Définir des ressources de tâche à l'aide d'un modèle d'instance de VM

Ce document explique comment définir les ressources de VM pour une tâche de traitement par lot en spécifiant un modèle d'instance de VM Compute Engine lorsque vous créez la tâche.

Les types de ressources VM sur lesquels un job s'exécute sont automatiquement définis par Batch, sauf si vous les définissez à l'aide de l'une des méthodes suivantes:

  • Définissez directement les ressources de VM d'une tâche à l'aide du champ instances[].policy. Cette méthode est illustrée dans la plupart des documents Batch.

  • Définissez les ressources de VM d'une tâche à l'aide d'un modèle à l'aide du champ instances[].instanceTemplate. C'est la méthode expliquée dans ce document.

    L'utilisation d'un modèle est obligatoire pour spécifier les options de VM pour lesquelles Batch ne fournit pas de champs de tâche. L'utilisation d'un modèle peut également être pratique lorsque vous souhaitez spécifier les mêmes ressources de VM pour plusieurs jobs.

Avant de commencer

  1. Si vous n'avez jamais utilisé Batch, consultez Premiers pas avec Batch et activez Batch en remplissant les conditions préalables pour les projets et les utilisateurs.
  2. Créez un modèle d'instance ou identifiez un modèle d'instance existant.

  3. Pour obtenir les autorisations nécessaires pour créer un job, demandez à votre administrateur de vous accorder les rôles IAM suivants:

    Pour en savoir plus sur l'attribution de rôles, consultez la page Gérer l'accès aux projets, aux dossiers et aux organisations.

    Vous pouvez également obtenir les autorisations requises via des rôles personnalisés ou d'autres rôles prédéfinis.

Créer une tâche à l'aide d'un modèle d'instance de VM Compute Engine

Cette section fournit des exemples de création d'une tâche de script de base à partir d'un modèle d'instance de VM existant. Vous pouvez créer un job à partir d'un modèle d'instance de VM à l'aide de la gcloud CLI, de l'API Batch, de Go, de Java, de Node.js, de Python ou de C++.

gcloud

Pour créer une tâche à partir d'un modèle d'instance de VM à l'aide de gcloud CLI, utilisez la commande gcloud batch jobs submit et spécifiez le modèle d'instance de VM dans le fichier de configuration JSON de la tâche.

Par exemple, pour créer une tâche de script de base à partir d'un modèle d'instance de VM:

  1. Créez un fichier JSON dans le répertoire actuel nommé hello-world-instance-template.json avec le contenu suivant:

    {
    "taskGroups": [
        {
            "taskSpec": {
                "runnables": [
                    {
                        "script": {
                            "text": "echo Hello world! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks."
                        }
                    }
                ],
                "computeResource": {
                    "cpuMilli": 2000,
                    "memoryMib": 16
                },
                "maxRetryCount": 2,
                "maxRunDuration": "3600s"
            },
            "taskCount": 4,
            "parallelism": 2
        }
    ],
    "allocationPolicy": {
        "instances": [
            {
                "installGpuDrivers": INSTALL_GPU_DRIVERS,
                "instanceTemplate": "INSTANCE_TEMPLATE_NAME"
            }
        ]
    },
    "labels": {
        "department": "finance",
        "env": "testing"
    },
    "logsPolicy": {
        "destination": "CLOUD_LOGGING"
    }
}

    Remplacez les éléments suivants :

    • INSTALL_GPU_DRIVERS : facultatif. Lorsque la valeur est true, Batch récupère les pilotes requis pour le type de GPU que vous spécifiez dans le modèle d'instance de VM Compute Engine, puis les installe en votre nom. Pour en savoir plus, découvrez comment créer une tâche qui utilise un GPU.
    • INSTANCE_TEMPLATE_NAME: nom d'un modèle d'instance de VM Compute Engine existant. Découvrez comment créer et lister des modèles d'instance.

  2. Exécutez la commande suivante :

    gcloud batch jobs submit example-template-job \
  --location us-central1 \
  --config hello-world-instance-template.json

API

Pour créer une tâche de base à l'aide de l'API Batch, utilisez la méthode jobs.create et spécifiez un modèle d'instance de VM dans le champ allocationPolicy.

Par exemple, pour créer des tâches de script de base à partir d'un modèle d'instance de VM, utilisez la requête suivante:

POST https://batch.googleapis.com/v1/projects/PROJECT_ID/locations/us-central1/jobs?job_id=example-script-job

{
    "taskGroups": [
        {
            "taskSpec": {
                "runnables": [
                    {
                        "script": {
                            "text": "echo Hello world! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks."
                        }
                    }
                ],
                "computeResource": {
                    "cpuMilli": 2000,
                    "memoryMib": 16
                },
                "maxRetryCount": 2,
                "maxRunDuration": "3600s"
            },
            "taskCount": 4,
            "parallelism": 2
        }
    ],
    "allocationPolicy": {
        "instances": [
            {
                "installGpuDrivers": INSTALL_GPU_DRIVERS,
                "instanceTemplate": "INSTANCE_TEMPLATE_NAME"
            }
        ]
    },
    "labels": {
        "department": "finance",
        "env": "testing"
    },
    "logsPolicy": {
        "destination": "CLOUD_LOGGING"
    }
}

Remplacez les éléments suivants :

  • PROJECT_ID: ID de projet de votre projet.
  • INSTALL_GPU_DRIVERS : facultatif. Lorsque la valeur est true, Batch récupère les pilotes requis pour le type de GPU que vous spécifiez dans votre modèle d'instance de VM Compute Engine, puis les installe en votre nom. Pour en savoir plus, découvrez comment créer une tâche qui utilise un GPU.
  • INSTANCE_TEMPLATE_NAME: nom d'un modèle d'instance de VM Compute Engine existant. Découvrez comment créer et lister des modèles d'instance.

