diff --git a/milli/src/search/facet/facet_distribution.rs b/milli/src/search/facet/facet_distribution.rs
index 45ce13a28..f6ef51ccd 100644
--- a/milli/src/search/facet/facet_distribution.rs
+++ b/milli/src/search/facet/facet_distribution.rs
@@ -240,42 +240,49 @@ impl<'a> FacetDistribution<'a> {
     }
 
     fn facet_values(&self, field_id: FieldId) -> heed::Result<BTreeMap<String, u64>> {
-        use FacetType::{Number, String};
+        // use FacetType::{Number, String};
 
-        match self.candidates {
-            Some(ref candidates) => {
-                // Classic search, candidates were specified, we must return facet values only related
-                // to those candidates. We also enter here for facet strings for performance reasons.
-                let mut distribution = BTreeMap::new();
-                if candidates.len() <= CANDIDATES_THRESHOLD {
-                    self.facet_distribution_from_documents(
-                        field_id,
-                        Number,
-                        candidates,
-                        &mut distribution,
-                    )?;
-                    self.facet_distribution_from_documents(
-                        field_id,
-                        String,
-                        candidates,
-                        &mut distribution,
-                    )?;
-                } else {
-                    self.facet_numbers_distribution_from_facet_levels(
-                        field_id,
-                        candidates,
-                        &mut distribution,
-                    )?;
-                    self.facet_strings_distribution_from_facet_levels(
-                        field_id,
-                        candidates,
-                        &mut distribution,
-                    )?;
-                }
-                Ok(distribution)
-            }
-            None => self.facet_values_from_raw_facet_database(field_id),
+        let candidates = match self.candidates.as_ref() {
+            Some(candidates) => candidates.clone(),
+            None => todo!("fetch candidates"),
+        };
+
+        let mut distribution = BTreeMap::new();
+
+        let number_distribution = facet_distribution_iter::count_iterate_over_facet_distribution(
+            self.rtxn,
+            self.index
+                .facet_id_f64_docids
+                .remap_key_type::<FacetGroupKeyCodec<ByteSliceRefCodec>>(),
+            field_id,
+            &candidates,
+        )?;
+
+        for (count, facet_key, _) in number_distribution {
+            let facet_key = OrderedF64Codec::bytes_decode(facet_key).unwrap();
+            distribution.insert(facet_key.to_string(), count);
         }
+
+        let string_distribution = facet_distribution_iter::count_iterate_over_facet_distribution(
+            self.rtxn,
+            self.index
+                .facet_id_string_docids
+                .remap_key_type::<FacetGroupKeyCodec<ByteSliceRefCodec>>(),
+            field_id,
+            &candidates,
+        )?;
+
+        for (count, facet_key, any_docid) in string_distribution {
+            let facet_key = StrRefCodec::bytes_decode(facet_key).unwrap();
+
+            let key: (FieldId, _, &str) = (field_id, any_docid, facet_key);
+            let original_string =
+                self.index.field_id_docid_facet_strings.get(self.rtxn, &key)?.unwrap().to_owned();
+
+            distribution.insert(original_string, count);
+        }
+
+        Ok(distribution)
     }
 
     pub fn compute_stats(&self) -> Result<BTreeMap<String, (f64, f64)>> {
diff --git a/milli/src/search/facet/facet_distribution_iter.rs b/milli/src/search/facet/facet_distribution_iter.rs
index 0e1efaa0e..acd936eff 100644
--- a/milli/src/search/facet/facet_distribution_iter.rs
+++ b/milli/src/search/facet/facet_distribution_iter.rs
@@ -1,5 +1,5 @@
 use std::cmp::Reverse;
-use std::collections::{BTreeMap, BinaryHeap};
+use std::collections::BinaryHeap;
 use std::ops::ControlFlow;
 
 use heed::Result;
@@ -46,15 +46,12 @@ where
     }
 }
 
-pub fn count_iterate_over_facet_distribution<'t, CB>(
+pub fn count_iterate_over_facet_distribution<'t>(
     rtxn: &'t heed::RoTxn<'t>,
     db: heed::Database<FacetGroupKeyCodec<ByteSliceRefCodec>, FacetGroupValueCodec>,
     field_id: u16,
     candidates: &RoaringBitmap,
-) -> Result<Vec<(u64, &'t [u8])>>
-where
-    CB: FnMut(&'t [u8], u64, DocumentId) -> Result<ControlFlow<()>>,
-{
+) -> Result<Vec<(u64, &'t [u8], u32)>> {
     #[derive(Debug, PartialOrd, Ord, PartialEq, Eq)]
     struct LevelEntry<'t> {
         /// The number of candidates in this entry.
@@ -65,6 +62,8 @@ where
         left_bound: &'t [u8],
         /// The number of keys we must look for after `left_bound`.
         group_size: u8,
+        /// Any docid in the set of matching documents. Used to find the original facet string.
+        any_docid: u32,
     }
 
     // Represents the list of keys that we must explore.
@@ -88,20 +87,23 @@ where
             if key.field_id != field_id {
                 break;
             }
-            let count = value.bitmap.intersection_len(&candidates);
+            let intersection = value.bitmap & candidates;
+            let count = intersection.len();
             if count != 0 {
                 heap.push(LevelEntry {
                     count,
                     level: Reverse(key.level),
                     left_bound: key.left_bound,
                     group_size: value.size,
+                    any_docid: intersection.min().unwrap(),
                 });
             }
         }
 
-        while let Some(LevelEntry { count, level, left_bound, group_size }) = heap.pop() {
+        while let Some(LevelEntry { count, level, left_bound, group_size, any_docid }) = heap.pop()
+        {
             if let Reverse(0) = level {
-                results.push((count, left_bound));
+                results.push((count, left_bound, any_docid));
                 // TODO better just call the user callback and ask for a ControlFlow
                 if results.len() == 20 {
                     break;
@@ -116,13 +118,15 @@ where
                     if key.field_id != field_id {
                         break;
                     }
-                    let count = value.bitmap.intersection_len(&candidates);
+                    let intersection = value.bitmap & candidates;
+                    let count = intersection.len();
                     if count != 0 {
                         heap.push(LevelEntry {
                             count,
                             level: Reverse(key.level),
                             left_bound: key.left_bound,
                             group_size: value.size,
+                            any_docid: intersection.min().unwrap(),
                         });
                     }
                 }