into(), fid_details);
-                    order += 1;
-                }
-                ScoreDetails::Position(position) => {
-                    // For now, position is a virtual rule always preceded by the "fid" rule
-                    let attribute_details = details_map
-                        .get_mut("attribute")
-                        .expect("position not preceded by attribute");
-                    let attribute_details = attribute_details
-                        .as_object_mut()
-                        .expect("attribute details was not an object");
-                    attribute_details.insert(
-                        "attributes_query_word_order".into(),
-                        position.local_score_linear_scale().into(),
-                    );
-                    // do not update the order since this was already done by fid
-                }
-                ScoreDetails::ExactAttribute(exact_attribute) => {
-                    let exactness_details = serde_json::json!({
-                        "order": order,
-                        "exactIn": exact_attribute,
-                        "score": exact_attribute.rank().local_score_linear_scale(),
-                    });
-                    details_map.insert("exactness".into(), exactness_details);
-                    order += 1;
-                }
-                ScoreDetails::Exactness(details) => {
-                    // For now, exactness is a virtual rule always preceded by the "ExactAttribute" rule
-                    let exactness_details = details_map
-                        .get_mut("exactness")
-                        .expect("Exactness not preceded by exactAttribute");
-                    let exactness_details = exactness_details
-                        .as_object_mut()
-                        .expect("exactness details was not an object");
-                    if exactness_details.get("exactIn").expect("missing 'exactIn'")
-                        == &serde_json::json!(ExactAttribute::NoExactMatch)
-                    {
-                        let score = Rank::global_score_linear_scale(
-                            [ExactAttribute::NoExactMatch.rank(), *details].iter().copied(),
-                        );
-                        *exactness_details.get_mut("score").expect("missing score") = score.into();
-                    }
-                    // do not update the order since this was already done by exactAttribute
-                }
-                ScoreDetails::Sort(details) => {
-                    let sort = format!(
-                        "{}:{}",
-                        details.field_name,
-                        if details.ascending { "asc" } else { "desc" }
-                    );
-                    let sort_details = serde_json::json!({
-                        "order": order,
-                        "value": details.value,
-                    });
-                    details_map.insert(sort, sort_details);
-                    order += 1;
-                }
-                ScoreDetails::GeoSort(details) => {
-                    let sort = format!(
-                        "_geoPoint({}, {}):{}",
-                        details.target_point[0],
-                        details.target_point[1],
-                        if details.ascending { "asc" } else { "desc" }
-                    );
-                    let point = if let Some(value) = details.value {
-                        serde_json::json!({ "lat": value[0], "lng": value[1]})
-                    } else {
-                        serde_json::Value::Null
-                    };
-                    let sort_details = serde_json::json!({
-                        "order": order,
