emrcontainers | R Documentation |
Amazon EMR on EKS provides a deployment option for Amazon EMR that allows you to run open-source big data frameworks on Amazon Elastic Kubernetes Service (Amazon EKS). With this deployment option, you can focus on running analytics workloads while Amazon EMR on EKS builds, configures, and manages containers for open-source applications. For more information about Amazon EMR on EKS concepts and tasks, see What is Amazon EMR on EKS.
Amazon EMR containers is the API name for Amazon EMR on EKS. The
emr-containers
prefix is used in the following scenarios:
It is the prefix in the CLI commands for Amazon EMR on EKS. For
example, aws emr-containers start-job-run
.
It is the prefix before IAM policy actions for Amazon EMR on EKS.
For example, "Action": [ "emr-containers:StartJobRun"]
. For more
information, see Policy actions for Amazon EMR on EKS.
It is the prefix used in Amazon EMR on EKS service endpoints. For
example, emr-containers.us-east-2.amazonaws.com
. For more
information, see Amazon EMR on EKSService Endpoints.
emrcontainers(
config = list(),
credentials = list(),
endpoint = NULL,
region = NULL
)
config |
Optional configuration of credentials, endpoint, and/or region.
|
credentials |
Optional credentials shorthand for the config parameter
|
endpoint |
Optional shorthand for complete URL to use for the constructed client. |
region |
Optional shorthand for AWS Region used in instantiating the client. |
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.
svc <- emrcontainers( 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" )
cancel_job_run | Cancels a job run |
create_job_template | Creates a job template |
create_managed_endpoint | Creates a managed endpoint |
create_security_configuration | Creates a security configuration |
create_virtual_cluster | Creates a virtual cluster |
delete_job_template | Deletes a job template |
delete_managed_endpoint | Deletes a managed endpoint |
delete_virtual_cluster | Deletes a virtual cluster |
describe_job_run | Displays detailed information about a job run |
describe_job_template | Displays detailed information about a specified job template |
describe_managed_endpoint | Displays detailed information about a managed endpoint |
describe_security_configuration | Displays detailed information about a specified security configuration |
describe_virtual_cluster | Displays detailed information about a specified virtual cluster |
get_managed_endpoint_session_credentials | Generate a session token to connect to a managed endpoint |
list_job_runs | Lists job runs based on a set of parameters |
list_job_templates | Lists job templates based on a set of parameters |
list_managed_endpoints | Lists managed endpoints based on a set of parameters |
list_security_configurations | Lists security configurations based on a set of parameters |
list_tags_for_resource | Lists the tags assigned to the resources |
list_virtual_clusters | Lists information about the specified virtual cluster |
start_job_run | Starts a job run |
tag_resource | Assigns tags to resources |
untag_resource | Removes tags from resources |
## Not run:
svc <- emrcontainers()
svc$cancel_job_run(
Foo = 123
)
## End(Not run)
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