Use ExecuteGremlinQuery with an AWS SDK

The following code examples show how to use ExecuteGremlinQuery.

Action examples are code excerpts from larger programs and must be run in context. You can see this action in context in the following code example:

• Learn the basics

Java

SDK for Java 2.x

Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

    /**
     * Executes a Gremlin PROFILE query using the provided NeptunedataClient.
     *
     * @param client The NeptunedataClient instance to be used for executing the Gremlin PROFILE query.
     */
    private static void executeGremlinProfileQuery(NeptunedataClient client) {
        System.out.println("Executing Gremlin PROFILE query...");

        ExecuteGremlinProfileQueryRequest request = ExecuteGremlinProfileQueryRequest.builder()
                .gremlinQuery("g.V().has('code', 'ANC')")
                .build();

        ExecuteGremlinProfileQueryResponse response = client.executeGremlinProfileQuery(request);
        if (response.output() != null) {
            System.out.println("Query Profile Output:");
            System.out.println(response.output());
        } else {
            System.out.println("No output returned from the profile query.");
        }
    }

• For API details, see ExecuteGremlinQuery in AWS SDK for Java 2.x API Reference.

Python

SDK for Python (Boto3)

Note

There's more on GitHub. Find the complete example and learn how to set up and run in the AWS Code Examples Repository.

"""
Running this example.

----------------------------------------------------------------------------------
VPC Networking Requirement:
----------------------------------------------------------------------------------
Amazon Neptune must be accessed from **within the same VPC** as the Neptune cluster.
It does not expose a public endpoint, so this code must be executed from:

  - An **AWS Lambda function** configured to run inside the same VPC
  - An **EC2 instance** or **ECS task** running in the same VPC
  - A connected environment such as a **VPN**, **AWS Direct Connect**, or a **peered VPC**

"""

# Replace with your actual Neptune endpoint
NEPTUNE_ENDPOINT = "https://[Specify-Your-Endpoint]:8182"

def main():
    """
    Entry point of the program. Initializes the Neptune client and runs both EXPLAIN and PROFILE queries.
    """
    config = Config(connect_timeout=10, read_timeout=30, retries={'max_attempts': 3})

    neptune_client = boto3.client(
        "neptunedata",
        endpoint_url=NEPTUNE_ENDPOINT,
        config=config
    )

    try:
        run_profile_query(neptune_client)
    except ClientError as e:
        print(f"Neptune error: {e.response['Error']['Message']}")
    except BotoCoreError as e:
        print(f"BotoCore error: {str(e)}")
    except Exception as e:
        print(f"Unexpected error: {str(e)}")

def run_profile_query(neptune_client):
    """
    Runs a PROFILE query on the Neptune graph database.
    """
    print("Running Gremlin PROFILE query...")

    try:
        response = neptune_client.execute_gremlin_profile_query(
            gremlinQuery="g.V().has('code', 'ANC')"
        )
        print("Profile Query Result:")
        output = response.get("output")
        if output:
            print(output.read().decode('utf-8'))
        else:
            print("No explain output returned.")
    except Exception as e:
        print(f"Failed to execute PROFILE query: {str(e)}")


if __name__ == "__main__":
    main()

• For API details, see ExecuteGremlinQuery in AWS SDK for Python (Boto3) API Reference.