Move to the hgg crate

milli/src/distance.rs

@@ -18,3 +18,17 @@ impl Metric<Vec<f32>> for DotProduct {
         dist.to_bits()
     }
 }
+
+#[derive(Debug, Default, Clone, Copy, Serialize, Deserialize)]
+pub struct Euclidean;
+
+impl Metric<Vec<f32>> for Euclidean {
+    type Unit = u32;
+
+    fn distance(&self, a: &Vec<f32>, b: &Vec<f32>) -> Self::Unit {
+        let squared: f32 = a.iter().zip(b).map(|(a, b)| (a - b).powi(2)).sum();
+        let dist = squared.sqrt();
+        debug_assert!(!dist.is_nan());
+        dist.to_bits()
+    }
+}

milli/src/index.rs

@@ -8,12 +8,11 @@ use charabia::{Language, Script};
 use heed::flags::Flags;
 use heed::types::*;
 use heed::{CompactionOption, Database, PolyDatabase, RoTxn, RwTxn};
-use rand_pcg::Pcg32;
 use roaring::RoaringBitmap;
 use rstar::RTree;
 use time::OffsetDateTime;
 
-use crate::dot_product::DotProduct;
+use crate::distance::Euclidean;
 use crate::error::{InternalError, UserError};
 use crate::facet::FacetType;
 use crate::fields_ids_map::FieldsIdsMap;
@@ -28,8 +27,8 @@ use crate::{
     Result, RoaringBitmapCodec, RoaringBitmapLenCodec, Search, U8StrStrCodec, BEU16, BEU32,
 };
 
-/// The HNSW data-structure that we serialize, fill and search in.
-pub type Hnsw = hnsw::Hnsw<DotProduct, Vec<f32>, Pcg32, 12, 24>;
+/// The HGG data-structure that we serialize, fill and search in.
+pub type Hgg = hgg::Hgg<Euclidean, Vec<f32>, DocumentId>;
 
 pub const DEFAULT_MIN_WORD_LEN_ONE_TYPO: u8 = 5;
 pub const DEFAULT_MIN_WORD_LEN_TWO_TYPOS: u8 = 9;
@@ -47,7 +46,7 @@ pub mod main_key {
     pub const FIELDS_IDS_MAP_KEY: &str = "fields-ids-map";
     pub const GEO_FACETED_DOCUMENTS_IDS_KEY: &str = "geo-faceted-documents-ids";
     pub const GEO_RTREE_KEY: &str = "geo-rtree";
-    pub const VECTOR_HNSW_KEY: &str = "vector-hnsw";
+    pub const VECTOR_HGG_KEY: &str = "vector-hgg";
     pub const HARD_EXTERNAL_DOCUMENTS_IDS_KEY: &str = "hard-external-documents-ids";
     pub const NUMBER_FACETED_DOCUMENTS_IDS_PREFIX: &str = "number-faceted-documents-ids";
     pub const PRIMARY_KEY_KEY: &str = "primary-key";
@@ -92,7 +91,6 @@ pub mod db_name {
     pub const FACET_ID_STRING_DOCIDS: &str = "facet-id-string-docids";
     pub const FIELD_ID_DOCID_FACET_F64S: &str = "field-id-docid-facet-f64s";
     pub const FIELD_ID_DOCID_FACET_STRINGS: &str = "field-id-docid-facet-strings";
-    pub const VECTOR_ID_DOCID: &str = "vector-id-docids";
     pub const DOCUMENTS: &str = "documents";
     pub const SCRIPT_LANGUAGE_DOCIDS: &str = "script_language_docids";
 }
@@ -156,9 +154,6 @@ pub struct Index {
     /// Maps the document id, the facet field id and the strings.
     pub field_id_docid_facet_strings: Database<FieldDocIdFacetStringCodec, Str>,
 
-    /// Maps a vector id to the document id that have it.
-    pub vector_id_docid: Database<OwnedType<BEU32>, OwnedType<BEU32>>,
-
     /// Maps the document id to the document as an obkv store.
     pub(crate) documents: Database<OwnedType<BEU32>, ObkvCodec>,
 }
@@ -172,7 +167,7 @@ impl Index {
     ) -> Result<Index> {
         use db_name::*;
 
-        options.max_dbs(24);
+        options.max_dbs(23);
         unsafe { options.flag(Flags::MdbAlwaysFreePages) };
 
         let env = options.open(path)?;
@@ -212,7 +207,6 @@ impl Index {
             env.create_database(&mut wtxn, Some(FIELD_ID_DOCID_FACET_F64S))?;
         let field_id_docid_facet_strings =
             env.create_database(&mut wtxn, Some(FIELD_ID_DOCID_FACET_STRINGS))?;
-        let vector_id_docid = env.create_database(&mut wtxn, Some(VECTOR_ID_DOCID))?;
         let documents = env.create_database(&mut wtxn, Some(DOCUMENTS))?;
         wtxn.commit()?;
 
@@ -241,7 +235,6 @@ impl Index {
             facet_id_is_empty_docids,
             field_id_docid_facet_f64s,
             field_id_docid_facet_strings,
-            vector_id_docid,
             documents,
         })
     }
@@ -513,22 +506,22 @@ impl Index {
         }
     }
 
