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licence release rust

HNSW for Redis

redis_hnsw is a Hierarchical Navigable Small World (HNSW) implementation for Redis. Based on the paper Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs. Currently only supports Euclidean distance, Hamming distance forthcoming.

Table of Contents

Getting Started

⚠️ requires nightly rust

Build the module - cargo build

Load the module - redis-server --loadmodule ./target/<build_mode>/libredis_hnsw.<dylib|so>

Redis commands

Creating a new index - hnsw.new {index_name} [DIM {data_dim}] [M {m}] [EFCON {ef_construction}]

Add nodes - hnsw.node.add {index_name} {node_name} [DATA {dim} {...data}]

Delete nodes - hnsw.node.del {index_name} {node_name}

Search KNN - hnsw.search {index_name} [K {k}] [DATA {dim} {...data}]

Command Reference

HNSW.NEW

Format

HNSW.NEW {index} [DIM {data_dim}] [M {m}] [EFCON {ef_construction}]

Description

Creates an HNSW index

Example

HNSW.NEW foo DIM 128 M 5 EFCON 200

Parameters

  • index: required, name of the new index.
  • DIM: required, dimensionality of the data.
  • M: optional, algorithm parameter for the number of neighbors to select for each node.
  • EFCON: optional, algorithm parameter for the size of the dynamic candidate list.

Complexity

O(1)

Returns

OK or an error

HNSW.GET

Format

HNSW.GET {index}

Description

Retrieves an HNSW index

Example

HNSW.GET foo

Parameters

  • index: required, name of the index.

Complexity

O(1)

Returns

Array Reply key-value pairs of index attributes

HNSW.DEL

Format

HNSW.DEL {index}

Description

Deletes an HNSW index

Example

HNSW.DEL foo

Parameters

  • index: required, name of the index.

Complexity

O(1)

Returns

OK or an error

HNSW.NODE.ADD

Format

HNSW.NODE.ADD {index} {node} [DATA {dim} {...data}]

Description

Adds an element to the index

Example

HNSW.NODE.ADD foo bar DATA 4 1.0 1.0 1.0 1.0

Parameters

  • index: required, name of the index
  • node: required, name of the new node
  • DATA: required, dimensionality followed by a space separated vector of data. Total entries must match DIM of index

Complexity

O(log(n)) where n is the number of nodes in the index

Returns

OK or an error

HNSW.NODE.GET

Format

HNSW.NODE.GET {index} {node}

Description

Retrieves an element from the index

Example

HNSW.NODE.GET foo bar

Parameters

  • index: required, name of the index
  • node: required, name of the node

Complexity

O(1)

Returns

Array Reply key-value pairs of node attributes

HNSW.NODE.DEL

Format

HNSW.NODE.DEL {index} {node}

Description

Removes an element from the index

Example

HNSW.NODE.DEL foo bar

Parameters

  • index: required, name of the index
  • node: required, name of the node

Complexity

O(log(n)) where n is the number of nodes in the index

Returns

OK or an error

HNSW.SEARCH

Format

HNSW.SEARCH {index} [K {k}] [QUERY {dim} {...data}]

Description

Search the index for the K nearest elements to the query

Example

HNSW.SEARCH foo K 5 QUERY 4 0.0 0.0 0.0 0.0

Parameters

  • index: required, name of the index
  • K: required, number of nearest neighbors to return
  • DATA: required, dimensionality followed by space separated vector of query data. Total entries must match DIM of index

Complexity

O(log(n)) where n is the number of nodes in the index

Returns

Array Reply where the first element is the number of results, followed by key-value pairs of similiarity and returned node key.