Hyper-Converged Database (HCD) quickstart for collections (Java)

network_check Beginner
query_builder 15 min

If your data is fully structured and you want to use a fixed schema, see the quickstart for tables instead.

This quickstart demonstrates how to create a collection, insert data with vector embeddings to the collection, and perform a vector search to find similar data.

To learn more about vector databases and vector search, see About vector databases and What is Vector Search.

Store your endpoint

The Data API endpoint for your database has the form: http://CLUSTER_HOST:GATEWAY_PORT

  • Replace CLUSTER_HOST with the external IP address of any node in your cluster. To find this, run kubectl get nodes -o wide and use any of the values listed under "EXTERNAL-IP" in the output.

  • Replace GATEWAY_PORT with the port number for your API gateway service. To find this, run kubectl get svc and look for the "PORT(S)" value that corresponds to NodePort.

For this quickstart, store the endpoint in an environment variable:

  • Linux or macOS

  • Windows

export API_ENDPOINT=API_ENDPOINT
set API_ENDPOINT=API_ENDPOINT

Store your username and password

You set a username and password when you create a cluster.

If you didn’t provide superuser credentials when you created your cluster, they were generated automatically and saved in a superuser secret named CLUSTER_NAME-superuser. The CLUSTER_NAME-superuser secret contains both the username and the password.

For this quickstart, store the username and password in environment variables:

  • Linux or macOS

  • Windows

export USERNAME=USERNAME
export PASSWORD=PASSWORD
set USERNAME=USERNAME
set PASSWORD=PASSWORD

Install a client

Install one of the Data API clients to facilitate interactions with the Data API.

  • Maven

  • Gradle

  1. Update to Java version 17 or later if needed. DataStax recommends Java 21.

  2. Update to Apache Maven™ version 3.9 or later if needed.

  3. Add a dependency to the latest version of the astra-db-java package.

    pom.xml
    <dependencies>
  <dependency>
    <groupId>com.datastax.astra</groupId>
    <artifactId>astra-db-java</artifactId>
    <version>VERSION</version>
  </dependency>
</dependencies>

  1. Update to Java version 17 or later if needed. DataStax recommends Java 21.

  2. Update to Gradle version 11 or later if needed.

  3. Add a dependency to the latest version of the astra-db-java package.

    build.gradle(.kts)
    dependencies {
    implementation 'com.datastax.astra:astra-db-java:VERSION'
}

Connect to your database

The following function will connect to your database.

Copy the file into your project. You don’t need to execute the function now; the subsequent code examples will import and use this function.

src/main/java/com/quickstart/QuickstartConnect.java
package com.quickstart;

import com.datastax.astra.client.DataAPIClient;
import com.datastax.astra.client.DataAPIClients;
import com.datastax.astra.client.databases.Database;

public class QuickstartConnect {

  /**
   * Connects to your database. This function retrieves the database endpoint and application token
   * from the environment variables `API_ENDPOINT`, `USERNAME`, and `PASSWORD`.
   *
   * @return an instance of the connected database
   * @throws IllegalStateException if the environment variables `API_ENDPOINT`, `USERNAME`, or
   *     `PASSWORD` are not defined
   */
  public static Database connectToDatabase(String keyspace) {
    String endpoint = System.getenv("API_ENDPOINT"); (1)
    String username = System.getenv("USERNAME");
    String password = System.getenv("PASSWORD");

    if (endpoint == null || username == null || password == null) {
      throw new IllegalStateException(
          "Environment variables API_ENDPOINT, USERNAME, and PASSWORD must be defined");
    }

    // Create an instance of `DataAPIClient`
    DataAPIClient client = DataAPIClients.clientHCD(username, password);

    // Get the database specified by your endpoint
    Database database;
    if (keyspace != null && !keyspace.trim().isEmpty()) {
      // Connect with the provided keyspace
      database = client.getDatabase(endpoint, keyspace);
      System.out.println("Connected to database with keyspace: " + keyspace);
    } else {
      // Default connection without a specific keyspace
      database = client.getDatabase(endpoint);
      System.out.println("Connected to database (no keyspace specified).");
    }

    return database;
  }

  public static Database connectToDatabase() {
    return connectToDatabase(null);
  }
}
1 Store your database’s endpoint, username, and password in environment variables named API_ENDPOINT, USERNAME, and PASSWORD, as instructed in Store your endpoint and Store your username and password.

Create a keyspace

The following code will create a new keyspace in your database.

