batch function

AWS Batch

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.

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.

Returns

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_job_queue	Creates an Batch job queue
create_scheduling_policy	Creates an Batch scheduling policy
delete_compute_environment	Deletes an Batch compute environment
delete_job_queue	Deletes the specified job queue
delete_scheduling_policy	Deletes the specified scheduling policy
deregister_job_definition	Deregisters an Batch job definition
describe_compute_environments	Describes one or more of your compute environments
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_scheduling_policies	Describes one or more of your scheduling policies
get_job_queue_snapshot	Provides a list of the first 100 RUNNABLE jobs associated to a single job queue
list_jobs	Returns a list of Batch jobs
list_scheduling_policies	Returns a list of Batch scheduling policies
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
tag_resource	Associates the specified tags to a resource with the specified resourceArn
terminate_job	Terminates a job in a job queue
untag_resource	Deletes specified tags from an Batch resource
update_compute_environment	Updates an Batch compute environment
update_job_queue	Updates a job queue
update_scheduling_policy	Updates a scheduling policy

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)