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https://github.com/zhao-lang/redis_hnsw
HSNW module for Redis
https://github.com/zhao-lang/redis_hnsw
approximate-nearest-neighbor-search hnsw knn redis redis-module rust
Last synced: about 1 month ago
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HSNW module for Redis
- Host: GitHub
- URL: https://github.com/zhao-lang/redis_hnsw
- Owner: zhao-lang
- License: mit
- Created: 2020-03-11T21:10:21.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2020-09-01T23:57:31.000Z (over 4 years ago)
- Last Synced: 2024-01-27T23:07:01.799Z (11 months ago)
- Topics: approximate-nearest-neighbor-search, hnsw, knn, redis, redis-module, rust
- Language: Rust
- Size: 148 KB
- Stars: 55
- Watchers: 3
- Forks: 4
- Open Issues: 4
-
Metadata Files:
- Readme: Readme.md
- License: LICENSE
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README
[![licence](https://img.shields.io/github/license/zhao-lang/redis_hnsw.svg)](https://github.com/zhao-lang/redis_hnsw/blob/master/LICENSE)
[![release](https://img.shields.io/github/v/release/zhao-lang/redis_hnsw.svg)](https://github.com/zhao-lang/redis_hnsw/releases/latest)
[![rust](https://github.com/zhao-lang/redis_hnsw/workflows/Rust/badge.svg)](https://github.com/zhao-lang/redis_hnsw/actions?query=workflow%3ARust)`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](https://arxiv.org/abs/1603.09320). Currently only supports Euclidean distance, Hamming distance forthcoming.
## Table of Contents
- [Getting Started](#getting-started)
- [Redis commands](#redis-commands)
- [Command Reference](#command-reference)
- [HNSW.NEW](#hnswnew)
- [HNSW.GET](#hnswget)
- [HNSW.DEL](#hnswdel)
- [HNSW.NODE.ADD](#hnswnodeadd)
- [HNSW.NODE.GET](#hnswnodeget)
- [HNSW.NODE.DEL](#hnswnodedel)
- [HNSW.SEARCH](#hnswsearch)> :warning: **requires nightly rust**
Build the module - `cargo build`
Load the module - `redis-server --loadmodule ./target//libredis_hnsw.`
### 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}]`
### 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.