DiskANN

Struct DiskANN 

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pub struct DiskANN<T, D>
where T: Pod + Copy + Send + Sync + 'static, D: Distance<T> + Send + Sync + Copy + Clone + 'static,
{ pub dim: usize, pub num_vectors: usize, pub max_degree: usize, pub distance_name: String, /* private fields */ }
Expand description

Main struct representing a DiskANN index (generic over vector element T and distance D)

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§dim: usize

Dimensionality of vectors in the index

§num_vectors: usize

Number of vectors in the index

§max_degree: usize

Maximum number of edges per node

§distance_name: String

Informational: type name of the distance (from metadata)

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impl<T, D> DiskANN<T, D>
where T: Pod + Copy + Send + Sync + 'static, D: Distance<T> + Send + Sync + Copy + Clone + 'static,

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pub fn build_index_default( vectors: &[Vec<T>], dist: D, file_path: &str, ) -> Result<Self, DiskAnnError>

Build with default parameters: (M=64, L=128, alpha=1.2).

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pub fn build_index_with_params( vectors: &[Vec<T>], dist: D, file_path: &str, p: DiskAnnParams, ) -> Result<Self, DiskAnnError>

Build with a DiskAnnParams bundle.

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pub fn open_index_with(path: &str, dist: D) -> Result<Self, DiskAnnError>

Opens an existing index file, supplying the distance strategy explicitly.

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impl<T, D> DiskANN<T, D>
where T: Pod + Copy + Send + Sync + 'static, D: Distance<T> + Default + Send + Sync + Copy + Clone + 'static,

Extra sugar when your distance type implements Default.

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pub fn build_index_default_metric( vectors: &[Vec<T>], file_path: &str, ) -> Result<Self, DiskAnnError>

Build with default params and D::default() metric.

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pub fn open_index_default_metric(path: &str) -> Result<Self, DiskAnnError>

Open an index using D::default() as the distance (matches what you built with).

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impl<T, D> DiskANN<T, D>
where T: Pod + Copy + Send + Sync + 'static, D: Distance<T> + Send + Sync + Copy + Clone + 'static,

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pub fn build_index( vectors: &[Vec<T>], max_degree: usize, build_beam_width: usize, alpha: f32, dist: D, file_path: &str, ) -> Result<Self, DiskAnnError>

Builds a new index from provided vectors

§Arguments
  • vectors - The vectors to index (slice of Vec)
  • max_degree - Maximum edges per node (M ~ 24-64+)
  • build_beam_width - Construction L (e.g., 128-400)
  • alpha - Pruning parameter (1.2–2.0)
  • dist - Any anndists::Distance<T>
  • file_path - Path of index file
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pub fn search_with_dists( &self, query: &[T], k: usize, beam_width: usize, ) -> Vec<(u32, f32)>

Searches the index for nearest neighbors using a best-first beam search. Termination rule: continue while the best frontier can still improve the worst in working set. Like search but also returns the distance for each neighbor.

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pub fn search(&self, query: &[T], k: usize, beam_width: usize) -> Vec<u32>

search but only return neighbor ids

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pub fn get_vector(&self, idx: usize) -> Vec<T>

Gets a vector from the index

Auto Trait Implementations§

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impl<T, D> Freeze for DiskANN<T, D>
where D: Freeze,

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impl<T, D> RefUnwindSafe for DiskANN<T, D>

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impl<T, D> Send for DiskANN<T, D>

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impl<T, D> Sync for DiskANN<T, D>

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impl<T, D> Unpin for DiskANN<T, D>
where D: Unpin, T: Unpin,

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impl<T, D> UnwindSafe for DiskANN<T, D>
where D: UnwindSafe, T: UnwindSafe,

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impl<T> Any for T
where T: 'static + ?Sized,

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fn borrow_mut(&mut self) -> &mut T

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impl<T> From<T> for T

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