@redis/search

@redis/search

This package provides support for the RediSearch module, which adds indexing and querying support for data stored in Redis Hashes or as JSON documents with the RedisJSON module.

Should be used with redis/@redis/client.

:warning: To use these extra commands, your Redis server must have the RediSearch module installed. To index and query JSON documents, you'll also need to add the RedisJSON module.

Usage

For complete examples, see search-hashes.js and search-json.js in the examples folder.

Indexing and Querying Data in Redis Hashes

Creating an Index

Before we can perform any searches, we need to tell RediSearch how to index our data, and which Redis keys to find that data in. The FT.CREATE command creates a RediSearch index. Here's how to use it to create an index we'll call idx:animals where we want to index hashes containing name, species and age fields, and whose key names in Redis begin with the prefix noderedis:animals:

await client.ft.create('idx:animals', {
  name: {
    type: SCHEMA_FIELD_TYPE.TEXT,
    SORTABLE: true
  },
  species: SCHEMA_FIELD_TYPE.TAG,
  age: SCHEMA_FIELD_TYPE.NUMERIC
}, {
  ON: 'HASH',
  PREFIX: 'noderedis:animals'
});

See the FT.CREATE documentation for information about the different field types and additional options.

Querying the Index

Once we've created an index, and added some data to Redis hashes whose keys begin with the prefix noderedis:animals, we can start writing some search queries. RediSearch supports a rich query syntax for full-text search, faceted search, aggregation and more. Check out the FT.SEARCH documentation and the query syntax reference for more information.

Let's write a query to find all the animals where the species field has the value dog:

const results = await client.ft.search('idx:animals', '@species:{dog}');

results looks like this:

{
  total: 2,
  documents: [
    {
      id: 'noderedis:animals:4',
      value: {
        name: 'Fido',
        species: 'dog',
        age: '7'
      }
    },
    {
      id: 'noderedis:animals:3',
      value: {
        name: 'Rover',
        species: 'dog',
        age: '9'
      }
    }
  ]
}

Indexing and Querying Data with RedisJSON

RediSearch can also index and query JSON documents stored in Redis using the RedisJSON module. The approach is similar to that for indexing and searching data in hashes, but we can now use JSON Path like syntax and the data no longer has to be flat name/value pairs - it can contain nested objects and arrays.

Creating an Index

As before, we create an index with the FT.CREATE command, this time specifying we want to index JSON documents that look like this:

{
  name: 'Alice',
  age: 32,
  coins: 100
}

Each document represents a user in some system, and users have name, age and coins properties.

One way we might choose to index these documents is as follows:

await client.ft.create('idx:users', {
  '$.name': {
    type: SCHEMA_FIELD_TYPE.TEXT,
    SORTABLE: 'UNF'
  },
  '$.age': {
    type: SCHEMA_FIELD_TYPE.NUMERIC,
    AS: 'age'
  },
  '$.coins': {
    type: SCHEMA_FIELD_TYPE.NUMERIC,
    AS: 'coins'
  }
}, {
  ON: 'JSON',
  PREFIX: 'noderedis:users'
});

Note that we're using JSON Path to specify where the fields to index are in our JSON documents, and the AS clause to define a name/alias for each field. We'll use these when writing queries.

Querying the Index

Now we have an index and some data stored as JSON documents in Redis (see the JSON package documentation for examples of how to store JSON), we can write some queries...

We'll use the RediSearch query language and FT.SEARCH command. Here's a query to find users under the age of 30:

await client.ft.search('idx:users', '@age:[0 30]');

Similar packages

Other packages similar to @redis/search

redis-om

Redis OM provides an object mapping solution for Redis, including support for indexing and searching objects. While it offers similar search capabilities, @redis/search is more focused on leveraging the RediSearch module directly for advanced search features.

elasticsearch

Elasticsearch is a distributed, RESTful search and analytics engine capable of solving a broad set of use cases. While not a Redis-based solution, it offers comprehensive full-text search capabilities similar to those of @redis/search but is designed for use cases requiring distributed search capabilities across large datasets.