Create and run a basic job

This document explains the basics for Batch job creation: how to create and run a job that is based on a script or container image and use predefined and custom variables. To learn more about creating and running jobs, see Job creation and execution overview.

Before you begin

  1. If you haven't used Batch before, review Get started with Batch and enable Batch by completing the prerequisites for projects and users.
  2. To get the permissions that you need to create a job, ask your administrator to grant you the following IAM roles:

    For more information about granting roles, see Manage access to projects, folders, and organizations.

    You might also be able to get the required permissions through custom roles or other predefined roles.

  3. Each time you create a job, make sure the job has a valid network configuration.
    • If you don't have any specific networking requirements for your workload or project and you haven't modified the default network for your project, no action is required.
    • Otherwise, you need to configure networking when you create a job. Learn how to configure networking for a job before you create a basic job, so you can modify the examples below to meet your networking requirements.
    For more information about the network configuration for a job, see Batch networking overview.
  4. Each time you create a job, make sure the job has a valid VM operating system (OS) environment.
    • If you don't have any specific VM OS image or boot disk requirements for your workload or project, no action is required.
    • Otherwise, you need to prepare a valid VM OS environment option. Before creating a basic job, either allow the default configuration for the VM OS environment or learn how to customize the VM OS environment so you can modify the examples below to meet your requirements.
    For more information about the VM OS environment for a job, see VM OS environment overview.

Create a basic job

For information about all the fields you can specify for a job, see the reference documentation for the projects.locations.jobs REST resource. To summarize, a job consists of an array of one or more tasks that all run one or more runnables, which are the executable script(s) and/or container(s) for your job. To cover the basics, this section explains how to create an example job with just one runnable, either a script or a container image:

  • If you want to use Batch to write jobs that run a container image, see create a container job.
  • Otherwise, if you aren't sure if you want to use container images or if you are unfamiliar with containers, creating a script job is recommended.

The example job for both types of jobs contains a task group with an array of 4 tasks. Each task prints a message and its index to the standard output and Cloud Logging. The definition for this job specifies a parallelism of 2, which indicates that the job should run on 2 VMs to allow 2 tasks to run at a time.

Create a basic container job

You can select or create a container image to provide the code and dependencies for your job to run from any compute environment. For more information, see Working with container images and Running containers on VM instances.

You can create a basic container job using the Google Cloud console, gcloud CLI, Batch API, Go, Java, Node.js, Python, or C++.

Console

To create a basic container job using the Google Cloud console, do the following:

  1. In the Google Cloud console, go to the Job list page.

    Go to Job list

  2. Click Create. The Create batch job page opens. In the left pane, the Job details page is selected.

  3. Configure the Job details page:

    1. Optional: In the Job name field, customize the job name.

      For example, enter example-basic-job.

    2. Configure the Task details section:

      1. In the New runnable window, add at least one script or container for this job to run.

        For example, to add one container, do the following:

        1. Select Container image URL (default).

        2. In the Container image URL field, enter the URL for a container image that you want to run for each task in this job.

          For example, to use the busybox Docker container image, enter the following URL:

          gcr.io/google-containers/busybox
          
        3. Optional: To override the container image's ENTRYPOINT command, enter a command in the Entry point field.

          For example, enter the following:

          /bin/sh
          
        4. Optional: To override the container image's CMD command, do the following:

          1. Select the Override container image's CMD command checkbox. A text box appears.

          2. In the text box, enter one or more commands, separating each command with a new line.

            For example, enter the following commands:

            -c
            echo Hello world! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks.
            
          3. Click Done.

      2. In the Task count field, enter the number of tasks for this job. The value must be a whole number between 1 and the tasks per task group limit.

        For example, enter 4.

      3. In the Parallelism field, enter the number of tasks to run concurrently. The number cannot be larger than the total number of tasks and must be a whole number between 1 and the parallel tasks per job limit.

        For example, enter 2.