  1. Copy the code into your project.

  2. If needed, update the import path to the "connect to database" function from the previous section.

  3. Execute the code.

    For information about executing code, refer to the documentation for your programming language.

    Once the code completes, you should see a printed message confirming keyspace creation.

src/main/java/com/quickstart/QuickstartCreateKeyspaceDemo.java
package com.quickstart;

import com.datastax.astra.client.admin.DatabaseAdmin;
import com.datastax.astra.client.databases.Database;

public class QuickstartCreateKeyspaceDemo {

  public static void main(String[] args) {
    Database database = QuickstartConnect.connectToDatabase(); (1)

    // Get an admin object
    DatabaseAdmin admin = database.getDatabaseAdmin();

    // Create a keyspace
    admin.createKeyspace("quickstart_keyspace"); (2)

    System.out.println("Created keyspace");
  }
}
1 This is the connectToDatabase function from the previous section.

To use the function, ensure you stored your database’s endpoint, username, and password in environment variables as instructed in Store your endpoint and Store your username and password.
2 This code creates a keyspace named quickstart_keyspace. If you want to use a different name, change the name before running the code.

Create a collection

The following code will create an empty collection in your database.

  1. Copy the code into your project.

  2. If needed, update the import path to the "connect to database" function from the previous section.

  3. Execute the code.

    For information about executing code, refer to the documentation for your programming language.

    Once the code completes, you should see a printed message confirming the collection creation.

src/main/java/com/quickstart/QuickstartCreateCollectionDemo.java
package com.quickstart;

import com.datastax.astra.client.collections.Collection;
import com.datastax.astra.client.collections.definition.CollectionDefinition;
import com.datastax.astra.client.collections.definition.documents.Document;
import com.datastax.astra.client.core.vector.SimilarityMetric;
import com.datastax.astra.client.databases.Database;

public class QuickstartCreateCollectionDemo {

  public static void main(String[] args) {
    Database database = QuickstartConnect.connectToDatabase("quickstart_keyspace"); (1)

    Collection<Document> collection =
        database.createCollection(
            "quickstart_collection", (2)
            new CollectionDefinition() (3)
                .vectorDimension(5)
                .vectorSimilarity(SimilarityMetric.COSINE));

    System.out.println("Created collection " + collection.getCollectionName());
  }
}
1 This is the connectToDatabase function from the previous section.

To use the function, ensure you stored your database’s endpoint, username, and password in environment variables as instructed in Store your endpoint and Store your username and password.

If you used a different keyspace name in the previous section, update it here.
2 This code creates a collection named quickstart_collection. If you want to use a different name, change the name before running the code.
3 This collection will store 5-dimensional vector data and use the cosine similarity metric for comparisons.

Insert data to your collection

The following code will insert data from a JSON file to your collection.

  1. Copy the code into your project.

  2. Download the quickstart_dataset.json sample dataset (76 kB). This dataset is a JSON array describing library books.

  3. Replace PATH_TO_DATA_FILE in the code with the path to the dataset.

  4. If needed, update the import path to the "connect to database" function from the previous section.

  5. Execute the code.

    For information about executing code, refer to the documentation for your programming language.

    Once the code completes, you should see a printed message confirming the insertion of 100 documents.

src/main/java/com/quickstart/QuickstartInsertToCollectionDemo.java
package com.quickstart;

import com.datastax.astra.client.collections.Collection;
import com.datastax.astra.client.collections.commands.results.CollectionInsertManyResult;
import com.datastax.astra.client.collections.definition.documents.Document;
import com.datastax.astra.client.databases.Database;
import com.fasterxml.jackson.core.type.TypeReference;
import com.fasterxml.jackson.databind.ObjectMapper;
import java.io.File;
import java.io.FileInputStream;
import java.util.List;

public class QuickstartInsertToCollectionDemo {

  public static void main(String[] args) throws Exception {
    Database database = QuickstartConnect.connectToDatabase("quickstart_keyspace"); (1)

    Collection<Document> collection = database.getCollection("quickstart_collection"); (2)

    // Read the JSON file
    File jsonFile =
        new File(
            QuickstartInsertToCollectionDemo.class
                .getClassLoader()
                .getResource("PATH_TO_DATA_FILE") (3)
                .toURI());

    // Load the JSON file into a list of documents
    List<Document> documents =
        new ObjectMapper().readValue(new FileInputStream(jsonFile), new TypeReference<>() {});

    // Populate the reserved $vector field for each document
    List<Document> documentsWithVectorField =
        documents.stream()
            .peek(
                document -> {
                  if (document.containsKey("summary_genres_vector")) {
                    document.put("$vector", document.get("summary_genres_vector"));
                    document.remove("summary_genres_vector");
                  }
                })
            .toList();

    CollectionInsertManyResult result = collection.insertMany(documentsWithVectorField);

    System.out.println("Inserted " + result.getInsertedIds().size() + " documents.");
  }
}
1 This is the connectToDatabase function from the previous section.

