batch: AWS Batch

Description Usage Arguments Value Service syntax Operations Examples

View source: R/batch_service.R

Description

Using AWS Batch, you can run batch computing workloads on the AWS Cloud. Batch computing is a common means for developers, scientists, and engineers to access large amounts of compute resources. AWS Batch utilizes the advantages of this computing workload to remove the undifferentiated heavy lifting of configuring and managing required infrastructure, while also adopting a familiar batch computing software approach. Given these advantages, AWS Batch can help you to efficiently provision resources in response to jobs submitted, thus effectively helping to eliminate capacity constraints, reduce compute costs, and deliver your results more quickly.

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

Usage

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batch(config = list())

Arguments

config

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

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

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svc <- batch(
  config = list(
    credentials = list(
      creds = list(
        access_key_id = "string",
        secret_access_key = "string",
        session_token = "string"
      ),
      profile = "string"
    ),
    endpoint = "string",
    region = "string"
  )
)

Operations

cancel_job Cancels a job in an AWS Batch job queue
create_compute_environment Creates an AWS Batch compute environment
create_job_queue Creates an AWS Batch job queue
delete_compute_environment Deletes an AWS Batch compute environment
delete_job_queue Deletes the specified job queue
deregister_job_definition Deregisters an AWS 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 AWS Batch jobs
list_jobs Returns a list of AWS Batch jobs
list_tags_for_resource Lists the tags for an AWS Batch resource
register_job_definition Registers an AWS Batch job definition
submit_job Submits an AWS 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 AWS Batch resource
update_compute_environment Updates an AWS Batch compute environment
update_job_queue Updates a job queue

Examples

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## 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)

paws.compute documentation built on Aug. 23, 2021, 9:09 a.m.