  4. Configure the Resource specifications page:

    1. In the left pane, click Resource specifications. The Resource specifications page opens.

    2. In the VM provisioning model section, select one of the following options for the provisioning model for this job's VMs:

      • If your job can withstand preemption and you want discounted VMs, select Spot.

      • Otherwise, select Standard.

      For example, select Standard (default).

    3. Select the location for this job:

      1. In the Region field, select a region.

        For example, select us-central1 (Iowa) (default).

      2. In the Zone field, do one of the following:

        • If you want to restrict this job to run in a specific zone only, select a zone.

        • Otherwise, select any.

        For example, select any (default).

    4. Select one of the following machine families:

      • For common workloads, click General purpose.

      • For performance-intensive workloads, click Compute optimized.

      • For memory-intensive workloads, click Memory optimized.

      For example, click General purpose (default).

    5. In the Series field, select a machine series for this job's VMs.

      For example, if you selected General purpose for the machine family, select E2 (default).

    6. In the Machine type field, select a machine type for this job's VMs.

      For example, if you selected E2 for the machine series, select e2-medium (2 vCPU, 4 GB memory) (default).

    7. Configure the amount of VM resources required for each task:

      1. In the Cores field, enter the amount of vCPUs per task.

        For example, enter 1 (default).

      2. In the Memory field, enter the amount of RAM in GB per task.

        For example, enter 0.5 (default).

  5. Optional: To review the job configuration, in the left pane, click Preview.

  6. Click Create.

The Job details page displays the job that you created.

gcloud

To create a basic container job using the gcloud CLI, do the following:

  1. Create a JSON file that specifies your job's configuration details. For example, to create a basic container job, create a JSON file with the following contents. For more information about all the fields you can specify for a job, see the reference documentation for the projects.locations.jobs REST resource.

    {
        "taskGroups": [
            {
                "taskSpec": {
                    "runnables": [
                        {
                            "container": {
                                CONTAINER
                            }
                        }
                    ],
                    "computeResource": {
                        "cpuMilli": CORES,
                        "memoryMib": MEMORY
                    },
                    "maxRetryCount": MAX_RETRY_COUNT,
                    "maxRunDuration": "MAX_RUN_DURATION"
                },
                "taskCount": TASK_COUNT,
                "parallelism": PARALLELISM
            }
        ]
    }
    

    Replace the following:

    • CONTAINER: the container that each task runs. At minimum, a container must specify an image in the imageUri subfield, but additional subfields might also be required. For more information, see the container subfields and the example container job in this section.
    • CORES: Optional. The amount of cores—specifically vCPUs, which usually represent half a physical core—to allocate for each task in milliCPU units. If the cpuMilli field is not specified, the value is set to 2000 (2 vCPUs).
    • MEMORY: Optional. The amount of memory to allocate for each task in MB. If the memoryMib field is not specified, the value is set to 2000 (2 GB).
    • MAX_RETRY_COUNT: Optional. The maximum number of retries for a task. The value must be a whole number between 0 and 10. If the maxRetryCount field is not specified, the value is set to 0, which means to not retry the task. For more information about the maxRetryCount field, see Automate task retries.
    • MAX_RUN_DURATION: Optional. The maximum time a task is allowed to run before being retried or failing, formatted as a value in seconds followed by s—for example, 3600s for 1 hour. If the maxRunDuration field is not specified, the value is set to the maximum run time for a job. For more information about the maxRunDuration field, see Limit run times for tasks and runnables using timeouts.
    • TASK_COUNT: Optional. The number of tasks for the job. The value must be a whole number between 1 and the tasks per task group limit. If the taskCount field is not specified, the value is set to 1.
    • PARALLELISM: Optional. The number of tasks the job runs concurrently. The number cannot be larger than the number of tasks and must be a whole number between 1 and the parallel tasks per job limit. If the parallelism field is not specified, the value is set to 1.
  2. Create a job by using the gcloud batch jobs submit command.

    gcloud batch jobs submit JOB_NAME \
      --location LOCATION \
      --config JSON_CONFIGURATION_FILE
    

    Replace the following:

    • JOB_NAME: the name of the job.
    • LOCATION: the location of the job.
    • JSON_CONFIGURATION_FILE: the path for a JSON file with the job's configuration details.

