Amazon EMR Containers¶

Description¶

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.

Usage¶

emrcontainers(
  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
- use_dual_stack: Set this to true to use the dualstack (IPv4 and IPv6) endpoint for a service, where available, falling back to the regular endpoint when it isn't. Defaults to the AWS_USE_DUALSTACK_ENDPOINT environment variable when unset.
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 <- 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",
    use_dual_stack = "logical"
  ),
  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_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_security_configuration`	Deletes a security configuration
`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
`update_virtual_cluster`	Updates a virtual cluster

Examples¶

svc <- emrcontainers()
svc$cancel_job_run(
  Foo = 123
)