To use the function, ensure you stored your database’s endpoint, username, and password in environment variables as instructed in Store your endpoint and Store your username and password.

If you used a different keyspace name in the previous sections, update it here.
2 This code expects that your keyspace has a collection named quickstart_collection. If you used a different collection name in the previous sections, update it here.
3 Replace PATH_TO_DATA_FILE with the path to the JSON data file.

Find data in your collection

After you insert data to your collection, you can search the data. In addition to traditional database filtering, you can perform a vector search to find data that is most similar to a search vector.

The following code performs three searches on the sample data that you loaded in Insert data to your collection.

src/main/java/com/quickstart/QuickstartFindDemo.java
package com.quickstart;

import static com.datastax.astra.client.core.query.Projection.include;

import com.datastax.astra.client.collections.Collection;
import com.datastax.astra.client.collections.commands.options.CollectionFindOneOptions;
import com.datastax.astra.client.collections.commands.options.CollectionFindOptions;
import com.datastax.astra.client.collections.definition.documents.Document;
import com.datastax.astra.client.core.query.Filter;
import com.datastax.astra.client.core.query.Filters;
import com.datastax.astra.client.core.query.Sort;
import com.datastax.astra.client.databases.Database;

public class QuickstartFindDemo {

  public static void main(String[] args) {

    Database database = QuickstartConnect.connectToDatabase("quickstart_keyspace"); (1)

    Collection<Document> collection = database.getCollection("quickstart_collection"); (2)

    // Find documents that match a filter
    System.out.println("\nFinding books with rating greater than 4.7...");

    Filter filter = Filters.gt("rating", 4.7);

    CollectionFindOptions options = new CollectionFindOptions().limit(10);

    collection
        .find(filter, options)
        .forEach(
            document -> {
              System.out.println(
                  document.getString("title") + " is rated " + document.get("rating"));
            });

    // Perform a vector search to find the closest match to a given vector
    System.out.println("\nUsing vector search to find a book...");

    CollectionFindOneOptions options2 =
        new CollectionFindOneOptions()
            .sort(
                Sort.vector(
                    new float[] {
                      0.016326904f, -0.031677246f, 0.04815674f, 0.0033435822f, 0.01876831f
                    }));

    collection
        .findOne(options2)
        .ifPresent(
            document -> {
              System.out.println(document.getString("title") + " is the best match");
            });

    // Combine a filter, vector search, and projection to find the 3 books with
    // more than 400 pages that are the closest matches to a given vector,
    // and just return the title and author
    System.out.println(
        "\nUsing filters and vector search to find 3 books with more than 400 pages, returning just the title and author...");

    Filter filter3 = Filters.gt("number_of_pages", 400);

    CollectionFindOptions options3 =
        new CollectionFindOptions()
            .limit(3)
            .sort(
                Sort.vector(
                    new float[] {
                      0.016326904f, -0.031677246f, 0.04815674f, 0.0033435822f, 0.01876831f
                    }))
            .projection(include("title", "author"));

    collection
        .find(filter3, options3)
        .forEach(
            document -> {
              System.out.println(document);
            });
  }
}
1 This is the connectToDatabase function from the previous section.

To use the function, ensure you stored your database’s endpoint, username, and password in environment variables as instructed in Store your endpoint and Store your username and password.

If you used a different keyspace name in the previous sections, update it here.
2 This code expects that your keyspace has a collection named quickstart_collection. If you used a different collection name in the previous sections, update it here.

Next steps

For more practice, you can continue building with the collection that you created here. For example, try inserting more data to the collection, or try different searches. The Data API reference provides code examples for various operations.

Insert data from different sources

This quickstart demonstrated how to insert data from a JSON file, but you can insert data from many sources, including CSV and PDF files.

This quickstart also demonstrated how to insert data to a collection, which uses a flexible schema. If your data is structured and you want to use a fixed schema, you can use a table instead of a collection. See the quickstart for tables.

Perform more complex searches

This quickstart demonstrated how to find data using filters and vector search. To learn more about the searches you can perform, see Find a document (Java), Find documents (Java), and Find data with vector search.

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