For example, to create a job that runs tasks using the busybox Docker container image:

  1. Create a JSON file in the current directory named hello-world-container.json with the following contents:

    {
        "taskGroups": [
            {
                "taskSpec": {
                    "runnables": [
                        {
                            "container": {
                                "imageUri": "gcr.io/google-containers/busybox",
                                "entrypoint": "/bin/sh",
                                "commands": [
                                    "-c",
                                    "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": [
                {
                    "policy": { "machineType": "e2-standard-4" }
                }
            ]
        },
        "labels": {
            "department": "finance",
            "env": "testing"
        },
        "logsPolicy": {
            "destination": "CLOUD_LOGGING"
        }
    }
    
  2. Run the following command:

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

API

To create a basic container job using the Batch API, use the jobs.create method. For more information about all the fields you can specify for a job, see the reference documentation for the projects.locations.jobs REST resource.

POST https://batch.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/jobs?job_id=JOB_NAME

{
    "taskGroups": [
        {
            "taskSpec": {
                "runnables": [
                    {
                        "container": {
                            CONTAINER
                        }
                    }
                ],
                "computeResource": {
                    "cpuMilli": CORES,
                    "memoryMib": MEMORY
                },
                "maxRetryCount": MAX_RETRY_COUNT,
                "maxRunDuration": "MAX_RUN_DURATION"
            },
            "taskCount": TASK_COUNT,
            "parallelism": PARALLELISM
        }
    ]
}

Replace the following:

  • PROJECT_ID: the project ID of your project.
  • LOCATION: the location of the job.
  • JOB_NAME: the name of the job.
  • CONTAINER: the container that each task runs. At minimum, a container must specify an image in the imageUri subfield, but additional subfields might also be required. For more information, see the container subfields and the example container job in this section.
  • CORES: Optional. The amount of cores—specifically vCPUs, which usually represent half a physical core—to allocate for each task in milliCPU units. If the cpuMilli field is not specified, the value is set to 2000 (2 vCPUs).
  • MEMORY: Optional. The amount of memory to allocate for each task in MB. If the memoryMib field is not specified, the value is set to 2000 (2 GB).
  • MAX_RETRY_COUNT: Optional. The maximum number of retries for a task. The value must be a whole number between 0 and 10. If the maxRetryCount field is not specified, the value is set to 0, which means to not retry the task. For more information about the maxRetryCount field, see Automate task retries.
  • MAX_RUN_DURATION: Optional. The maximum time a task is allowed to run before being retried or failing, formatted as a value in seconds followed by s—for example, 3600s for 1 hour. If the maxRunDuration field is not specified, the value is set to the maximum run time for a job. For more information about the maxRunDuration field, see Limit run times for tasks and runnables using timeouts.
  • TASK_COUNT: Optional. The number of tasks for the job, which must be a whole number between 1 and the tasks per task group limit. If the taskCount field is not specified, the value is set to 1.
  • PARALLELISM: Optional. The number of tasks the job runs concurrently. The number cannot be larger than the number of tasks and must be a whole number between 1 and the parallel tasks per job limit. If the parallelism field is not specified, the value is set to 1.

For example, to create a job that runs tasks using the busybox Docker container image, use the following request:

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

{
    "taskGroups": [
        {
            "taskSpec": {
                "runnables": [
                    {
                        "container": {
                            "imageUri": "gcr.io/google-containers/busybox",
                            "entrypoint": "/bin/sh",
                            "commands": [
                                "-c",
                                "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": [
            {
                "policy": { "machineType": "e2-standard-4" }
            }
        ]
    },
    "labels": {
        "department": "finance",
        "env": "testing"
    },
    "logsPolicy": {
        "destination": "CLOUD_LOGGING"
    }
}

where PROJECT_ID is the project ID of your project.

