Mit ExecuteGremlinQuery einem SDK verwenden AWS

Die folgenden Code-Beispiele zeigen, wie ExecuteGremlinQuery verwendet wird.

Java

SDK für Java 2.x

Anmerkung

Es gibt noch mehr dazu GitHub. Hier finden Sie das vollständige Beispiel und erfahren, wie Sie das AWS -Code-Beispiel- einrichten und ausführen.

    /**
     * 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.");
        }
    }

• Einzelheiten zur API finden Sie ExecuteGremlinQueryin der AWS SDK for Java 2.x API-Referenz.

Python

SDK für Python (Boto3)

Anmerkung

Es gibt noch mehr dazu GitHub. Hier finden Sie das vollständige Beispiel und erfahren, wie Sie das AWS -Code-Beispiel- einrichten und ausführen.

"""
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()

• Einzelheiten zur API finden Sie ExecuteGremlinQueryin AWS SDK for Python (Boto3) API Reference.