-                        "value": point,
-                        "distance": details.distance(),
-                    });
-                    details_map.insert(sort, sort_details);
-                    order += 1;
-                }
-            }
-        }
-        details_map
-    }
-}
-
-#[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord, Hash)]
-pub struct Words {
-    pub matching_words: u32,
-    pub max_matching_words: u32,
-}
-
-impl Words {
-    pub fn rank(&self) -> Rank {
-        Rank { rank: self.matching_words, max_rank: self.max_matching_words }
-    }
-
-    pub(crate) fn from_rank(rank: Rank) -> Words {
-        Words { matching_words: rank.rank, max_matching_words: rank.max_rank }
-    }
-}
-
-#[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord, Hash)]
-pub struct Typo {
-    pub typo_count: u32,
-    pub max_typo_count: u32,
-}
-
-impl Typo {
-    pub fn rank(&self) -> Rank {
-        Rank {
-            rank: self.max_typo_count - self.typo_count + 1,
-            max_rank: (self.max_typo_count + 1),
-        }
-    }
-
-    // max_rank = max_typo + 1
-    // max_typo = max_rank - 1
-    //
-    // rank = max_typo - typo + 1
-    // rank = max_rank - 1 - typo + 1
-    // rank + typo = max_rank
-    // typo = max_rank - rank
-    pub fn from_rank(rank: Rank) -> Typo {
-        Typo { typo_count: rank.max_rank - rank.rank, max_typo_count: rank.max_rank - 1 }
-    }
-}
-
-#[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord, Hash)]
-pub struct Rank {
-    /// The ordinal rank, such that `max_rank` is the first rank, and 0 is the last rank.
-    ///
-    /// The higher the better. Documents with a rank of 0 have a score of 0 and are typically never returned
-    /// (they don't match the query).
-    pub rank: u32,
-    /// The maximum possible rank. Documents with this rank have a score of 1.
-    ///
-    /// The max rank should not be 0.
-    pub max_rank: u32,
-}
-
-impl Rank {
-    pub fn local_score(self) -> f64 {
-        self.rank as f64 / self.max_rank as f64
-    }
-
-    pub fn local_score_linear_scale(self) -> u64 {
-        (self.local_score() * LINEAR_SCALE_FACTOR).round() as u64
-    }
-
-    pub fn global_score(details: impl Iterator<Item = Self>) -> f64 {
-        let mut rank = Rank { rank: 1, max_rank: 1 };
-        for inner_rank in details {
-            rank.rank -= 1;
-
-            rank.rank *= inner_rank.max_rank;
-            rank.max_rank *= inner_rank.max_rank;
-
-            rank.rank += inner_rank.rank;
-        }
-        rank.local_score()
-    }
-
-    pub fn global_score_linear_scale(details: impl Iterator<Item = Self>) -> u64 {
-        (Self::global_score(details) * LINEAR_SCALE_FACTOR).round() as u64
-    }
-}
-
-#[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord, Hash, Serialize)]
-#[serde(rename_all = "camelCase")]
-pub enum ExactAttribute {
-    MatchesFull,
-    MatchesStart,
-    NoExactMatch,
-}
-
-impl ExactAttribute {
-    pub fn rank(&self) -> Rank {
-        let rank = match self {
-            ExactAttribute::MatchesFull => 3,
-            ExactAttribute::MatchesStart => 2,
-            ExactAttribute::NoExactMatch => 1,
-        };
-        Rank { rank, max_rank: 3 }
-    }
-}
-
-#[derive(Debug, Clone, PartialEq)]
-pub struct Sort {
-    pub field_name: String,
-    pub ascending: bool,
-    pub value: serde_json::Value,
-}
-
-#[derive(Debug, Clone, Copy, PartialEq, PartialOrd)]
-pub struct GeoSort {
-    pub target_point: [f64; 2],
-    pub ascending: bool,
-    pub value: Option<[f64; 2]>,
-}
-
-impl GeoSort {
-    pub fn distance(&self) -> Option<f64> {
-        self.value.map(|value| distance_between_two_points(&self.target_point, &value))
-    }
-}
-
-const LINEAR_SCALE_FACTOR: f64 = 1000.0;