Go

Go

For more information, see the Batch Go API reference documentation.

To authenticate to Batch, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

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

Java

For more information, see the Batch Java API reference documentation.

To authenticate to Batch, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

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

Node.js

For more information, see the Batch Node.js API reference documentation.

To authenticate to Batch, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

/**
 * 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

Python

For more information, see the Batch Python API reference documentation.

To authenticate to Batch, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

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)

C++

C++

For more information, see the Batch C++ API reference documentation.

To authenticate to Batch, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

#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";
  }

Create a basic script job

You can create a basic script job using the Google Cloud console, gcloud CLI, Batch API, Go, Java, Node.js, Python, or C++.

Console

To create a basic script job using the Google Cloud console, do the following:

  1. In the Google Cloud console, go to the Job list page.

    Go to Job list

  2. Click Create. The Create batch job page opens. In the left pane, the Job details page is selected.

  3. Configure the Job details page:

    1. Optional: In the Job name field, customize the job name.

      For example, enter example-basic-job.

    2. Configure the Task details section:

      1. In the New runnable window, add at least one script or container for this job to run.

        For example, to add one script, do the following:

        1. Select Script. A text box appears.

        2. In the text box, enter a script that you want to run for each task in this job.

          For example, enter the following script:

          echo Hello world! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks.
          
        3. Click Done.

      2. In the Task count field, enter the number of tasks for this job. The value must be a whole number between 1 and the tasks per task group limit.

        For example, enter 4.

      3. In the Parallelism field, enter the number of tasks to run concurrently. The number cannot be larger than the total number of tasks and must be a whole number between 1 and the parallel tasks per job limit.

        For example, enter 2.

  4. Configure the Resource specifications page:

    1. In the left pane, click Resource specifications. The Resource specifications page opens.

    2. In the VM provisioning model section, select one of the following options for the provisioning model for this job's VMs:

      • If your job can withstand preemption and you want discounted VMs, select Spot.

      • Otherwise, select Standard.

      For example, select Standard (default).

    3. Select the location for this job:

      1. In the Region field, select a region.

        For example, select us-central1 (Iowa) (default).

      2. In the Zone field, do one of the following:

        • If you want to restrict this job to run in a specific zone only, select a zone.

        • Otherwise, select any.

        For example, select any (default).

    4. Select one of the following machine families:

      • For common workloads, click General purpose.

      • For performance-intensive workloads, click Compute optimized.

      • For memory-intensive workloads, click Memory optimized.

      For example, click General purpose (default).

    5. In the Series field, select a machine series for this job's VMs.

      For example, if you selected General purpose for the machine family, select E2 (default).

    6. In the Machine type field, select a machine type for this job's VMs.

      For example, if you selected E2 for the machine series, select e2-medium (2 vCPU, 4 GB memory) (default).

    7. Configure the amount of VM resources required for each task:

      1. In the Cores field, enter the amount of vCPUs per task.

        For example, enter 1 (default).

      2. In the Memory field, enter the amount of RAM in GB per task.

        For example, enter 0.5 (default).

  5. Optional: To review the job configuration, in the left pane, click Preview.

  6. Click Create.

The Job details page displays the job that you created.

gcloud

To create a basic script job using the gcloud CLI, do the following:

  1. Create a JSON file that specifies your job's configuration details. For example, to create a basic script job, create a JSON file with the following contents. For more information about all the fields you can specify for a job, see the reference documentation for the projects.locations.jobs REST resource.

