rng_query_operator

rust/index/src/spann/types.rs

@@ -19,10 +19,11 @@ use crate::{
     hnsw_provider::{
         HnswIndexProvider, HnswIndexProviderCreateError, HnswIndexProviderForkError, HnswIndexRef,
     },
+    spann::utils::cluster,
     Index, IndexUuid,
 };
 
-use super::utils::{cluster, KMeansAlgorithmInput, KMeansError};
+use super::utils::{rng_query, KMeansAlgorithmInput, KMeansError};
 
 pub struct VersionsMapInner {
     pub versions_map: HashMap<u32, u32>,
@@ -363,68 +364,16 @@ impl SpannIndexWriter {
         &self,
         query: &[f32],
     ) -> Result<(Vec<usize>, Vec<f32>, Vec<Vec<f32>>), SpannIndexWriterError> {
-        let mut nearby_ids: Vec<usize> = vec![];
-        let mut nearby_distances: Vec<f32> = vec![];
-        let mut embeddings: Vec<Vec<f32>> = vec![];
-        {
-            let read_guard = self.hnsw_index.inner.read();
-            let allowed_ids = vec![];
-            let disallowed_ids = vec![];
-            let (ids, distances) = read_guard
-                .query(
-                    query,
-                    NUM_CENTROIDS_TO_SEARCH as usize,
-                    &allowed_ids,
-                    &disallowed_ids,
-                )
-                .map_err(|_| SpannIndexWriterError::HnswIndexSearchError)?;
-            // Get the embeddings also for distance computation.
-            // Normalization is idempotent and since we write normalized embeddings
-            // to the hnsw index, we'll get the same embeddings after denormalization.
-            for (id, distance) in ids.iter().zip(distances.iter()) {
-                if *distance <= (1_f32 + QUERY_EPSILON) * distances[0] {
-                    nearby_ids.push(*id);
-                    nearby_distances.push(*distance);
-                }
-            }
-            // Get the embeddings also for distance computation.
-            for id in nearby_ids.iter() {
-                let emb = read_guard
-                    .get(*id)
-                    .map_err(|_| SpannIndexWriterError::HnswIndexSearchError)?
-                    .ok_or(SpannIndexWriterError::HnswIndexSearchError)?;
-                embeddings.push(emb);
-            }
-        }
-        // Apply the RNG rule to prune.
-        let mut res_ids = vec![];
-        let mut res_distances = vec![];
-        let mut res_embeddings: Vec<Vec<f32>> = vec![];
-        // Embeddings that were obtained are already normalized.
-        for (id, (distance, embedding)) in nearby_ids
-            .iter()
-            .zip(nearby_distances.iter().zip(embeddings))
-        {
-            let mut rng_accepted = true;
-            for nbr_embedding in res_embeddings.iter() {
-                // Embeddings are already normalized so no need to normalize again.
-                let dist = self
-                    .distance_function
-                    .distance(&embedding[..], &nbr_embedding[..]);
-                if RNG_FACTOR * dist <= *distance {
-                    rng_accepted = false;
-                    break;
-                }
-            }
-            if !rng_accepted {
-                continue;
-            }
-            res_ids.push(*id);
-            res_distances.push(*distance);
-            res_embeddings.push(embedding);
-        }
-
-        Ok((res_ids, res_distances, res_embeddings))
+        rng_query(
+            query,
+            self.hnsw_index.clone(),
+            NUM_CENTROIDS_TO_SEARCH as usize,
+            QUERY_EPSILON,
+            RNG_FACTOR,
+            self.distance_function.clone(),
+        )
+        .await
+        .map_err(|_| SpannIndexWriterError::HnswIndexSearchError)
     }
 
     async fn is_outdated(

rust/index/src/spann/utils.rs

@@ -5,6 +5,8 @@ use chroma_error::{ChromaError, ErrorCodes};
 use rand::{seq::SliceRandom, Rng};
 use thiserror::Error;
 
+use crate::{hnsw_provider::HnswIndexRef, Index};
+
 // TODO(Sanket): I don't understand why the reference implementation defined
 // max_distance this way.
 // TODO(Sanket): Make these configurable.
@@ -501,6 +503,82 @@ pub fn cluster(input: &mut KMeansAlgorithmInput) -> Result<KMeansAlgorithmOutput
     })
 }
 