Go

Go

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

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 executes the specified script
func createScriptJobWithTemplate(w io.Writer, projectID, region, jobName, templateLink string) error {
	// projectID := "your_project_id"
	// region := "us-central1"
	// jobName := "some-job"
	/* A link to an existing Instance Template. Acceptable formats:
	*  "projects/{project_id}/global/instanceTemplates/{template_name}"
	*  "{template_name}" - if the template is defined in the same project as used to create the Job.
	 */
	// template_link := "my-instance-template"

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

	// Define what will be done as part of the job.
	command := &batchpb.Runnable_Script_Text{
		Text: "echo Hello world! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks.",
	}

	// 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_Script_{
				Script: &batchpb.Runnable_Script{Command: command},
			},
		}},
		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 are going to use an Instance Template that defines the VM.
	allocationPolicy := &batchpb.AllocationPolicy{
		Instances: []*batchpb.AllocationPolicy_InstancePolicyOrTemplate{{
			PolicyTemplate: &batchpb.AllocationPolicy_InstancePolicyOrTemplate_InstanceTemplate{
				InstanceTemplate: templateLink,
			},
		}},
	}

	// 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": "script"}

	// 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

Java

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

import com.google.cloud.batch.v1.AllocationPolicy;
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.Script;
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 CreateWithTemplate {

  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";

    // A link to an existing Instance Template. Acceptable formats:
    //   * "projects/{projectId}/global/instanceTemplates/{templateName}"
    //   * "{templateName}" - if the template is defined in the same project
    //   as used to create the Job.
    String templateLink = "TEMPLATE_LINK";

    createWithTemplate(projectId, region, jobName, templateLink);
  }

  // This method shows how to create a sample Batch Job that will run
  // a simple command on Cloud Compute instances created using a provided Template.
  public static void createWithTemplate(String projectId, String region, String jobName,
      String templateLink)
      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()
              .setScript(
                  Script.newBuilder()
                      .setText(
                          "echo Hello world! This is task ${BATCH_TASK_INDEX}. "
                              + "This job has a total of ${BATCH_TASK_COUNT} tasks.")
                      // You can also run a script from a file. Just remember, that needs to be a
                      // script that's already on the VM that will be running the job.
                      // Using setText() and setPath() is mutually exclusive.
                      // .setPath("/tmp/test.sh")
                      .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 an instance template that defines all the
      // required parameters.
      AllocationPolicy allocationPolicy =
          AllocationPolicy.newBuilder()
              .addInstances(
                  InstancePolicyOrTemplate.newBuilder().setInstanceTemplate(templateLink).build())
              .build();

      Job job =
          Job.newBuilder()
              .addTaskGroups(taskGroup)
              .setAllocationPolicy(allocationPolicy)
              .putLabels("env", "testing")
              .putLabels("type", "script")
              // 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

Node.js

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

/**
 * 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';
/**
 * a link to an existing Instance Template. Acceptable formats:
 * "projects/{project_id}/global/instanceTemplates/{template_name}"
 * "{template_name}" - if the template is defined in the same project as used to create the Job.
 */
// const templateLink = 'YOUR_TEMPLATE'

// 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.script = new batch.Runnable.Script();
runnable.script.text =
  'echo Hello world! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks.';
// You can also run a script from a file. Just remember, that needs to be a script that's
// already on the VM that will be running the job. Using runnable.script.text and runnable.script.path is mutually
// exclusive.
// runnable.script.path = '/tmp/test.sh'
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 instances = new batch.AllocationPolicy.InstancePolicyOrTemplate();
instances.instanceTemplate = templateLink;
allocationPolicy.instances = [instances];

const job = new batch.Job();
job.name = jobName;
job.taskGroups = [group];
job.allocationPolicy = allocationPolicy;
job.labels = {env: 'testing', type: 'script'};
// 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

Python

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

from google.cloud import batch_v1


def create_script_job_with_template(
    project_id: str, region: str, job_name: str, template_link: str
) -> batch_v1.Job:
    """
    This method shows how to create a sample Batch Job that will run
    a simple command on Cloud Compute instances created using a provided Template.

    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.
        template_link: a link to an existing Instance Template. Acceptable formats:
            * "projects/{project_id}/global/instanceTemplates/{template_name}"
            * "{template_name}" - if the template is defined in the same project as used to create the Job.

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

    # Define what will be done as part of the job.
    task = batch_v1.TaskSpec()
    runnable = batch_v1.Runnable()
    runnable.script = batch_v1.Runnable.Script()
    runnable.script.text = "echo Hello world! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks."
    # You can also run a script from a file. Just remember, that needs to be a script that's
    # already on the VM that will be running the job. Using runnable.script.text and runnable.script.path is mutually
    # exclusive.
    # runnable.script.path = '/tmp/test.sh'
    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
    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 an instance template that defines all the
    # required parameters.
    allocation_policy = batch_v1.AllocationPolicy()
    instances = batch_v1.AllocationPolicy.InstancePolicyOrTemplate()
    instances.instance_template = template_link
    allocation_policy.instances = [instances]

    job = batch_v1.Job()
    job.task_groups = [group]
    job.allocation_policy = allocation_policy
    job.labels = {"env": "testing", "type": "script"}
    # 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)

C++

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, std::string const& template_name) {
    // 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, and then override the template name.
    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 {
            script {
              text: "echo Hello world! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks."
            }
          }
        }
      }
      labels { key: "env" value: "testing" }
      labels { key: "type" value: "script" }
      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");
    }
    job->mutable_allocation_policy()->add_instances()->set_instance_template(
        template_name);
    // 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";
  }

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