Index and query documents

This example shows how to create a [search index]({{< relref "/develop/ai/search-and-query/indexing" >}}) for [JSON]({{< relref "/develop/data-types/json" >}}) documents and run queries against the index. It then goes on to show the slight differences in the equivalent code for [hash]({{< relref "/develop/data-types/hashes" >}}) documents.

{{< note >}}From v6.0.0 onwards, Jedis uses query dialect 2 by default. Redis Search methods such as [ftSearch()]({{< relref "/commands/ft.search" >}}) will explicitly request this dialect, overriding the default set for the server. See [Query dialects]({{< relref "/develop/ai/search-and-query/advanced-concepts/dialects" >}}) for more information. {{< /note >}}

Initialize

Make sure that you have [Redis Open Source]({{< relref "/operate/oss_and_stack/" >}}) or another Redis server available. Also install the [Jedis]({{< relref "/develop/clients/jedis" >}}) client library if you haven't already done so.

Add the following dependencies. All of them are applicable to both JSON and hash, except for the Path and JSONObject classes, which are specific to JSON (see [Path]({{< relref "/develop/data-types/json/path" >}}) for a description of the JSON path syntax).

{{< clients-example set="java_home_json" step="import" description="Foundational: Import required Jedis classes for JSON indexing and query operations" difficulty="beginner" >}} {{< /clients-example >}}

Create data

Create some test data to add to the database:

{{< clients-example set="java_home_json" step="create_data" description="Foundational: Define sample user data structures for indexing and querying" difficulty="beginner" >}} {{< /clients-example >}}

Add the index

Connect to your Redis database. The code below shows the most basic connection but see [Connect to the server]({{< relref "/develop/clients/jedis/connect" >}}) to learn more about the available connection options.

{{< clients-example set="java_home_json" step="connect" description="Foundational: Establish a connection to a Redis server for query operations" difficulty="beginner" >}} {{< /clients-example >}}

Delete any existing index called idx:users and any keys that start with user:.

{{< clients-example set="java_home_json" step="cleanup_json" description="Foundational: Clean up existing indexes and data before creating new indexes" difficulty="beginner" >}} {{< /clients-example >}}

Create an index. In this example, only JSON documents with the key prefix user: are indexed. For more information, see [Query syntax]({{< relref "/develop/ai/search-and-query/query/" >}}).

{{< clients-example set="java_home_json" step="make_index" description="Foundational: Create a search index for JSON documents with field definitions and key prefix filtering" difficulty="intermediate" >}} {{< /clients-example >}}

Add the data

Add the three sets of user data to the database as [JSON]({{< relref "/develop/data-types/json" >}}) objects. If you use keys with the user: prefix then Redis will index the objects automatically as you add them:

{{< clients-example set="java_home_json" step="add_data" description="Foundational: Store JSON documents in Redis with automatic indexing based on key prefix" difficulty="beginner" >}} {{< /clients-example >}}

Query the data

You can now use the index to search the JSON objects. The [query]({{< relref "/develop/ai/search-and-query/query" >}}) below searches for objects that have the text "Paul" in any field and have an age value in the range 30 to 40:

{{< clients-example set="java_home_json" step="query1" description="Query with filters: Search JSON documents using text matching and numeric range filters to find specific records" difficulty="intermediate" >}} {{< /clients-example >}}

Specify query options to return only the city field:

{{< clients-example set="java_home_json" step="query2" description="Query with field projection: Retrieve only specific fields from search results to reduce data transfer" difficulty="intermediate" >}} {{< /clients-example >}}

Use an [aggregation query]({{< relref "/develop/ai/search-and-query/query/aggregation" >}}) to count all users in each city.

{{< clients-example set="java_home_json" step="query3" description="Aggregation query: Group and count results by field values to analyze data patterns" difficulty="intermediate" >}} {{< /clients-example >}}

Differences with hash documents

Indexing for hash documents is very similar to JSON indexing but you need to specify some slightly different options.

When you create the schema for a hash index, you don't need to add aliases for the fields, since you use the basic names to access the fields anyway. Also, you must use IndexDataType.HASH for the On() option of FTCreateParams when you create the index. The code below shows these changes with a new index called hash-idx:users, which is otherwise the same as the idx:users index used for JSON documents in the previous examples.

First, delete any existing index called hash-idx:users and any keys that start with huser:.

{{< clients-example set="java_home_json" step="cleanup_hash" description="Foundational: Clean up existing hash indexes and data before creating new indexes" difficulty="beginner" >}} {{< /clients-example >}}

Now create the new index:

{{< clients-example set="java_home_json" step="make_hash_index" description="Foundational: Create a search index for hash documents with field definitions and key prefix filtering" difficulty="intermediate" >}} {{< /clients-example >}}

Use [hset()]({{< relref "/commands/hset" >}}) to add the hash documents instead of [jsonSet()]({{< relref "/commands/json.set" >}}).

{{< clients-example set="java_home_json" step="add_hash_data" description="Foundational: Store hash documents in Redis with automatic indexing based on key prefix" difficulty="beginner" >}} {{< /clients-example >}}

The query commands work the same here for hash as they do for JSON (but the name of the hash index is different). The results are returned in a List of Document objects, as with JSON:

{{< clients-example set="java_home_json" step="query1_hash" description="Query with filters: Search hash documents using text matching and numeric range filters (same as JSON queries)" difficulty="intermediate" >}} {{< /clients-example >}}

More information

See the [Redis Search]({{< relref "/develop/ai/search-and-query" >}}) docs for a full description of all query features with examples.