milli/src/search/mod.rs

@@ -7,7 +7,6 @@ use roaring::bitmap::RoaringBitmap;
 pub use self::facet::{FacetDistribution, Filter, DEFAULT_VALUES_PER_FACET};
 pub use self::new::matches::{FormatOptions, MatchBounds, Matcher, MatcherBuilder, MatchingWords};
 use self::new::PartialSearchResult;
-use crate::score_details::ScoreDetails;
 use crate::{
     execute_search, AscDesc, DefaultSearchLogger, DocumentId, Index, Result, SearchContext,
 };
@@ -94,7 +93,7 @@ impl<'a> Search<'a> {
         self
     }
 
-    /// Forces the search to exhaustively compute the number of candidates,
+    /// Force the search to exhastivelly compute the number of candidates,
     /// this will increase the search time but allows finite pagination.
     pub fn exhaustive_number_hits(&mut self, exhaustive_number_hits: bool) -> &mut Search<'a> {
         self.exhaustive_number_hits = exhaustive_number_hits;
@@ -103,7 +102,7 @@ impl<'a> Search<'a> {
 
     pub fn execute(&self) -> Result<SearchResult> {
         let mut ctx = SearchContext::new(self.index, self.rtxn);
-        let PartialSearchResult { located_query_terms, candidates, documents_ids, document_scores } =
+        let PartialSearchResult { located_query_terms, candidates, documents_ids } =
             execute_search(
                 &mut ctx,
                 &self.query,
@@ -125,7 +124,7 @@ impl<'a> Search<'a> {
             None => MatchingWords::default(),
         };
 
-        Ok(SearchResult { matching_words, candidates, document_scores, documents_ids })
+        Ok(SearchResult { matching_words, candidates, documents_ids })
     }
 }
 
@@ -161,8 +160,8 @@ impl fmt::Debug for Search<'_> {
 pub struct SearchResult {
     pub matching_words: MatchingWords,
     pub candidates: RoaringBitmap,
+    // TODO those documents ids should be associated with their criteria scores.
     pub documents_ids: Vec<DocumentId>,
-    pub document_scores: Vec<Vec<ScoreDetails>>,
 }
 
 #[derive(Debug, Clone, Copy, PartialEq, Eq)]

milli/src/search/new/bucket_sort.rs

@@ -3,13 +3,11 @@ use roaring::RoaringBitmap;
 use super::logger::SearchLogger;
 use super::ranking_rules::{BoxRankingRule, RankingRuleQueryTrait};
 use super::SearchContext;
-use crate::score_details::ScoreDetails;
 use crate::search::new::distinct::{apply_distinct_rule, distinct_single_docid, DistinctOutput};
 use crate::Result;
 
 pub struct BucketSortOutput {
     pub docids: Vec<u32>,
-    pub scores: Vec<Vec<ScoreDetails>>,
     pub all_candidates: RoaringBitmap,
 }
 
@@ -33,11 +31,7 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
     };
 
     if universe.len() < from as u64 {
-        return Ok(BucketSortOutput {
-            docids: vec![],
-            scores: vec![],
-            all_candidates: universe.clone(),
-        });
+        return Ok(BucketSortOutput { docids: vec![], all_candidates: universe.clone() });
     }
     if ranking_rules.is_empty() {
         if let Some(distinct_fid) = distinct_fid {
@@ -55,32 +49,22 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
             }
             let mut all_candidates = universe - excluded;
             all_candidates.extend(results.iter().copied());
-            return Ok(BucketSortOutput {
-                scores: vec![Default::default(); results.len()],
-                docids: results,
-                all_candidates,
-            });
+            return Ok(BucketSortOutput { docids: results, all_candidates });
         } else {
-            let docids: Vec<u32> = universe.iter().skip(from).take(length).collect();
-            return Ok(BucketSortOutput {
-                scores: vec![Default::default(); docids.len()],
-                docids,
-                all_candidates: universe.clone(),
-            });
+            let docids = universe.iter().skip(from).take(length).collect();
+            return Ok(BucketSortOutput { docids, all_candidates: universe.clone() });
         };
     }
 
     let ranking_rules_len = ranking_rules.len();
 
     logger.start_iteration_ranking_rule(0, ranking_rules[0].as_ref(), query, universe);
-
     ranking_rules[0].start_iteration(ctx, logger, universe, query)?;
 
-    let mut ranking_rule_scores: Vec<ScoreDetails> = vec![];
-
     let mut ranking_rule_universes: Vec<RoaringBitmap> =
         vec![RoaringBitmap::default(); ranking_rules_len];
     ranking_rule_universes[0] = universe.clone();
+
     let mut cur_ranking_rule_index = 0;
 
