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Créer et envoyer une tâche de conteneur de base

Créez et envoyez un exemple de job par lot qui exécute une commande simple spécifiée en tant qu'image de conteneur. Une fois le job envoyé, Batch le met automatiquement en file d'attente, le planifie et l'exécute sur des VM Compute Engine.

En savoir plus

Pour obtenir une documentation détaillée incluant cet exemple de code, consultez les articles suivants :

Créer et exécuter une tâche de base

Exemple de code

C++

Pour en savoir plus, consultez la documentation de référence de l'API C++ par lot.

Pour vous authentifier auprès de Batch, configurez les Identifiants par défaut de l'application. Pour en savoir plus, consultez Configurer l'authentification pour un environnement de développement local.

#include "google/cloud/batch/v1/batch_client.h"

  [](std::string const& project_id, std::string const& location_id,
     std::string const& job_id) {
    // Initialize the request; start with the fields that depend on the sample
    // input.
    google::cloud::batch::v1::CreateJobRequest request;
    request.set_parent("projects/" + project_id + "/locations/" + location_id);
    request.set_job_id(job_id);
    // Most of the job description is fixed in this example; use a string to
    // initialize it.
    auto constexpr kText = R"pb(
      task_groups {
        task_count: 4
        task_spec {
          compute_resource { cpu_milli: 500 memory_mib: 16 }
          max_retry_count: 2
          max_run_duration { seconds: 3600 }
          runnables {
            container {
              image_uri: "gcr.io/google-containers/busybox"
              entrypoint: "/bin/sh"
              commands: "-c"
              commands: "echo Hello world! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks."
            }
          }
        }
      }
      allocation_policy {
        instances {
          policy { machine_type: "e2-standard-4" provisioning_model: STANDARD }
        }
      }
      labels { key: "env" value: "testing" }
      labels { key: "type" value: "container" }
      logs_policy { destination: CLOUD_LOGGING }
    )pb";
    auto* job = request.mutable_job();
    if (!google::protobuf::TextFormat::ParseFromString(kText, job)) {
      throw std::runtime_error("Error parsing Job description");
    }
    // Create a client and issue the request.
    auto client = google::cloud::batch_v1::BatchServiceClient(
        google::cloud::batch_v1::MakeBatchServiceConnection());
    auto response = client.CreateJob(request);
    if (!response) throw std::move(response).status();
    std::cout << "Job : " << response->DebugString() << "\n";
  }

Go

Pour en savoir plus, consultez la documentation de référence de l'API Go par lot.

import (
	"context"
	"fmt"
	"io"

	batch "cloud.google.com/go/batch/apiv1"
	"cloud.google.com/go/batch/apiv1/batchpb"
	durationpb "google.golang.org/protobuf/types/known/durationpb"
)

// Creates and runs a job that runs the specified container
func createContainerJob(w io.Writer, projectID, region, jobName string) error {
	// projectID := "your_project_id"
	// region := "us-central1"
	// jobName := "some-job"

	ctx := context.Background()
	batchClient, err := batch.NewClient(ctx)
	if err != nil {
		return fmt.Errorf("NewClient: %w", err)
	}
	defer batchClient.Close()

	container := &batchpb.Runnable_Container{
		ImageUri:   "gcr.io/google-containers/busybox",
		Commands:   []string{"-c", "echo Hello world! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks."},
		Entrypoint: "/bin/sh",
	}

	// We can specify what resources are requested by each task.
	resources := &batchpb.ComputeResource{
		// CpuMilli is milliseconds per cpu-second. This means the task requires 2 whole CPUs.
		CpuMilli:  2000,
		MemoryMib: 16,
	}

	taskSpec := &batchpb.TaskSpec{
		Runnables: []*batchpb.Runnable{{
			Executable: &batchpb.Runnable_Container_{Container: container},
		}},
		ComputeResource: resources,
		MaxRunDuration: &durationpb.Duration{
			Seconds: 3600,
		},
		MaxRetryCount: 2,
	}

	// Tasks are grouped inside a job using TaskGroups.
	taskGroups := []*batchpb.TaskGroup{
		{
			TaskCount: 4,
			TaskSpec:  taskSpec,
		},
	}