    {
        "taskGroups": [
            {
                "taskSpec": {
                    "runnables": [
                        {
                            "script": {
                                SCRIPT
                            }
                        }
                    ],
                    "computeResource": {
                        "cpuMilli": CORES,
                        "memoryMib": MEMORY
                    },
                    "maxRetryCount": MAX_RETRY_COUNT,
                    "maxRunDuration": "MAX_RUN_DURATION"
                },
                "taskCount": TASK_COUNT,
                "parallelism": PARALLELISM
            }
        ]
    }
    

    Replace the following:

    • SCRIPT: the script that each task runs. A script must be defined either as text using the text subfield or as the path to an accessible file using the file subfield. For more information, see the script subfields and the example script job in this section.
    • CORES: Optional. The amount of cores—specifically vCPUs, which usually represent half a physical core—to allocate for each task in milliCPU units. If the cpuMilli field is not specified, the value is set to 2000 (2 vCPUs).
    • MEMORY: Optional. The amount of memory to allocate for each task in MB. If the memoryMib field is not specified, the value is set to 2000 (2 GB).
    • MAX_RETRY_COUNT: Optional. The maximum number of retries for a task. The value must be a whole number between 0 and 10. If the maxRetryCount field is not specified, the value is set to 0, which means to not retry the task. For more information about the maxRetryCount field, see Automate task retries.
    • MAX_RUN_DURATION: Optional. The maximum time a task is allowed to run before being retried or failing, formatted as a value in seconds followed by s—for example, 3600s for 1 hour. If the maxRunDuration field is not specified, the value is set to the maximum run time for a job. For more information about the maxRunDuration field, see Limit run times for tasks and runnables using timeouts.
    • TASK_COUNT: Optional. The number of tasks for the job. The value must be a whole number between 1 and the tasks per task group limit. If the taskCount field is not specified, the value is set to 1.
    • PARALLELISM: Optional. The number of tasks the job runs concurrently. The number cannot be larger than the number of tasks and must be a whole number between 1 and the parallel tasks per job limit. If the parallelism field is not specified, the value is set to 1.
  2. Create a job by using the gcloud batch jobs submit command.

    gcloud batch jobs submit JOB_NAME \
      --location LOCATION \
      --config JSON_CONFIGURATION_FILE
    

    Replace the following:

    • JOB_NAME: the name of the job.
    • LOCATION: the location of the job.
    • JSON_CONFIGURATION_FILE: the path for a JSON file with the job's configuration details.

For example, to create a job that runs tasks using a script:

  1. Create a JSON file in the current directory named hello-world-script.json with the following contents:

    {
        "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": [
                {
                    "policy": { "machineType": "e2-standard-4" }
                }
            ]
        },
        "labels": {
            "department": "finance",
            "env": "testing"
        },
        "logsPolicy": {
            "destination": "CLOUD_LOGGING"
        }
    }
    
  2. Run the following command:

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

API

To create a basic script job using the Batch API, use the jobs.create method. For more information about all the fields you can specify for a job, see the reference documentation for the projects.locations.jobs REST resource.

POST https://batch.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/jobs?job_id=JOB_NAME

{
    "taskGroups": [
        {
            "taskSpec": {
                "runnables": [
                    {
                        "script": {
                            SCRIPT
                        }
                    }
                ],
                "computeResource": {
                    "cpuMilli": CORES,
                    "memoryMib": MEMORY
                },
                "maxRetryCount": MAX_RETRY_COUNT,
                "maxRunDuration": "MAX_RUN_DURATION"
            },
            "taskCount": TASK_COUNT,
            "parallelism": PARALLELISM
        }
    ]
}

Replace the following:

  • PROJECT_ID: the project ID of your project.
  • LOCATION: the location of the job.
  • JOB_NAME: the name of the job.
  • SCRIPT: the script that each task runs. A script must be defined either as text using the text subfield or as the path to an accessible file using the file subfield. For more information, see the script subfields and the example script job in this section.
  • CORES: Optional. The amount of cores—specifically vCPUs, which usually represent half a physical core—to allocate for each task in milliCPU units. If the cpuMilli field is not specified, the value is set to 2000 (2 vCPUs).
  • MEMORY: Optional. The amount of memory to allocate for each task in MB. If the memoryMib field is not specified, the value is set to 2000 (2 GB).
  • MAX_RETRY_COUNT: Optional. The maximum number of retries for a task. The value must be a whole number between 0 and 10. If the maxRetryCount field is not specified, the value is set to 0, which means to not retry the task. For more information about the maxRetryCount field, see Automate task retries.
  • MAX_RUN_DURATION: Optional. The maximum time a task is allowed to run before being retried or failing, formatted as a value in seconds followed by s—for example, 3600s for 1 hour. If the maxRunDuration field is not specified, the value is set to the maximum run time for a job. For more information about the maxRunDuration field, see Limit run times for tasks and runnables using timeouts.
  • TASK_COUNT: Optional. The number of tasks for the job. The value must be a whole number between 1 and the tasks per task group limit. If the taskCount field is not specified, the value is set to 1.
  • PARALLELISM: Optional. The number of tasks the job runs concurrently. The number cannot be larger than the number of tasks and must be a whole number between 1 and the parallel tasks per job limit. If the parallelism field is not specified, the value is set to 1.

For example, to create a job that runs tasks using a script, use the following request:

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": [
            {
                "policy": { "machineType": "e2-standard-4" }
            }
        ]
    },
    "labels": {
        "department": "finance",
        "env": "testing"
    },
    "logsPolicy": {
        "destination": "CLOUD_LOGGING"
    }
}

where PROJECT_ID is the project ID of your project.

Go

Go

For more information, see the Batch Go API reference documentation.

To authenticate to Batch, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

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 createScriptJob(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()

	// 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.",
	}
	// 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.
	// command := &batchpb.Runnable_Script_Path{
	// 	Path: "/tmp/test.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_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 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": "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

For more information, see the Batch Java API reference documentation.

To authenticate to Batch, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

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.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 CreateWithScriptNoMounting {

  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";

    createScriptJob(projectId, region, jobName);
  }

  // This method shows how to create a sample Batch Job that will run
  // a simple command on Cloud Compute instances.
  public static void createScriptJob(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()
              .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 "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", "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

For more information, see the Batch Node.js API reference documentation.

To authenticate to Batch, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

/**
 * 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.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 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: '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

For more information, see the Batch Python API reference documentation.

To authenticate to Batch, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

from google.cloud import batch_v1


def create_script_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 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.
    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 "e2-standard-4" machine type.
    # Read more about machine types here: https://cloud.google.com/compute/docs/machine-types
    allocation_policy = batch_v1.AllocationPolicy()
    policy = batch_v1.AllocationPolicy.InstancePolicy()
    policy.machine_type = "e2-standard-4"
    instances = batch_v1.AllocationPolicy.InstancePolicyOrTemplate()
    instances.policy = policy
    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++

For more information, see the Batch C++ API reference documentation.

To authenticate to Batch, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

#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 {
            script {
              text: "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: "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");
    }
    // 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";
  }

Use environment variables

Use environment variables when you write a container image or script that you want a job to run. You can use any of the environment variables that are predefined for all Batch jobs and any custom environment variables that you define while creating the job.

Use predefined environment variables

By default, the runnables in your job can use the following predefined environment variables:

  • BATCH_TASK_COUNT: the total number of tasks in this task group.
  • BATCH_TASK_INDEX: the index number of this task in the task group. The index of the first task is 0 and is incremented for each additional task.
  • BATCH_HOSTS_FILE: the path to a file listing all the running VM instances in this task group. To use this environment variable, the requireHostsFile field must be set to true.
  • BATCH_TASK_RETRY_ATTEMPT: the number of times that this task has already been attempted. The value is 0 during the first attempt of a task and is incremented for each following retry. The total number of retries allowed for a task is determined by the value of the maxRetryCount field, which is 0 if undefined. For more information about retries, see Automate task retries.

For an example of how to use predefined environment variables, see the previous example runnables in Create a basic job in this document.

Define and use custom environment variables

Optionally, you can define one or more custom environment variables in a job.

