Example - Index and query JSON documents

Learn how to use the Redis query engine with JSON

This example shows how to create a search index for JSON data and run queries against the index.

Make sure that you have Redis Stack and NRedisStack installed.

Start by connecting to the Redis server:

import (
	"context"
	"fmt"

	"github.com/redis/go-redis/v9"
)

func main() {
	ctx := context.Background()

	rdb := redis.NewClient(&redis.Options{
		Addr:     "localhost:6379",
		Password: "",
		DB:       0,
		Protocol: 2,
	})

    // ...
}

Add some map objects to store in JSON format in the database:

user1 := map[string]interface{}{
    "name":  "Paul John",
    "email": "paul.john@example.com",
    "age":   42,
    "city":  "London",
}

user2 := map[string]interface{}{
    "name":  "Eden Zamir",
    "email": "eden.zamir@example.com",
    "age":   29,
    "city":  "Tel Aviv",
}

user3 := map[string]interface{}{
    "name":  "Paul Zamir",
    "email": "paul.zamir@example.com",
    "age":   35,
    "city":  "Tel Aviv",
}

Use the code below to create a search index. The FTCreateOptions parameter enables indexing only for JSON objects where the key has a user: prefix. The schema for the index has three fields for the user's name, age, and city. The FieldName field of the FieldSchema struct specifies a JSON path that identifies which data field to index. Use the As struct field to provide an alias for the JSON path expression. You can use the alias in queries as a short and intuitive way to refer to the expression, instead of typing it in full:

_, err := rdb.FTCreate(
    ctx,
    "idx:users",
    // Options:
    &redis.FTCreateOptions{
        OnJSON: true,
        Prefix: []interface{}{"user:"},
    },
    // Index schema fields:
    &redis.FieldSchema{
        FieldName: "$.name",
        As:        "name",
        FieldType: redis.SearchFieldTypeText,
    },
    &redis.FieldSchema{
        FieldName: "$.city",
        As:        "city",
        FieldType: redis.SearchFieldTypeTag,
    },
    &redis.FieldSchema{
        FieldName: "$.age",
        As:        "age",
        FieldType: redis.SearchFieldTypeNumeric,
    },
).Result()

if err != nil {
    panic(err)
}

Add the three sets of user data to the database as JSON objects. If you use keys with the user: prefix then Redis will index the objects automatically as you add them:

_, err = rdb.JSONSet(ctx, "user:1", "$", user1).Result()

if err != nil {
    panic(err)
}

_, err = rdb.JSONSet(ctx, "user:2", "$", user2).Result()

if err != nil {
    panic(err)
}

_, err = rdb.JSONSet(ctx, "user:3", "$", user3).Result()

if err != nil {
    panic(err)
}

You can now use the index to search the JSON objects. The query below searches for objects that have the text "Paul" in any field and have an age value in the range 30 to 40:

searchResult, err := rdb.FTSearch(
    ctx,
    "idx:users",
    "Paul @age:[30 40]",
).Result()

if err != nil {
    panic(err)
}

fmt.Println(searchResult)
// >>> {1 [{user:3 <nil> <nil> <nil> map[$:{"age":35,"city":"Tel Aviv"...
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