	// Policies are used to define on what kind of virtual machines the tasks will run on.
	// In this case, we tell the system to use "e2-standard-4" machine type.
	// Read more about machine types here: https://cloud.google.com/compute/docs/machine-types
	allocationPolicy := &batchpb.AllocationPolicy{
		Instances: []*batchpb.AllocationPolicy_InstancePolicyOrTemplate{{
			PolicyTemplate: &batchpb.AllocationPolicy_InstancePolicyOrTemplate_Policy{
				Policy: &batchpb.AllocationPolicy_InstancePolicy{
					MachineType: "e2-standard-4",
				},
			},
		}},
	}

	// We use Cloud Logging as it's an out of the box available option
	logsPolicy := &batchpb.LogsPolicy{
		Destination: batchpb.LogsPolicy_CLOUD_LOGGING,
	}

	jobLabels := map[string]string{"env": "testing", "type": "container"}

	// The job's parent is the region in which the job will run
	parent := fmt.Sprintf("projects/%s/locations/%s", projectID, region)

	job := batchpb.Job{
		TaskGroups:       taskGroups,
		AllocationPolicy: allocationPolicy,
		Labels:           jobLabels,
		LogsPolicy:       logsPolicy,
	}

	req := &batchpb.CreateJobRequest{
		Parent: parent,
		JobId:  jobName,
		Job:    &job,
	}

	created_job, err := batchClient.CreateJob(ctx, req)
	if err != nil {
		return fmt.Errorf("unable to create job: %w", err)
	}

	fmt.Fprintf(w, "Job created: %v\n", created_job)

	return nil
}

Java

Pour en savoir plus, consultez la documentation de référence de l'API Java par lot.

import com.google.cloud.batch.v1.AllocationPolicy;
import com.google.cloud.batch.v1.AllocationPolicy.InstancePolicy;
import com.google.cloud.batch.v1.AllocationPolicy.InstancePolicyOrTemplate;
import com.google.cloud.batch.v1.BatchServiceClient;
import com.google.cloud.batch.v1.ComputeResource;
import com.google.cloud.batch.v1.CreateJobRequest;
import com.google.cloud.batch.v1.Job;
import com.google.cloud.batch.v1.LogsPolicy;
import com.google.cloud.batch.v1.LogsPolicy.Destination;
import com.google.cloud.batch.v1.Runnable;
import com.google.cloud.batch.v1.Runnable.Container;
import com.google.cloud.batch.v1.TaskGroup;
import com.google.cloud.batch.v1.TaskSpec;
import com.google.protobuf.Duration;
import java.io.IOException;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.TimeoutException;

public class CreateWithContainerNoMounting {

  public static void main(String[] args)
      throws IOException, ExecutionException, InterruptedException, TimeoutException {
    // TODO(developer): Replace these variables before running the sample.
    // Project ID or project number of the Cloud project you want to use.
    String projectId = "YOUR_PROJECT_ID";

    // Name of the region you want to use to run the job. Regions that are
    // available for Batch are listed on: https://cloud.google.com/batch/docs/get-started#locations
    String region = "europe-central2";

    // The name of the job that will be created.
    // It needs to be unique for each project and region pair.
    String jobName = "JOB_NAME";

    createContainerJob(projectId, region, jobName);
  }

  // This method shows how to create a sample Batch Job that will run a simple command inside a
  // container on Cloud Compute instances.
  public static void createContainerJob(String projectId, String region, String jobName)
      throws IOException, ExecutionException, InterruptedException, TimeoutException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the `batchServiceClient.close()` method on the client to safely
    // clean up any remaining background resources.
    try (BatchServiceClient batchServiceClient = BatchServiceClient.create()) {

      // Define what will be done as part of the job.
      Runnable runnable =
          Runnable.newBuilder()
              .setContainer(
                  Container.newBuilder()
                      .setImageUri("gcr.io/google-containers/busybox")
                      .setEntrypoint("/bin/sh")
                      .addCommands("-c")
                      .addCommands(
                          "echo Hello world! This is task ${BATCH_TASK_INDEX}. "
                              + "This job has a total of ${BATCH_TASK_COUNT} tasks.")
                      .build())
              .build();