-    /* vector HNSW */
+    /* vector HGG */
 
-    /// Writes the provided `hnsw`.
-    pub(crate) fn put_vector_hnsw(&self, wtxn: &mut RwTxn, hnsw: &Hnsw) -> heed::Result<()> {
-        self.main.put::<_, Str, SerdeBincode<Hnsw>>(wtxn, main_key::VECTOR_HNSW_KEY, hnsw)
+    /// Writes the provided `hgg`.
+    pub(crate) fn put_vector_hgg(&self, wtxn: &mut RwTxn, hgg: &Hgg) -> heed::Result<()> {
+        self.main.put::<_, Str, SerdeBincode<Hgg>>(wtxn, main_key::VECTOR_HGG_KEY, hgg)
     }
 
-    /// Delete the `hnsw`.
-    pub(crate) fn delete_vector_hnsw(&self, wtxn: &mut RwTxn) -> heed::Result<bool> {
-        self.main.delete::<_, Str>(wtxn, main_key::VECTOR_HNSW_KEY)
+    /// Delete the `hgg`.
+    pub(crate) fn delete_vector_hgg(&self, wtxn: &mut RwTxn) -> heed::Result<bool> {
+        self.main.delete::<_, Str>(wtxn, main_key::VECTOR_HGG_KEY)
     }
 
-    /// Returns the `hnsw`.
-    pub fn vector_hnsw(&self, rtxn: &RoTxn) -> Result<Option<Hnsw>> {
-        match self.main.get::<_, Str, SerdeBincode<Hnsw>>(rtxn, main_key::VECTOR_HNSW_KEY)? {
-            Some(hnsw) => Ok(Some(hnsw)),
+    /// Returns the `hgg`.
+    pub fn vector_hgg(&self, rtxn: &RoTxn) -> Result<Option<Hgg>> {
+        match self.main.get::<_, Str, SerdeBincode<Hgg>>(rtxn, main_key::VECTOR_HGG_KEY)? {
+            Some(hgg) => Ok(Some(hgg)),
             None => Ok(None),
         }
     }

milli/src/lib.rs

@@ -10,7 +10,7 @@ pub mod documents;
 
 mod asc_desc;
 mod criterion;
-pub mod dot_product;
+mod distance;
 mod error;
 mod external_documents_ids;
 pub mod facet;

milli/src/search/new/mod.rs

@@ -28,7 +28,6 @@ use db_cache::DatabaseCache;
 use exact_attribute::ExactAttribute;
 use graph_based_ranking_rule::{Exactness, Fid, Position, Proximity, Typo};
 use heed::RoTxn;
-use hnsw::Searcher;
 use interner::{DedupInterner, Interner};
 pub use logger::visual::VisualSearchLogger;
 pub use logger::{DefaultSearchLogger, SearchLogger};
@@ -40,7 +39,7 @@ use ranking_rules::{
 use resolve_query_graph::{compute_query_graph_docids, PhraseDocIdsCache};
 use roaring::RoaringBitmap;
 use sort::Sort;
-use space::Neighbor;
+use space::{KnnMap, Neighbor};
 
 use self::geo_sort::GeoSort;
 pub use self::geo_sort::Strategy as GeoSortStrategy;
@@ -48,9 +47,7 @@ use self::graph_based_ranking_rule::Words;
 use self::interner::Interned;
 use crate::score_details::{ScoreDetails, ScoringStrategy};
 use crate::search::new::distinct::apply_distinct_rule;
-use crate::{
-    AscDesc, DocumentId, Filter, Index, Member, Result, TermsMatchingStrategy, UserError, BEU32,
-};
+use crate::{AscDesc, DocumentId, Filter, Index, Member, Result, TermsMatchingStrategy, UserError};
 
 /// A structure used throughout the execution of a search query.
 pub struct SearchContext<'ctx> {
@@ -450,26 +447,15 @@ pub fn execute_search(
     let docids = match vector {
         Some(vector) => {
             // return the nearest documents that are also part of the candidates.
-            let mut searcher = Searcher::new();
-            let hnsw = ctx.index.vector_hnsw(ctx.txn)?.unwrap_or_default();
-            let ef = hnsw.len().min(100);
-            let mut dest = vec![Neighbor { index: 0, distance: 0 }; ef];
-            let neighbors = hnsw.nearest(&vector, ef, &mut searcher, &mut dest[..]);
-
-            let mut docids = Vec::new();
-            for Neighbor { index, distance } in neighbors.iter() {
-                let index = BEU32::new(*index as u32);
-                let docid = ctx.index.vector_id_docid.get(ctx.txn, &index)?.unwrap().get();
-                dbg!(distance, f32::from_bits(*distance));
-                if universe.contains(docid) {
-                    docids.push(docid);
-                    if docids.len() == length {
-                        break;
-                    }
-                }
-            }
-
-            docids
+            let hgg = ctx.index.vector_hgg(ctx.txn)?.unwrap_or_default();
+            hgg.knn_values(&vector, 100)
+                .into_iter()
+                .filter(|(Neighbor { distance, .. }, docid)| {
+                    dbg!(distance, f32::from_bits(*distance));
+                    universe.contains(**docid)
+                })
+                .map(|(_, docid)| *docid)
+                .collect()
         }
         // return the search docids if the vector field is not specified
         None => docids,

milli/src/update/clear_documents.rs

@@ -39,7 +39,6 @@ impl<'t, 'u, 'i> ClearDocuments<'t, 'u, 'i> {
             facet_id_is_empty_docids,
             field_id_docid_facet_f64s,
             field_id_docid_facet_strings,
-            vector_id_docid,
             documents,
         } = self.index;
 
