pub struct HNSWConfig {
pub m: usize,
pub m0: usize,
pub ef_construction: usize,
pub ef_search: usize,
pub ml: f64,
pub sparsity_threshold: f32,
pub max_nodes: usize,
pub distance_metric: HNSWDistanceMetric,
}Expand description
Configuration for HNSW index.
Fields§
§m: usizeMaximum number of connections per node per layer (default: 16)
m0: usizeMaximum connections at layer 0 (default: 2*m = 32)
ef_construction: usizeCandidates to consider during construction (default: 200)
ef_search: usizeCandidates to consider during search (default: 50)
ml: f64Level multiplier for layer selection (default: 1/ln(m))
sparsity_threshold: f32Sparsity threshold for auto-sparse storage (default: 0.5 = 50% zeros)
When using insert_auto(), vectors with sparsity above this threshold
will be stored as sparse vectors for memory savings.
max_nodes: usizeMaximum number of nodes allowed in the index (0 = unlimited). Default: 10,000,000 (10M nodes) to prevent memory exhaustion.
distance_metric: HNSWDistanceMetricDistance metric for similarity computation.
Determines how distances are calculated during index construction and search. Must match the embedding model’s training objective:
- Use
Cosinefor normalized embeddings (most common) - Use
Euclideanfor spatial/geometric embeddings - Use
DotProductfor MIPS (maximum inner product search)
Default: HNSWDistanceMetric::Cosine
Implementations§
Source§impl HNSWConfig
impl HNSWConfig
Sourcepub fn high_recall() -> HNSWConfig
pub fn high_recall() -> HNSWConfig
Create a config optimized for high recall (slower but more accurate)
Sourcepub fn high_speed() -> HNSWConfig
pub fn high_speed() -> HNSWConfig
Create a config optimized for speed (faster but lower recall)
Sourcepub const fn with_distance_metric(
self,
metric: HNSWDistanceMetric,
) -> HNSWConfig
pub const fn with_distance_metric( self, metric: HNSWDistanceMetric, ) -> HNSWConfig
Set the distance metric for this configuration.
§Example
use tensor_store::{HNSWConfig, HNSWDistanceMetric};
let config = HNSWConfig::default()
.with_distance_metric(HNSWDistanceMetric::Euclidean);Trait Implementations§
Source§impl Clone for HNSWConfig
impl Clone for HNSWConfig
Source§fn clone(&self) -> HNSWConfig
fn clone(&self) -> HNSWConfig
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source. Read moreSource§impl Debug for HNSWConfig
impl Debug for HNSWConfig
Source§impl Default for HNSWConfig
impl Default for HNSWConfig
Source§fn default() -> HNSWConfig
fn default() -> HNSWConfig
Source§impl<'de> Deserialize<'de> for HNSWConfig
impl<'de> Deserialize<'de> for HNSWConfig
Source§fn deserialize<__D>(
__deserializer: __D,
) -> Result<HNSWConfig, <__D as Deserializer<'de>>::Error>where
__D: Deserializer<'de>,
fn deserialize<__D>(
__deserializer: __D,
) -> Result<HNSWConfig, <__D as Deserializer<'de>>::Error>where
__D: Deserializer<'de>,
Source§impl Serialize for HNSWConfig
impl Serialize for HNSWConfig
Source§fn serialize<__S>(
&self,
__serializer: __S,
) -> Result<<__S as Serializer>::Ok, <__S as Serializer>::Error>where
__S: Serializer,
fn serialize<__S>(
&self,
__serializer: __S,
) -> Result<<__S as Serializer>::Ok, <__S as Serializer>::Error>where
__S: Serializer,
Auto Trait Implementations§
impl Freeze for HNSWConfig
impl RefUnwindSafe for HNSWConfig
impl Send for HNSWConfig
impl Sync for HNSWConfig
impl Unpin for HNSWConfig
impl UnsafeUnpin for HNSWConfig
impl UnwindSafe for HNSWConfig
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