      // We can specify what resources are requested by each task.
      ComputeResource computeResource =
          ComputeResource.newBuilder()
              // In milliseconds per cpu-second. This means the task requires 2 whole CPUs.
              .setCpuMilli(2000)
              // In MiB.
              .setMemoryMib(16)
              .build();

      TaskSpec task =
          TaskSpec.newBuilder()
              // Jobs can be divided into tasks. In this case, we have only one task.
              .addRunnables(runnable)
              .setComputeResource(computeResource)
              .setMaxRetryCount(2)
              .setMaxRunDuration(Duration.newBuilder().setSeconds(3600).build())
              .build();

      // Tasks are grouped inside a job using TaskGroups.
      // Currently, it's possible to have only one task group.
      TaskGroup taskGroup = TaskGroup.newBuilder().setTaskCount(4).setTaskSpec(task).build();

      // Policies are used to define on what kind of virtual machines the tasks will run on.
      // In this case, we tell the system to use "e2-standard-4" machine type.
      // Read more about machine types here: https://cloud.google.com/compute/docs/machine-types
      InstancePolicy instancePolicy =
          InstancePolicy.newBuilder().setMachineType("e2-standard-4").build();

      AllocationPolicy allocationPolicy =
          AllocationPolicy.newBuilder()
              .addInstances(InstancePolicyOrTemplate.newBuilder().setPolicy(instancePolicy).build())
              .build();

      Job job =
          Job.newBuilder()
              .addTaskGroups(taskGroup)
              .setAllocationPolicy(allocationPolicy)
              .putLabels("env", "testing")
              .putLabels("type", "container")
              // We use Cloud Logging as it's an out of the box available option.
              .setLogsPolicy(
                  LogsPolicy.newBuilder().setDestination(Destination.CLOUD_LOGGING).build())
              .build();

      CreateJobRequest createJobRequest =
          CreateJobRequest.newBuilder()
              // The job's parent is the region in which the job will run.
              .setParent(String.format("projects/%s/locations/%s", projectId, region))
              .setJob(job)
              .setJobId(jobName)
              .build();

      Job result =
          batchServiceClient
              .createJobCallable()
              .futureCall(createJobRequest)
              .get(5, TimeUnit.MINUTES);

      System.out.printf("Successfully created the job: %s", result.getName());
    }
  }
}

Node.js

Pour en savoir plus, consultez la documentation de référence de l'API Node.js par lot.

/**
 * TODO(developer): Uncomment and replace these variables before running the sample.
 */
// const projectId = 'YOUR_PROJECT_ID';
/**
 * The region you want to the job to run in. The regions that support Batch are listed here:
 * https://cloud.google.com/batch/docs/get-started#locations
 */
// const region = 'us-central-1';
/**
 * The name of the job that will be created.
 * It needs to be unique for each project and region pair.
 */
// const jobName = 'YOUR_JOB_NAME';

// Imports the Batch library
const batchLib = require('@google-cloud/batch');
const batch = batchLib.protos.google.cloud.batch.v1;

// Instantiates a client
const batchClient = new batchLib.v1.BatchServiceClient();

// Define what will be done as part of the job.
const task = new batch.TaskSpec();
const runnable = new batch.Runnable();
runnable.container = new batch.Runnable.Container();
runnable.container.imageUri = 'gcr.io/google-containers/busybox';
runnable.container.entrypoint = '/bin/sh';
runnable.container.commands = [
  '-c',
  'echo Hello world! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks.',
];
task.runnables = [runnable];

// We can specify what resources are requested by each task.
const resources = new batch.ComputeResource();
resources.cpuMilli = 2000; // in milliseconds per cpu-second. This means the task requires 2 whole CPUs.
resources.memoryMib = 16;
task.computeResource = resources;

task.maxRetryCount = 2;
task.maxRunDuration = {seconds: 3600};

// Tasks are grouped inside a job using TaskGroups.
const group = new batch.TaskGroup();
group.taskCount = 4;
group.taskSpec = task;