@@ -58,7 +57,7 @@ impl<'t, 'u, 'i> ClearDocuments<'t, 'u, 'i> {
         self.index.put_field_distribution(self.wtxn, &FieldDistribution::default())?;
         self.index.delete_geo_rtree(self.wtxn)?;
         self.index.delete_geo_faceted_documents_ids(self.wtxn)?;
-        self.index.delete_vector_hnsw(self.wtxn)?;
+        self.index.delete_vector_hgg(self.wtxn)?;
 
         // We clean all the faceted documents ids.
         for field_id in faceted_fields {
@@ -97,7 +96,6 @@ impl<'t, 'u, 'i> ClearDocuments<'t, 'u, 'i> {
         facet_id_string_docids.clear(self.wtxn)?;
         field_id_docid_facet_f64s.clear(self.wtxn)?;
         field_id_docid_facet_strings.clear(self.wtxn)?;
-        vector_id_docid.clear(self.wtxn)?;
         documents.clear(self.wtxn)?;
 
         Ok(number_of_documents)

milli/src/update/delete_documents.rs

@@ -240,7 +240,6 @@ impl<'t, 'u, 'i> DeleteDocuments<'t, 'u, 'i> {
             facet_id_exists_docids,
             facet_id_is_null_docids,
             facet_id_is_empty_docids,
-            vector_id_docid,
             documents,
         } = self.index;
         // Remove from the documents database
@@ -275,6 +274,8 @@ impl<'t, 'u, 'i> DeleteDocuments<'t, 'u, 'i> {
             &mut words_to_delete,
         )?;
 
+        todo!("delete the documents from the Hgg datastructure");
+
         // We construct an FST set that contains the words to delete from the words FST.
         let words_to_delete = fst::Set::from_iter(words_to_delete.difference(&words_to_keep))?;
 

milli/src/update/index_documents/typed_chunk.rs

@@ -9,8 +9,8 @@ use charabia::{Language, Script};
 use grenad::MergerBuilder;
 use heed::types::ByteSlice;
 use heed::RwTxn;
-use hnsw::Searcher;
 use roaring::RoaringBitmap;
+use space::KnnInsert;
 
 use super::helpers::{
     self, merge_ignore_values, serialize_roaring_bitmap, valid_lmdb_key, CursorClonableMmap,
@@ -19,7 +19,7 @@ use super::{ClonableMmap, MergeFn};
 use crate::facet::FacetType;
 use crate::update::facet::FacetsUpdate;
 use crate::update::index_documents::helpers::as_cloneable_grenad;
-use crate::{lat_lng_to_xyz, CboRoaringBitmapCodec, DocumentId, GeoPoint, Index, Result, BEU32};
+use crate::{lat_lng_to_xyz, CboRoaringBitmapCodec, DocumentId, GeoPoint, Index, Result};
 
 pub(crate) enum TypedChunk {
     FieldIdDocidFacetStrings(grenad::Reader<CursorClonableMmap>),
@@ -225,19 +225,16 @@ pub(crate) fn write_typed_chunk_into_index(
             index.put_geo_faceted_documents_ids(wtxn, &geo_faceted_docids)?;
         }
         TypedChunk::VectorPoints(vector_points) => {
-            let mut hnsw = index.vector_hnsw(wtxn)?.unwrap_or_default();
-            let mut searcher = Searcher::new();
-
+            let mut hgg = index.vector_hgg(wtxn)?.unwrap_or_default();
             let mut cursor = vector_points.into_cursor()?;
             while let Some((key, value)) = cursor.move_on_next()? {
                 // convert the key back to a u32 (4 bytes)
                 let docid = key.try_into().map(DocumentId::from_be_bytes).unwrap();
-                // convert the vector back to a Vec<f32>
-                let vector: Vec<f32> = pod_collect_to_vec(value);
-                let vector_id = hnsw.insert(vector, &mut searcher) as u32;
-                index.vector_id_docid.put(wtxn, &BEU32::new(vector_id), &BEU32::new(docid))?;
+                // convert the vector back to a Vec<f32> and insert it.
+                // TODO enable again when the library is fixed
+                hgg.insert(pod_collect_to_vec(value), docid);
             }
-            index.put_vector_hnsw(wtxn, &hnsw)?;
+            index.put_vector_hgg(wtxn, &hgg)?;
         }
         TypedChunk::ScriptLanguageDocids(hash_pair) => {
             let mut buffer = Vec::new();