// Deprecated storage placement params (`on_disk`, `always_ram`, `on_disk_payload`) are still // handled here for backward compatibility with the new `memory` parameter #![allow(deprecated)] use std::collections::{BTreeSet, HashMap}; use std::sync::Arc; use std::sync::atomic::AtomicBool; use atomic_refcell::AtomicRefCell; use common::budget::ResourcePermit; use common::counter::hardware_counter::HardwareCounterCell; use common::flags::FeatureFlags; use common::progress_tracker::ProgressTracker; use common::types::ScoredPointOffset; use ordered_float::OrderedFloat; use rand::prelude::StdRng; use rand::{Rng, RngExt, SeedableRng}; use rstest::rstest; use segment::data_types::vectors::{ DEFAULT_VECTOR_NAME, MultiDenseVectorInternal, QueryVector, only_default_multi_vector, }; use segment::entry::entry_point::SegmentEntry; use segment::fixtures::payload_fixtures::{random_int_payload, random_multi_vector}; use segment::fixtures::query_fixtures::QueryVariant; use segment::index::hnsw_index::hnsw::{HNSWIndex, HnswIndexOpenArgs}; use segment::index::{PayloadIndex, VectorIndexRead}; use segment::json_path::JsonPath; use segment::segment_constructor::build_segment; use segment::types::{ BinaryQuantizationConfig, CompressionRatio, Condition, Distance, FieldCondition, Filter, HnswConfig, Indexes, MultiVectorConfig, PayloadSchemaType, ProductQuantizationConfig, QuantizationSearchParams, Range, ScalarQuantizationConfig, SearchParams, SegmentConfig, SeqNumberType, VectorDataConfig, VectorStorageType, }; use segment::vector_storage::quantized::quantized_vectors::{ QuantizedVectors, QuantizedVectorsStorageType, }; use tempfile::Builder; const MAX_VECTORS_COUNT: usize = 3; enum QuantizationVariant { Scalar, PQ, Binary, } fn random_vector(rng: &mut R, dim: usize) -> MultiDenseVectorInternal { let count = rng.random_range(1..=MAX_VECTORS_COUNT); let mut vector = random_multi_vector(rng, dim, count); // for BQ change range to [-0.5; 0.5] vector.flattened_vectors.iter_mut().for_each(|x| *x -= 0.5); vector } fn random_query(variant: &QueryVariant, rng: &mut R, dim: usize) -> QueryVector { segment::fixtures::query_fixtures::random_query(variant, rng, |rng: &mut R| { random_vector(rng, dim).into() }) } fn sames_count(a: &[Vec], b: &[Vec]) -> usize { a[0].iter() .map(|x| x.idx) .collect::>() .intersection(&b[0].iter().map(|x| x.idx).collect()) .count() } #[cfg_attr(target_os = "windows", ignore = "slow on Windows, not OS-specific")] #[rstest] #[case::nearest_binary_dot( QueryVariant::Nearest, QuantizationVariant::Binary, Distance::Dot, 128, // dim 32, // ef false, 25., // min_acc out of 100 )] #[case::discover_binary_dot( QueryVariant::Discover, QuantizationVariant::Binary, Distance::Dot, 128, // dim 128, // ef false, 20., // min_acc out of 100 )] #[case::recobestscore_binary_dot( QueryVariant::RecoBestScore, QuantizationVariant::Binary, Distance::Dot, 128, // dim 64, // ef false, 20., // min_acc out of 100 )] #[case::recosumscores_binary_dot( QueryVariant::RecoSumScores, QuantizationVariant::Binary, Distance::Dot, 128, // dim 64, // ef false, 20., // min_acc out of 100 )] #[case::nearest_binary_cosine( QueryVariant::Nearest, QuantizationVariant::Binary, Distance::Cosine, 128, // dim 32, // ef false, 25., // min_acc out of 100 )] #[case::discover_binary_cosine( QueryVariant::Discover, QuantizationVariant::Binary, Distance::Cosine, 128, // dim 128, // ef false, 15., // min_acc out of 100 )] #[case::recobestscore_binary_cosine( QueryVariant::RecoBestScore, QuantizationVariant::Binary, Distance::Cosine, 128, // dim 64, // ef false, 15., // min_acc out of 100 )] #[case::recosumscores_binary_cosine( QueryVariant::RecoSumScores, QuantizationVariant::Binary, Distance::Cosine, 128, // dim 64, // ef false, 15., // min_acc out of 100 )] #[case::nearest_scalar_dot( QueryVariant::Nearest, QuantizationVariant::Scalar, Distance::Dot, 32, // dim 32, // ef false, 80., // min_acc out of 100 )] #[case::nearest_scalar_cosine( QueryVariant::Nearest, QuantizationVariant::Scalar, Distance::Cosine, 32, // dim 32, // ef false, 80., // min_acc out of 100 )] #[case::nearest_pq_dot( QueryVariant::Nearest, QuantizationVariant::PQ, Distance::Dot, 16, // dim 32, // ef false, 70., // min_acc out of 100 )] #[case::nearest_scalar_cosine_on_disk( QueryVariant::Nearest, QuantizationVariant::Scalar, Distance::Cosine, 32, // dim 32, // ef true, 80., // min_acc out of 100 )] fn test_multivector_quantization_hnsw( #[case] query_variant: QueryVariant, #[case] quantization_variant: QuantizationVariant, #[case] distance: Distance, #[case] dim: usize, #[case] ef: usize, #[case] on_disk: bool, #[case] min_acc: f64, // out of 100 ) { use segment::payload_json; use segment::segment_constructor::VectorIndexBuildArgs; use segment::types::HnswGlobalConfig; let stopped = AtomicBool::new(false); let