// Policies are used to define on what kind of virtual machines the tasks will run on.
// In this case, we tell the system to use "e2-standard-4" machine type.
// Read more about machine types here: https://cloud.google.com/compute/docs/machine-types
const allocationPolicy = new batch.AllocationPolicy();
const policy = new batch.AllocationPolicy.InstancePolicy();
policy.machineType = 'e2-standard-4';
const instances = new batch.AllocationPolicy.InstancePolicyOrTemplate();
instances.policy = policy;
allocationPolicy.instances = [instances];

const job = new batch.Job();
job.name = jobName;
job.taskGroups = [group];
job.allocationPolicy = allocationPolicy;
job.labels = {env: 'testing', type: 'container'};
// We use Cloud Logging as it's an option available out of the box
job.logsPolicy = new batch.LogsPolicy();
job.logsPolicy.destination = batch.LogsPolicy.Destination.CLOUD_LOGGING;

// The job's parent is the project and region in which the job will run
const parent = `projects/${projectId}/locations/${region}`;

async function callCreateJob() {
  // Construct request
  const request = {
    parent,
    jobId: jobName,
    job,
  };

  // Run request
  const response = await batchClient.createJob(request);
  console.log(response);
}

await callCreateJob();

Python

Pour en savoir plus, consultez la documentation de référence de l'API Python par lot.

from google.cloud import batch_v1


def create_container_job(project_id: str, region: str, job_name: str) -> batch_v1.Job:
    """
    This method shows how to create a sample Batch Job that will run
    a simple command inside a container on Cloud Compute instances.

    Args:
        project_id: project ID or project number of the Cloud project you want to use.
        region: name of the region you want to use to run the job. Regions that are
            available for Batch are listed on: https://cloud.google.com/batch/docs/get-started#locations
        job_name: the name of the job that will be created.
            It needs to be unique for each project and region pair.

    Returns:
        A job object representing the job created.
    """
    client = batch_v1.BatchServiceClient()

    # Define what will be done as part of the job.
    runnable = batch_v1.Runnable()
    runnable.container = batch_v1.Runnable.Container()
    runnable.container.image_uri = "gcr.io/google-containers/busybox"
    runnable.container.entrypoint = "/bin/sh"
    runnable.container.commands = [
        "-c",
        "echo Hello world! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks.",
    ]

    # Jobs can be divided into tasks. In this case, we have only one task.
    task = batch_v1.TaskSpec()
    task.runnables = [runnable]

    # We can specify what resources are requested by each task.
    resources = batch_v1.ComputeResource()
    resources.cpu_milli = 2000  # in milliseconds per cpu-second. This means the task requires 2 whole CPUs.
    resources.memory_mib = 16  # in MiB
    task.compute_resource = resources

    task.max_retry_count = 2
    task.max_run_duration = "3600s"

    # Tasks are grouped inside a job using TaskGroups.
    # Currently, it's possible to have only one task group.
    group = batch_v1.TaskGroup()
    group.task_count = 4
    group.task_spec = task

    # Policies are used to define on what kind of virtual machines the tasks will run on.
    # In this case, we tell the system to use "e2-standard-4" machine type.
    # Read more about machine types here: https://cloud.google.com/compute/docs/machine-types
    policy = batch_v1.AllocationPolicy.InstancePolicy()
    policy.machine_type = "e2-standard-4"
    instances = batch_v1.AllocationPolicy.InstancePolicyOrTemplate()
    instances.policy = policy
    allocation_policy = batch_v1.AllocationPolicy()
    allocation_policy.instances = [instances]

    job = batch_v1.Job()
    job.task_groups = [group]
    job.allocation_policy = allocation_policy
    job.labels = {"env": "testing", "type": "container"}
    # We use Cloud Logging as it's an out of the box available option
    job.logs_policy = batch_v1.LogsPolicy()
    job.logs_policy.destination = batch_v1.LogsPolicy.Destination.CLOUD_LOGGING

    create_request = batch_v1.CreateJobRequest()
    create_request.job = job
    create_request.job_id = job_name
    # The job's parent is the region in which the job will run
    create_request.parent = f"projects/{project_id}/locations/{region}"

    return client.create_job(create_request)

Étape suivante

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