     /// Finish iterating over the current ranking rule, yielding
@@ -105,16 +89,11 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
             } else {
                 cur_ranking_rule_index -= 1;
             }
-            // FIXME: check off by one
-            if ranking_rule_scores.len() > cur_ranking_rule_index {
-                ranking_rule_scores.pop();
-            }
         };
     }
 
     let mut all_candidates = universe.clone();
     let mut valid_docids = vec![];
-    let mut valid_scores = vec![];
     let mut cur_offset = 0usize;
 
     macro_rules! maybe_add_to_results {
@@ -125,23 +104,23 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
                 length,
                 logger,
                 &mut valid_docids,
-                &mut valid_scores,
                 &mut all_candidates,
                 &mut ranking_rule_universes,
                 &mut ranking_rules,
                 cur_ranking_rule_index,
                 &mut cur_offset,
                 distinct_fid,
-                &ranking_rule_scores,
                 $candidates,
             )?;
         };
     }
 
     while valid_docids.len() < length {
-        // 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() {
+        // The universe for this bucket is zero or one element, so we don't need to sort
+        // anything, just extend the results and go back to the parent ranking rule.
+        if ranking_rule_universes[cur_ranking_rule_index].len() <= 1 {
+            let bucket = std::mem::take(&mut ranking_rule_universes[cur_ranking_rule_index]);
+            maybe_add_to_results!(bucket);
             back!();
             continue;
         }
@@ -151,8 +130,6 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
             continue;
         };
 
-        ranking_rule_scores.push(next_bucket.score);
-
         logger.next_bucket_ranking_rule(
             cur_ranking_rule_index,
             ranking_rules[cur_ranking_rule_index].as_ref(),
@@ -166,11 +143,10 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
         ranking_rule_universes[cur_ranking_rule_index] -= &next_bucket.candidates;
 
         if cur_ranking_rule_index == ranking_rules_len - 1
+            || next_bucket.candidates.len() <= 1
             || cur_offset + (next_bucket.candidates.len() as usize) < from
         {
             maybe_add_to_results!(next_bucket.candidates);
-            // FIXME: use index based logic like all the other rules so that you don't have to maintain the pop/push?
-            ranking_rule_scores.pop();
             continue;
         }
 
@@ -190,7 +166,7 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
         )?;
     }
 
-    Ok(BucketSortOutput { docids: valid_docids, scores: valid_scores, all_candidates })
+    Ok(BucketSortOutput { docids: valid_docids, all_candidates })
 }
 
 /// Add the candidates to the results. Take `distinct`, `from`, `length`, and `cur_offset`
@@ -203,18 +179,14 @@ fn maybe_add_to_results<'ctx, Q: RankingRuleQueryTrait>(
     logger: &mut dyn SearchLogger<Q>,
 
     valid_docids: &mut Vec<u32>,
-    valid_scores: &mut Vec<Vec<ScoreDetails>>,
     all_candidates: &mut RoaringBitmap,
 
     ranking_rule_universes: &mut [RoaringBitmap],
     ranking_rules: &mut [BoxRankingRule<'ctx, Q>],
-
     cur_ranking_rule_index: usize,
 
     cur_offset: &mut usize,
-
     distinct_fid: Option<u16>,
-    ranking_rule_scores: &[ScoreDetails],
     candidates: RoaringBitmap,
 ) -> Result<()> {
     // First apply the distinct rule on the candidates, reducing the universes if necessary
@@ -259,17 +231,13 @@ fn maybe_add_to_results<'ctx, Q: RankingRuleQueryTrait>(
             let candidates =
                 candidates.iter().take(length - valid_docids.len()).copied().collect::<Vec<_>>();
             logger.add_to_results(&candidates);
-            valid_docids.extend_from_slice(&candidates);
-            valid_scores
-                .extend(std::iter::repeat(ranking_rule_scores.to_owned()).take(candidates.len()));
+            valid_docids.extend(&candidates);
         }
     } else {
         // if we have passed the offset already, add some of the documents (up to the limit)
         let candidates = candidates.iter().take(length - valid_docids.len()).collect::<Vec<u32>>();
         logger.add_to_results(&candidates);
-        valid_docids.extend_from_slice(&candidates);
-        valid_scores
-            .extend(std::iter::repeat(ranking_rule_scores.to_owned()).take(candidates.len()));
+        valid_docids.extend(&candidates);
     }
 
