Awesome
HNSW for Redis
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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
<!-- /TOC -->Getting Started
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:warning: requires nightly rust
Build the module - cargo build
Load the module - redis-server --loadmodule ./target/<build_mode>/libredis_hnsw.<dylib|so>
Redis commands
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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
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HNSW.NEW
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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
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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
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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
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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
DIMof index
Complexity
O(log(n)) where n is the number of nodes in the index
Returns
OK or an error
HNSW.NODE.GET
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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
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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
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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
DIMof 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.