You define each variable in a specific environment based on the desired scope of its data:

In the selected environment, you define the name and value(s) of each variable by using one of the following environment subfields:

You can define and use custom environment variables for your job using the gcloud CLI or Batch API. The following examples explain how to create two jobs that define and use standard variables. The first example job has a variable for a specific runnable. The second example job has an array variable, which has a different value for each task.

gcloud

If you want to define a job that passes an environment variable to a runnable that each task runs, see the example for how to Define and use an environment variable for a runnable. Otherwise, if you want to define a job that passes a list of environment variables to different tasks based on the task index, see the example for how to Define and use an environment variable for each task.

Define and use an environment variable for a runnable

To create a job that passes environment variables to a runnable using the gcloud CLI, use the gcloud batch jobs submit command and specify the environment variables in the job's configuration file.

For example, to create a script job that defines an environment variable and passes it to the scripts of 3 tasks, make the following request:

  1. Create a JSON file in the current directory named hello-world-environment-variables.json with the following contents:

    {
        "taskGroups": [
            {
                "taskSpec": {
                    "runnables": [
                        {
                            "script": {
                                "text": "echo Hello ${VARIABLE_NAME}! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks."
                            },
                            "environment": {
                                "variables": {
                                    "VARIABLE_NAME": "VARIABLE_VALUE"
                                }
                            }
                        }
                    ],
                    "computeResource": {
                        "cpuMilli": 2000,
                        "memoryMib": 16
                    }
                },
                "taskCount": 3,
                "parallelism": 1
            }
        ],
        "allocationPolicy": {
            "instances": [
                {
                    "policy": {
                        "machineType": "e2-standard-4"
                    }
                }
            ]
        }
    }
    

    Replace the following:

    • VARIABLE_NAME: the name of the environment variable passed to each task. By convention, environment variable names are capitalized.
    • VARIABLE_VALUE: Optional. The value of the environment variable passed to each task.
  2. Run the following command:

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

Define and use an environment variable for each task

To create a job that passes environment variables to a task based on task index using the gcloud CLI, use the gcloud batch jobs submit command and specify the taskEnvironments array field in the job's configuration file.

For example, to create a job that includes an array of 3 environment variables with matching names and different values, and passes the environment variables to the scripts of the tasks which indices match the environment variables' indices in the array:

  1. Create a JSON file in the current directory named hello-world-task-environment-variables.json with the following contents:

    {
        "taskGroups": [
            {
                "taskSpec": {
                    "runnables": [
                        {
                            "script": {
                                "text": "echo Hello ${TASK_VARIABLE_NAME}! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks."
                            },
                        }
                    ],
                    "computeResource": {
                        "cpuMilli": 2000,
                        "memoryMib": 16
                    }
                },
                "taskCount": 3,
                "taskEnvironments": [
                    {
                        "variables": {
                            "TASK_VARIABLE_NAME": "TASK_VARIABLE_VALUE_0"
                        }
                    },
                    {
                        "variables": {
                            "TASK_VARIABLE_NAME": "TASK_VARIABLE_VALUE_1"
                        }
                    },
                    {
                        "variables": {
                            "TASK_VARIABLE_NAME": "TASK_VARIABLE_VALUE_2"
                        }
                    }
                ]
            }
        ],
        "allocationPolicy": {
            "instances": [
                {
                    "policy": {
                        "machineType": "e2-standard-4"
                    }
                }
            ]
        }
    }
    

    Replace the following:

    • TASK_VARIABLE_NAME: the name of the task environment variables passed to the tasks with matching indices. By convention, environment variable names are capitalized.
    • TASK_VARIABLE_VALUE_0: the value of the environment variable passed to the first task, for which BATCH_TASK_INDEX is equal to 0.
    • TASK_VARIABLE_VALUE_1: the value of the environment variable passed to the second task, for which BATCH_TASK_INDEX is equal to 1.
    • TASK_VARIABLE_VALUE_2: the value of the environment variable passed to the third task, for which BATCH_TASK_INDEX is equal to 2.
  2. Run the following command:

    gcloud batch jobs submit example-task-environment-variables-job \
      --location us-central1 \
      --config hello-world-task-environment-variables.json
    

API

If you want to define a job that passes an environment variable to a runnable that each task runs, see the example for how to Define and use an environment variable for a runnable. Otherwise, if you want to define a job that passes a list of environment variables to different tasks based on the task index, see the example for how to Define and use an environment variable for each task.