     *cur_offset += candidates.len() as usize;

milli/src/search/new/exact_attribute.rs

@@ -2,7 +2,6 @@ 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};
@@ -245,13 +244,7 @@ impl State {
                 candidates &= universe;
                 (
                     State::AttributeStarts(query_graph.clone(), candidates_per_attribute),
-                    Some(RankingRuleOutput {
-                        query: query_graph,
-                        candidates,
-                        score: ScoreDetails::ExactAttribute(
-                            score_details::ExactAttribute::MatchesFull,
-                        ),
-                    }),
+                    Some(RankingRuleOutput { query: query_graph, candidates }),
                 )
             }
             State::AttributeStarts(query_graph, candidates_per_attribute) => {
@@ -264,24 +257,12 @@ impl State {
                 candidates &= universe;
                 (
                     State::Empty(query_graph.clone()),
-                    Some(RankingRuleOutput {
-                        query: query_graph,
-                        candidates,
-                        score: ScoreDetails::ExactAttribute(
-                            score_details::ExactAttribute::MatchesStart,
-                        ),
-                    }),
+                    Some(RankingRuleOutput { query: query_graph, candidates }),
                 )
             }
             State::Empty(query_graph) => (
                 State::Empty(query_graph.clone()),
-                Some(RankingRuleOutput {
-                    query: query_graph,
-                    candidates: universe.clone(),
-                    score: ScoreDetails::ExactAttribute(
-                        score_details::ExactAttribute::NoExactMatch,
-                    ),
-                }),
+                Some(RankingRuleOutput { query: query_graph, candidates: universe.clone() }),
             ),
         };
         (state, output)

milli/src/search/new/geo_sort.rs

@@ -8,7 +8,6 @@ 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,
@@ -81,7 +80,7 @@ pub struct GeoSort<Q: RankingRuleQueryTrait> {
     field_ids: Option<[u16; 2]>,
     rtree: Option<RTree<GeoPoint>>,
 
-    cached_sorted_docids: VecDeque<(u32, [f64; 2])>,
+    cached_sorted_docids: VecDeque<u32>,
     geo_candidates: RoaringBitmap,
 }
 
@@ -131,7 +130,7 @@ 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);
+                        self.cached_sorted_docids.push_back(point.data.0);
                         if self.cached_sorted_docids.len() >= cache_size {
                             break;
                         }
@@ -143,7 +142,7 @@ 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);
+                        self.cached_sorted_docids.push_front(point.data.0);
                         if self.cached_sorted_docids.len() >= cache_size {
                             break;
                         }
@@ -178,7 +177,7 @@ 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());
+            self.cached_sorted_docids.extend(documents.into_iter().map(|(doc_id, _)| doc_id));
         };
 
         Ok(())
@@ -221,19 +220,12 @@ 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(),
-                score: ScoreDetails::GeoSort(score_details::GeoSort {
-                    target_point: self.point,
-                    ascending: self.ascending,
-                    value: None,
-                }),
-            }));
+            return Ok(Some(RankingRuleOutput { query, candidates: universe.clone() }));
         }
 
         let ascending = self.ascending;
@@ -244,16 +236,11 @@ impl<'ctx, Q: RankingRuleQueryTrait> RankingRule<'ctx, Q> for GeoSort<Q> {
                 cache.pop_back()
             }
         };
-        while let Some((id, point)) = next(&mut self.cached_sorted_docids) {
+        while let Some(id) = 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