+#[derive(Error, Debug)]
+pub enum RngQueryError {
+    #[error("Error searching Hnsw graph")]
+    HnswSearchError,
+}
+
+impl ChromaError for RngQueryError {
+    fn code(&self) -> ErrorCodes {
+        match self {
+            Self::HnswSearchError => ErrorCodes::Internal,
+        }
+    }
+}
+
+// Assumes that query is already normalized.
+pub async fn rng_query(
+    normalized_query: &[f32],
+    hnsw_index: HnswIndexRef,
+    k: usize,
+    rng_epsilon: f32,
+    rng_factor: f32,
+    distance_function: DistanceFunction,
+) -> Result<(Vec<usize>, Vec<f32>, Vec<Vec<f32>>), RngQueryError> {
+    let mut nearby_ids: Vec<usize> = vec![];
+    let mut nearby_distances: Vec<f32> = vec![];
+    let mut embeddings: Vec<Vec<f32>> = vec![];
+    {
+        let read_guard = hnsw_index.inner.read();
+        let allowed_ids = vec![];
+        let disallowed_ids = vec![];
+        let (ids, distances) = read_guard
+            .query(normalized_query, k, &allowed_ids, &disallowed_ids)
+            .map_err(|_| RngQueryError::HnswSearchError)?;
+        for (id, distance) in ids.iter().zip(distances.iter()) {
+            if *distance <= (1_f32 + rng_epsilon) * distances[0] {
+                nearby_ids.push(*id);
+                nearby_distances.push(*distance);
+            }
+        }
+        // Get the embeddings also for distance computation.
+        for id in nearby_ids.iter() {
+            let emb = read_guard
+                .get(*id)
+                .map_err(|_| RngQueryError::HnswSearchError)?
+                .ok_or(RngQueryError::HnswSearchError)?;
+            embeddings.push(emb);
+        }
+    }
+    // Apply the RNG rule to prune.
+    let mut res_ids = vec![];
+    let mut res_distances = vec![];
+    let mut res_embeddings: Vec<Vec<f32>> = vec![];
+    // Embeddings that were obtained are already normalized.
+    for (id, (distance, embedding)) in nearby_ids
+        .iter()
+        .zip(nearby_distances.iter().zip(embeddings))
+    {
+        let mut rng_accepted = true;
+        for nbr_embedding in res_embeddings.iter() {
+            let dist = distance_function.distance(&embedding[..], &nbr_embedding[..]);
+            if rng_factor * dist <= *distance {
+                rng_accepted = false;
+                break;
+            }
+        }
+        if !rng_accepted {
+            continue;
+        }
+        res_ids.push(*id);
+        res_distances.push(*distance);
+        res_embeddings.push(embedding);
+    }
+
+    Ok((res_ids, res_distances, res_embeddings))
+}
+
 #[cfg(test)]
 mod tests {
     use std::collections::HashMap;

rust/worker/src/execution/operators/mod.rs

@@ -9,6 +9,7 @@ pub(super) mod partition;
 pub(super) mod pull_log;
 pub(super) mod record_segment_prefetch;
 pub(super) mod register;
+pub(super) mod spann_centers_search;
 pub(super) mod write_segments;
 
 // Required for benchmark

rust/worker/src/execution/operators/spann_centers_search.rs

@@ -0,0 +1,83 @@
+use chroma_distance::DistanceFunction;
+use chroma_error::{ChromaError, ErrorCodes};
+use chroma_index::spann::utils::rng_query;
+use thiserror::Error;
+use tonic::async_trait;
+
+use crate::{
+    execution::operator::Operator,
+    segment::spann_segment::{SpannSegmentReader, SpannSegmentReaderContext},
+};
+
+#[derive(Debug)]
+pub struct SpannCentersSearchInput {
+    reader_context: SpannSegmentReaderContext,
+    // Assumes that query is already normalized in case of cosine.
+    query: Vec<f32>,
+    k: usize,
+    rng_epsilon: f32,
+    rng_factor: f32,
+    distance_function: DistanceFunction,
+}
+
+#[derive(Debug)]
+pub struct SpannCentersSearchOutput {
+    center_ids: Vec<usize>,
+}
+
+#[derive(Error, Debug)]
+pub enum SpannCentersSearchError {
+    #[error("Error creating spann segment reader")]
+    SpannSegmentReaderCreationError,
+    #[error("Error querying RNG")]
+    RngQueryError,
+}
+
+impl ChromaError for SpannCentersSearchError {
+    fn code(&self) -> ErrorCodes {
+        match self {
+            Self::SpannSegmentReaderCreationError => ErrorCodes::Internal,
+            Self::RngQueryError => ErrorCodes::Internal,
+        }
+    }
+}
+
+#[derive(Debug)]
+pub struct SpannCentersSearchOperator {}
+
+impl SpannCentersSearchOperator {
+    pub fn new() -> Box<Self> {
+        Box::new(SpannCentersSearchOperator {})
+    }
+}
+
+#[async_trait]
+impl Operator<SpannCentersSearchInput, SpannCentersSearchOutput> for SpannCentersSearchOperator {
+    type Error = SpannCentersSearchError;
+
+    async fn run(
+        &self,
+        input: &SpannCentersSearchInput,
+    ) -> Result<SpannCentersSearchOutput, SpannCentersSearchError> {
+        let spann_reader = SpannSegmentReader::from_segment(
+            &input.reader_context.segment,
+            &input.reader_context.blockfile_provider,
+            &input.reader_context.hnsw_provider,
+            input.reader_context.dimension,
+        )
+        .await
+        .map_err(|_| SpannCentersSearchError::SpannSegmentReaderCreationError)?;
+        // RNG Query.
+        let res = rng_query(
+            &input.query,
+            spann_reader.index_reader.hnsw_index.clone(),
+            input.k,
+            input.rng_epsilon,
+            input.rng_factor,
+            input.distance_function.clone(),
+        )
+        .await
+        .map_err(|_| SpannCentersSearchError::RngQueryError)?;
+        Ok(SpannCentersSearchOutput { center_ids: res.0 })
+    }
+}

rust/worker/src/segment/spann_segment.rs

@@ -344,9 +344,17 @@ impl ChromaError for SpannSegmentReaderError {
     }
 }
 
+#[derive(Debug)]
+pub struct SpannSegmentReaderContext {
+    pub segment: Segment,
+    pub blockfile_provider: BlockfileProvider,
+    pub hnsw_provider: HnswIndexProvider,
+    pub dimension: usize,
+}
+
 #[derive(Clone)]
 pub(crate) struct SpannSegmentReader<'me> {
-    index_reader: SpannIndexReader<'me>,
+    pub index_reader: SpannIndexReader<'me>,
     id: SegmentUuid,
 }