Créer une offre d'emploi à partir d'un modèle (asynchrone)

Explique comment créer une tâche à partir d'un modèle.

Exemple de code

C#

Pour vous authentifier auprès de Dataflow, configurez le service Identifiants par défaut de l'application. Pour en savoir plus, consultez la page Configurer l'authentification pour un environnement de développement local.

using Google.Cloud.Dataflow.V1Beta3;
using System.Threading.Tasks;

public sealed partial class GeneratedTemplatesServiceClientSnippets
{
    /// <summary>Snippet for CreateJobFromTemplateAsync</summary>
    /// <remarks>
    /// This snippet has been automatically generated and should be regarded as a code template only.
    /// It will require modifications to work:
    /// - It may require correct/in-range values for request initialization.
    /// - It may require specifying regional endpoints when creating the service client as shown in
    ///   https://cloud.google.com/dotnet/docs/reference/help/client-configuration#endpoint.
    /// </remarks>
    public async Task CreateJobFromTemplateRequestObjectAsync()
    {
        // Create client
        TemplatesServiceClient templatesServiceClient = await TemplatesServiceClient.CreateAsync();
        // Initialize request argument(s)
        CreateJobFromTemplateRequest request = new CreateJobFromTemplateRequest
        {
            ProjectId = "",
            GcsPath = "",
            Parameters = { { "", "" }, },
            JobName = "",
            Environment = new RuntimeEnvironment(),
            Location = "",
        };
        // Make the request
        Job response = await templatesServiceClient.CreateJobFromTemplateAsync(request);
    }
}

Java

Pour vous authentifier auprès de Dataflow, configurez le service Identifiants par défaut de l'application. Pour en savoir plus, consultez la page Configurer l'authentification pour un environnement de développement local.

import com.google.api.core.ApiFuture;
import com.google.dataflow.v1beta3.CreateJobFromTemplateRequest;
import com.google.dataflow.v1beta3.Job;
import com.google.dataflow.v1beta3.RuntimeEnvironment;
import com.google.dataflow.v1beta3.TemplatesServiceClient;
import java.util.HashMap;

public class AsyncCreateJobFromTemplate {

  public static void main(String[] args) throws Exception {
    asyncCreateJobFromTemplate();
  }

  public static void asyncCreateJobFromTemplate() throws Exception {
    // This snippet has been automatically generated and should be regarded as a code template only.
    // It will require modifications to work:
    // - It may require correct/in-range values for request initialization.
    // - It may require specifying regional endpoints when creating the service client as shown in
    // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
    try (TemplatesServiceClient templatesServiceClient = TemplatesServiceClient.create()) {
      CreateJobFromTemplateRequest request =
          CreateJobFromTemplateRequest.newBuilder()
              .setProjectId("projectId-894832108")
              .setJobName("jobName-1438096408")
              .putAllParameters(new HashMap<String, String>())
              .setEnvironment(RuntimeEnvironment.newBuilder().build())
              .setLocation("location1901043637")
              .build();
      ApiFuture<Job> future =
          templatesServiceClient.createJobFromTemplateCallable().futureCall(request);
      // Do something.
      Job response = future.get();
    }
  }
}

Node.js

Pour vous authentifier auprès de Dataflow, configurez le service Identifiants par défaut de l'application. Pour en savoir plus, consultez la page Configurer l'authentification pour un environnement de développement local.

/**
 * This snippet has been automatically generated and should be regarded as a code template only.
 * It will require modifications to work.
 * It may require correct/in-range values for request initialization.
 * TODO(developer): Uncomment these variables before running the sample.
 */
/**
 *  Required. The ID of the Cloud Platform project that the job belongs to.
 */
// const projectId = 'abc123'
/**
 *  Required. The job name to use for the created job.
 */
// const jobName = 'abc123'
/**
 *  Required. A Cloud Storage path to the template from which to
 *  create the job.
 *  Must be a valid Cloud Storage URL, beginning with `gs://`.
 */
// const gcsPath = 'abc123'
/**
 *  The runtime parameters to pass to the job.
 */
// const parameters = [1,2,3,4]
/**
 *  The runtime environment for the job.
 */
// const environment = {}
/**
 *  The regional endpoint
 *  (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) to
 *  which to direct the request.
 */
// const location = 'abc123'

// Imports the Dataflow library
const {TemplatesServiceClient} = require('@google-cloud/dataflow').v1beta3;

// Instantiates a client
const dataflowClient = new TemplatesServiceClient();

async function callCreateJobFromTemplate() {
  // Construct request
  const request = {
  };

  // Run request
  const response = await dataflowClient.createJobFromTemplate(request);
  console.log(response);
}

callCreateJobFromTemplate();

Python

Pour vous authentifier auprès de Dataflow, configurez le service Identifiants par défaut de l'application. Pour en savoir plus, consultez la page Configurer l'authentification pour un environnement de développement local.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dataflow_v1beta3

async def sample_create_job_from_template():
    # Create a client
    client = dataflow_v1beta3.TemplatesServiceAsyncClient()

    # Initialize request argument(s)
    request = dataflow_v1beta3.CreateJobFromTemplateRequest(
        gcs_path="gcs_path_value",
    )

    # Make the request
    response = await client.create_job_from_template(request=request)

    # Handle the response
    print(response)

Étapes suivantes

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