Skip to content

Client

batch R Documentation

AWS Batch

Description

Batch

Using Batch, you can run batch computing workloads on the Amazon Web Services Cloud. Batch computing is a common means for developers, scientists, and engineers to access large amounts of compute resources. Batch uses the advantages of the batch computing to remove the undifferentiated heavy lifting of configuring and managing required infrastructure. At the same time, it also adopts a familiar batch computing software approach. You can use Batch to efficiently provision resources, and work toward eliminating capacity constraints, reducing your overall compute costs, and delivering results more quickly.

As a fully managed service, Batch can run batch computing workloads of any scale. Batch automatically provisions compute resources and optimizes workload distribution based on the quantity and scale of your specific workloads. With Batch, there's no need to install or manage batch computing software. This means that you can focus on analyzing results and solving your specific problems instead.

Usage

batch(config = list(), credentials = list(), endpoint = NULL, region = NULL)

Arguments

config

Optional configuration of credentials, endpoint, and/or region.

  • credentials:

    • creds:

      • access_key_id: AWS access key ID

      • secret_access_key: AWS secret access key

      • session_token: AWS temporary session token

    • profile: The name of a profile to use. If not given, then the default profile is used.

    • anonymous: Set anonymous credentials.

  • endpoint: The complete URL to use for the constructed client.

  • region: The AWS Region used in instantiating the client.

  • close_connection: Immediately close all HTTP connections.

  • timeout: The time in seconds till a timeout exception is thrown when attempting to make a connection. The default is 60 seconds.

  • s3_force_path_style: Set this to true to force the request to use path-style addressing, i.e. ⁠http://s3.amazonaws.com/BUCKET/KEY⁠.

  • sts_regional_endpoint: Set sts regional endpoint resolver to regional or legacy https://docs.aws.amazon.com/sdkref/latest/guide/feature-sts-regionalized-endpoints.html

credentials

Optional credentials shorthand for the config parameter

  • creds:

    • access_key_id: AWS access key ID

    • secret_access_key: AWS secret access key

    • session_token: AWS temporary session token

  • profile: The name of a profile to use. If not given, then the default profile is used.

  • anonymous: Set anonymous credentials.

endpoint

Optional shorthand for complete URL to use for the constructed client.

region

Optional shorthand for AWS Region used in instantiating the client.

Value

A client for the service. You can call the service's operations using syntax like svc$operation(...), where svc is the name you've assigned to the client. The available operations are listed in the Operations section.

Service syntax

svc <- batch(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string",
      anonymous = "logical"
    ),
    endpoint = "string",
    region = "string",
    close_connection = "logical",
    timeout = "numeric",
    s3_force_path_style = "logical",
    sts_regional_endpoint = "string"
  ),
  credentials = list(
    creds = list(
      access_key_id = "string",
      secret_access_key = "string",
      session_token = "string"
    ),
    profile = "string",
    anonymous = "logical"
  ),
  endpoint = "string",
  region = "string"
)

Operations

cancel_job Cancels a job in an Batch job queue
create_compute_environment Creates an Batch compute environment
create_consumable_resource Creates an Batch consumable resource
create_job_queue Creates an Batch job queue
create_quota_share Creates an Batch quota share
create_scheduling_policy Creates an Batch scheduling policy
create_service_environment Creates a service environment for running service jobs
delete_compute_environment Deletes an Batch compute environment
delete_consumable_resource Deletes the specified consumable resource
delete_job_queue Deletes the specified job queue
delete_quota_share Deletes the specified quota share
delete_scheduling_policy Deletes the specified scheduling policy
delete_service_environment Deletes a Service environment
deregister_job_definition Deregisters an Batch job definition
describe_compute_environments Describes one or more of your compute environments
describe_consumable_resource Returns a description of the specified consumable resource
describe_job_definitions Describes a list of job definitions
describe_job_queues Describes one or more of your job queues
describe_jobs Describes a list of Batch jobs
describe_quota_share Returns a description of the specified quota share
describe_scheduling_policies Describes one or more of your scheduling policies
describe_service_environments Describes one or more of your service environments
describe_service_job The details of a service job
get_job_queue_snapshot Provides a snapshot of job queue state, including ordering of RUNNABLE jobs, as well as capacity utilization for already dispatched jobs
list_consumable_resources Returns a list of Batch consumable resources
list_jobs Returns a list of Batch jobs
list_jobs_by_consumable_resource Returns a list of Batch jobs that require a specific consumable resource
list_quota_shares Returns a list of Batch quota shares associated with a job queue
list_scheduling_policies Returns a list of Batch scheduling policies
list_service_jobs Returns a list of service jobs for a specified job queue
list_tags_for_resource Lists the tags for an Batch resource
register_job_definition Registers an Batch job definition
submit_job Submits an Batch job from a job definition
submit_service_job Submits a service job to a specified job queue to run on SageMaker AI
tag_resource Associates the specified tags to a resource with the specified resourceArn
terminate_job Terminates a job in a job queue
terminate_service_job Terminates a service job in a job queue
untag_resource Deletes specified tags from an Batch resource
update_compute_environment Updates an Batch compute environment
update_consumable_resource Updates a consumable resource
update_job_queue Updates a job queue
update_quota_share Updates a quota share
update_scheduling_policy Updates a scheduling policy
update_service_environment Updates a service environment
update_service_job Updates the priority of a specified service job in an Batch job queue

Examples

## Not run: 
svc <- batch()
# This example cancels a job with the specified job ID.
svc$cancel_job(
  jobId = "1d828f65-7a4d-42e8-996d-3b900ed59dc4",
  reason = "Cancelling job."
)

## End(Not run)