Define and use an environment variable for a runnable

To create a job that passes environment variables to a runnable using Batch API, use the gcloud batch jobs submit command and specify the environment variables in the environment field.

For example, to create a job that includes an environment variable and passes it to the scripts of 3 tasks, make the following request:

POST https://batch.googleapis.com/v1/projects/<var>PROJECT_ID</var>/locations/us-central1/jobs?job_id=example-environment-variables-job

{
    "taskGroups": [
        {
            "taskSpec": {
                "runnables": [
                    {
                        "script": {
                            "text": "echo Hello ${VARIABLE_NAME}! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks."
                        },
                        "environment": {
                            "variables": {
                                "VARIABLE_NAME": "VARIABLE_VALUE"
                            }
                        }
                    }
                ],
                "computeResource": {
                    "cpuMilli": 2000,
                    "memoryMib": 16
                }
            },
            "taskCount": 3,
            "parallelism": 1
        }

    ],
    "allocationPolicy": {
        "instances": [
            {
                "policy": {
                    "machineType": "e2-standard-4"
                }
            }
        ]
    }
}

Replace the following:

  • PROJECT_ID: the project ID of your project.
  • VARIABLE_NAME: the name of the environment variable passed to each task. By convention, environment variable names are capitalized.
  • VARIABLE_VALUE: the value of the environment variable passed to each task.

Define and use an environment variable for each task

To create a job that passes environment variables to a task based on task index using Batch API, use the jobs.create method and specify the environment variables in the taskEnvironments array field.

For example, to create a job that includes an array of 3 environment variables with matching names and different values, and passes the environment variables to the scripts of 3 tasks based on their indices, make the following request:

POST https://batch.googleapis.com/v1/projects/<var>PROJECT_ID</var>/locations/us-central1/jobs?job_id=example-task-environment-variables-job

{
    "taskGroups": [
        {
            "taskSpec": {
                "runnables": [
                    {
                        "script": {
                            "text": "echo Hello ${TASK_VARIABLE_NAME}! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks."
                        },
                    }
                ],
                "computeResource": {
                    "cpuMilli": 2000,
                    "memoryMib": 16
                }
            },
            "taskCount": 3,
            "taskEnvironments": [
                {
                    "variables": {
                        "TASK_VARIABLE_NAME": "TASK_VARIABLE_VALUE_0"
                    }
                },
                {
                    "variables": {
                        "TASK_VARIABLE_NAME": "TASK_VARIABLE_VALUE_1"
                    }
                },
                {
                    "variables": {
                        "TASK_VARIABLE_NAME": "TASK_VARIABLE_VALUE_2"
                    }
                }
            ]
        }
    ],
    "allocationPolicy": {
        "instances": [
            {
                "policy": { "machineType": "e2-standard-4" }
            }
        ]
    }
}

Replace the following:

  • PROJECT_ID: the project ID of your project.
  • TASK_VARIABLE_NAME: the name of the environment variables passed to the tasks with matching indices. By convention, environment variable names are capitalized.
  • TASK_VARIABLE_VALUE_0: the value of the environment variable passed to the first task, for which BATCH_TASK_INDEX is equal to 0.
  • TASK_VARIABLE_VALUE_1: the value of the environment variable passed to the second task, for which BATCH_TASK_INDEX is equal to 1.
  • TASK_VARIABLE_VALUE_2: the value of the environment variable passed to the third task, for which BATCH_TASK_INDEX is equal to 2.

What's next