m = 8; let num_vectors: u64 = 1_000; let ef_construct = 16; let full_scan_threshold = 16; // KB let num_payload_values = 2; let mut rng = StdRng::seed_from_u64(42); let dir = Builder::new().prefix("segment_dir").tempdir().unwrap(); let quantized_data_path = dir.path(); let hnsw_dir = Builder::new().prefix("hnsw_dir").tempdir().unwrap(); let storage_type = if on_disk { VectorStorageType::ChunkedMmap } else { VectorStorageType::InRamChunkedMmap }; let config = SegmentConfig { vector_data: HashMap::from([( DEFAULT_VECTOR_NAME.to_owned(), VectorDataConfig { size: dim, distance, storage_type, index: Indexes::Plain {}, quantization_config: None, multivector_config: Some(MultiVectorConfig::default()), // uses multivec config datatype: None, }, )]), sparse_vector_data: Default::default(), payload_storage_type: Default::default(), }; let int_key = "int"; let (mut segment, _) = build_segment(dir.path(), &config, None, true).unwrap(); let hw_counter = HardwareCounterCell::new(); for n in 0..num_vectors { let idx = n.into(); let vector = random_vector(&mut rng, dim); let int_payload = random_int_payload(&mut rng, num_payload_values..=num_payload_values); let payload = payload_json! {int_key: int_payload}; segment .upsert_point( n as SeqNumberType, idx, only_default_multi_vector(&vector), &hw_counter, ) .unwrap(); segment .set_full_payload(n as SeqNumberType, idx, &payload, &hw_counter) .unwrap(); } segment .payload_index .borrow_mut() .set_indexed( &JsonPath::new(int_key), PayloadSchemaType::Integer, &hw_counter, ) .unwrap(); let quantization_config = match quantization_variant { QuantizationVariant::Scalar => ScalarQuantizationConfig { memory: None, r#type: Default::default(), quantile: None, always_ram: Some(false), } .into(), QuantizationVariant::PQ => ProductQuantizationConfig { memory: None, compression: CompressionRatio::X8, always_ram: Some(false), } .into(), QuantizationVariant::Binary => BinaryQuantizationConfig { memory: None, always_ram: Some(false), encoding: None, query_encoding: None, } .into(), }; segment.vector_data.values_mut().for_each(|vector_storage| { { // test persistence, encode and save quantized vectors QuantizedVectors::create( &vector_storage.vector_storage.borrow(), &quantization_config, QuantizedVectorsStorageType::Immutable, quantized_data_path, 4, &stopped, ) .unwrap(); } // test persistence, load quantized vectors let quantized_vectors = QuantizedVectors::load( &quantization_config, &vector_storage.vector_storage.borrow(), quantized_data_path, &stopped, ) .unwrap() .unwrap(); vector_storage.quantized_vectors = Arc::new(AtomicRefCell::new(Some(quantized_vectors))); }); let hnsw_config = HnswConfig { memory: None, m, ef_construct, full_scan_threshold, max_indexing_threads: 2, on_disk: Some(false), payload_m: None, inline_storage: None, }; let permit_cpu_count = 1; // single-threaded for deterministic build let permit = Arc::new(ResourcePermit::dummy(permit_cpu_count as u32)); let hnsw_index = HNSWIndex::build( HnswIndexOpenArgs { path: hnsw_dir.path(), id_tracker: segment.id_tracker.clone(), vector_storage: segment.vector_data[DEFAULT_VECTOR_NAME] .vector_storage .clone(), quantized_vectors: segment.vector_data[DEFAULT_VECTOR_NAME] .quantized_vectors .clone(), payload_index: segment.payload_index.clone(), hnsw_config, }, VectorIndexBuildArgs { permit, old_indices: &[], gpu_device: None, rng: &mut rng, stopped: &stopped, hnsw_global_config: &HnswGlobalConfig::default(), feature_flags: FeatureFlags::default(), progress: ProgressTracker::new_for_test(), }, ) .unwrap(); let top = 5; let mut sames = 0; let attempts = 100; for _ in 0..attempts { let query = random_query(&query_variant, &mut rng, dim); let range_size = 40; let left_range = rng.random_range(0..400); let right_range = left_range + range_size; let filter = Filter::new_must(Condition::Field(FieldCondition::new_range( JsonPath::new(int_key), Range { lt: None, gt: None, gte: Some(OrderedFloat(f64::from(left_range))), lte: Some(OrderedFloat(f64::from(right_range))), }, ))); let filter_query = Some(&filter); let index_result = hnsw_index .search( &[&query], filter_query, top, Some(&SearchParams { hnsw_ef: Some(ef), quantization: Some(QuantizationSearchParams { oversampling: Some(1.3), ..Default::default() }), ..Default::default() }), &Default::default(), ) .unwrap(); let plain_result = hnsw_index .search( &[&query], filter_query, top, Some(&SearchParams { hnsw_ef: Some(ef), quantization: Some(QuantizationSearchParams { ignore: true, ..Default::default() }), exact: true, ..Default::default() }), &Default::default(), ) .unwrap(); sames += sames_count(&plain_result, &index_result); } let acc = 100.0 * sames as f64 / (attempts * top) as f64; println!("sames = {sames}, attempts = {attempts}, top = {top}, acc = {acc}"); assert!(acc > min_acc); }