@@ -50,7 +50,6 @@ 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};
@@ -119,8 +118,6 @@ 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> {
@@ -142,12 +139,13 @@ impl<'ctx, G: RankingRuleGraphTrait> RankingRule<'ctx, QueryGraph> for GraphBase
                     let mut forbidden_nodes =
                         SmallBitmap::for_interned_values_in(&query_graph.nodes);
                     let mut costs = query_graph.nodes.map(|_| None);
-                    // FIXME: this works because only words uses termsmatchingstrategy at the moment.
+                    let mut cost = 100;
                     for ns in removal_order {
                         for n in ns.iter() {
-                            *costs.get_mut(n) = Some((1, forbidden_nodes.clone()));
+                            *costs.get_mut(n) = Some((cost, forbidden_nodes.clone()));
                         }
                         forbidden_nodes.union(&ns);
+                        cost += 100;
                     }
                     costs
                 }
@@ -164,16 +162,12 @@ 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);
@@ -187,13 +181,17 @@ 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) = all_costs
+        let Some(&cost) = state
+            .all_costs
+            .get(state.graph.query_graph.root_node)
             .iter()
             .find(|c| **c >= state.cur_cost) else {
                 self.state = None;
@@ -209,12 +207,8 @@ 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);
@@ -331,7 +325,7 @@ impl<'ctx, G: RankingRuleGraphTrait> RankingRule<'ctx, QueryGraph> for GraphBase
 
         self.state = Some(state);
 
-        Ok(Some(RankingRuleOutput { query: next_query_graph, candidates: bucket, score }))
+        Ok(Some(RankingRuleOutput { query: next_query_graph, candidates: bucket }))
     }
 
     fn end_iteration(

milli/src/search/new/mod.rs

@@ -44,7 +44,6 @@ 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};
 
@@ -427,15 +426,13 @@ pub fn execute_search(
         )?
     };
 
-    let BucketSortOutput { docids, scores, mut all_candidates } = bucket_sort_output;
-
-    let fields_ids_map = ctx.index.fields_ids_map(ctx.txn)?;
+    let BucketSortOutput { docids, mut all_candidates } = bucket_sort_output;
 
     // The candidates is the universe unless the exhaustive number of hits
     // is requested and a distinct attribute is set.
     if exhaustive_number_hits {
         if let Some(f) = ctx.index.distinct_field(ctx.txn)? {
-            if let Some(distinct_fid) = fields_ids_map.id(f) {
+            if let Some(distinct_fid) = ctx.index.fields_ids_map(ctx.txn)?.id(f) {
                 all_candidates = apply_distinct_rule(ctx, distinct_fid, &all_candidates)?.remaining;
             }
         }
@@ -443,7 +440,6 @@ pub fn execute_search(
 
     Ok(PartialSearchResult {
         candidates: all_candidates,
-        document_scores: scores,
         documents_ids: docids,
         located_query_terms,
     })
@@ -495,5 +491,4 @@ pub struct PartialSearchResult {
     pub located_query_terms: Option<Vec<LocatedQueryTerm>>,
     pub candidates: RoaringBitmap,
     pub documents_ids: Vec<DocumentId>,
-    pub document_scores: Vec<Vec<ScoreDetails>>,
 }

milli/src/search/new/query_term/parse_query.rs

@@ -79,7 +79,7 @@ pub fn located_query_terms_from_tokens(
             TokenKind::Separator(separator_kind) => {
                 // add penalty for hard separators
                 if let SeparatorKind::Hard = separator_kind {
-                    position = position.wrapping_add(7);
+                    position = position.wrapping_add(1);
                 }
 
                 phrase = 'phrase: {

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

@@ -49,15 +49,10 @@ impl<G: RankingRuleGraphTrait> RankingRuleGraph<G> {
                 if let Some((cost_of_ignoring, forbidden_nodes)) =
                     cost_of_ignoring_node.get(dest_idx)
                 {
-                    let dest = graph_nodes.get(dest_idx);
-                    let dest_size = match &dest.data {
-                        QueryNodeData::Term(term) => term.term_ids.len(),
-                        _ => panic!(),
-                    };
                     let new_edge_id = edges_store.insert(Some(Edge {
                         source_node: source_id,
                         dest_node: dest_idx,
-                        cost: *cost_of_ignoring * dest_size as u32,
+                        cost: *cost_of_ignoring,
                         condition: None,
                         nodes_to_skip: forbidden_nodes.clone(),
                     }));

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

@@ -1,7 +1,6 @@
 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;
@@ -85,8 +84,4 @@ 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

@@ -2,7 +2,6 @@ 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;
@@ -69,7 +68,7 @@ impl RankingRuleGraphTrait for FidGraph {
         }
 
         let mut edges = vec![];
-        for fid in all_fields.iter().copied() {
+        for fid in all_fields {
             // TODO: We can improve performances and relevancy by storing
             //       the term subsets associated to each field ids fetched.
             edges.push((
@@ -81,35 +80,6 @@ impl RankingRuleGraphTrait for FidGraph {
             ));
         }
 
-        // always lookup the max_fid if we don't already and add an artificial condition for max scoring
-        let max_fid: Option<u16> = {
-            if let Some(max_fid) = ctx
-                .index
-                .searchable_fields_ids(ctx.txn)?
-                .map(|field_ids| field_ids.into_iter().max())
-            {
-                max_fid
-            } else {
-                ctx.index.fields_ids_map(ctx.txn)?.ids().max()
-            }
-        };
-
-        if let Some(max_fid) = max_fid {
-            if !all_fields.contains(&max_fid) {
-                edges.push((
-                    max_fid as u32 * term.term_ids.len() as u32, // TODO improve the fid score i.e. fid^10.
-                    conditions_interner.insert(FidCondition {
-                        term: term.clone(), // TODO remove this ugly clone
-                        fid: max_fid,
-                    }),
-                ));
-            }
-        }
-
         Ok(edges)
     }
-
-    fn rank_to_score(rank: Rank) -> ScoreDetails {
-        ScoreDetails::Fid(rank)
-    }
 }

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

@@ -41,7 +41,6 @@ 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 {
@@ -111,9 +110,6 @@ 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

@@ -2,7 +2,6 @@ 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;
@@ -106,20 +105,8 @@ impl RankingRuleGraphTrait for PositionGraph {
             ));
         }
 
-        // artificial empty condition for computing max cost
-        let max_cost = term.term_ids.len() as u32 * 10;
-        edges.push((
-            max_cost,
-            conditions_interner
-                .insert(PositionCondition { term: term.clone(), positions: Vec::default() }),
-        ));
-
         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/build.rs

@@ -1,6 +1,7 @@
 #![allow(clippy::too_many_arguments)]
 
 use super::ProximityCondition;
+use crate::proximity::MAX_DISTANCE;
 use crate::search::new::interner::{DedupInterner, Interned};
 use crate::search::new::query_term::LocatedQueryTermSubset;
 use crate::search::new::SearchContext;
@@ -47,7 +48,7 @@ pub fn build_edges(
     }
 
     conditions.push((
-        (7 + right_ngram_length) as u32,
+        MAX_DISTANCE - 1 + right_ngram_length as u32,
         conditions_interner.insert(ProximityCondition::Term { term: right_term.clone() }),
     ));
 

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

@@ -4,7 +4,6 @@ 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;
@@ -37,8 +36,4 @@ 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

@@ -1,7 +1,6 @@
 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;
@@ -76,8 +75,4 @@ 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

@@ -1,7 +1,6 @@
 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;
@@ -42,10 +41,9 @@ impl RankingRuleGraphTrait for WordsGraph {
         _from: Option<&LocatedQueryTermSubset>,
         to_term: &LocatedQueryTermSubset,
     ) -> 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))
+        Ok(vec![(
+            to_term.term_ids.len() as u32,
+            conditions_interner.insert(WordsCondition { term: to_term.clone() }),
+        )])
     }
 }

milli/src/search/new/ranking_rules.rs

@@ -2,7 +2,6 @@ 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`]
@@ -67,6 +66,4 @@ 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

@@ -1,11 +1,9 @@
-use heed::BytesDecode;
 use roaring::RoaringBitmap;
 
 use super::logger::SearchLogger;
 use super::{RankingRule, RankingRuleOutput, RankingRuleQueryTrait, SearchContext};
-use crate::heed_codec::facet::{FacetGroupKeyCodec, OrderedF64Codec};
-use crate::heed_codec::{ByteSliceRefCodec, StrRefCodec};
-use crate::score_details::{self, ScoreDetails};
+use crate::heed_codec::facet::FacetGroupKeyCodec;
+use crate::heed_codec::ByteSliceRefCodec;
 use crate::search::facet::{ascending_facet_sort, descending_facet_sort};
 use crate::{FieldId, Index, Result};
 
@@ -69,7 +67,7 @@ impl<'ctx, Query> Sort<'ctx, Query> {
 impl<'ctx, Query: RankingRuleQueryTrait> RankingRule<'ctx, Query> for Sort<'ctx, Query> {
     fn id(&self) -> String {
         let Self { field_name, is_ascending, .. } = self;
-        format!("{field_name}:{}", if *is_ascending { "asc" } else { "desc" })
+        format!("{field_name}:{}", if *is_ascending { "asc" } else { "desc " })
     }
     fn start_iteration(
         &mut self,
@@ -120,43 +118,12 @@ 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, value) = r?;
-                        Ok(RankingRuleOutput {
-                            query: query_graph.clone(),
-                            candidates: docids,
-                            score: ScoreDetails::Sort(score_details::Sort {
-                                field_name: field_name.clone(),
-                                ascending,
-                                value,
-                            }),
-                        })
+                        let (docids, _) = r?;
+                        Ok(RankingRuleOutput { query: query_graph.clone(), candidates: docids })
                     },
                 )))
             }
@@ -183,15 +150,7 @@ 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(),
-                score: ScoreDetails::Sort(score_details::Sort {
-                    field_name: self.field_name.clone(),
-                    ascending: self.is_ascending,
-                    value: serde_json::Value::Null,
-                }),
-            }))
+            Ok(Some(RankingRuleOutput { query, candidates: universe.clone() }))
         }
     }
 

milli/src/update/index_documents/extract/extract_fid_word_count_docids.rs

@@ -1,6 +1,6 @@
 use std::collections::HashMap;
 use std::fs::File;
-use std::io;
+use std::{cmp, io};
 
 use grenad::Sorter;
 
@@ -54,10 +54,11 @@ pub fn extract_fid_word_count_docids<R: io::Read + io::Seek>(
         }
 
         for position in read_u32_ne_bytes(value) {
-            let (field_id, _) = relative_from_absolute_position(position);
+            let (field_id, position) = relative_from_absolute_position(position);
+            let word_count = position as u32 + 1;
 
             let value = document_fid_wordcount.entry(field_id as FieldId).or_insert(0);
-            *value += 1;
+            *value = cmp::max(*value, word_count);
         }
     }
 
@@ -82,7 +83,7 @@ fn drain_document_fid_wordcount_into_sorter(
     let mut key_buffer = Vec::new();
 
     for (fid, count) in document_fid_wordcount.drain() {
-        if count <= 30 {
+        if count <= 10 {
             key_buffer.clear();
             key_buffer.extend_from_slice(&fid.to_be_bytes());
             key_buffer.push(count as u8);

milli/src/update/index_documents/extract/extract_word_pair_proximity_docids.rs

@@ -91,7 +91,7 @@ fn document_word_positions_into_sorter(
     while !word_positions_heap.is_empty() {
         while let Some(peeked_word_position) = word_positions_heap.pop() {
             ordered_peeked_word_positions.push(peeked_word_position);
-            if ordered_peeked_word_positions.len() == 7 {
+            if ordered_peeked_word_positions.len() == MAX_DISTANCE as usize - 1 {
                 break;
             }
         }