Class: Aws::EMRContainers::Client
- Inherits:
-
Seahorse::Client::Base
- Object
- Seahorse::Client::Base
- Aws::EMRContainers::Client
- Includes:
- ClientStubs
- Defined in:
- gems/aws-sdk-emrcontainers/lib/aws-sdk-emrcontainers/client.rb
Overview
An API client for EMRContainers. To construct a client, you need to configure a :region
and :credentials
.
client = Aws::EMRContainers::Client.new(
region: region_name,
credentials: credentials,
# ...
)
For details on configuring region and credentials see the developer guide.
See #initialize for a full list of supported configuration options.
Instance Attribute Summary
Attributes inherited from Seahorse::Client::Base
API Operations collapse
-
#cancel_job_run(params = {}) ⇒ Types::CancelJobRunResponse
Cancels a job run.
-
#create_managed_endpoint(params = {}) ⇒ Types::CreateManagedEndpointResponse
Creates a managed endpoint.
-
#create_virtual_cluster(params = {}) ⇒ Types::CreateVirtualClusterResponse
Creates a virtual cluster.
-
#delete_managed_endpoint(params = {}) ⇒ Types::DeleteManagedEndpointResponse
Deletes a managed endpoint.
-
#delete_virtual_cluster(params = {}) ⇒ Types::DeleteVirtualClusterResponse
Deletes a virtual cluster.
-
#describe_job_run(params = {}) ⇒ Types::DescribeJobRunResponse
Displays detailed information about a job run.
-
#describe_managed_endpoint(params = {}) ⇒ Types::DescribeManagedEndpointResponse
Displays detailed information about a managed endpoint.
-
#describe_virtual_cluster(params = {}) ⇒ Types::DescribeVirtualClusterResponse
Displays detailed information about a specified virtual cluster.
-
#list_job_runs(params = {}) ⇒ Types::ListJobRunsResponse
Lists job runs based on a set of parameters.
-
#list_managed_endpoints(params = {}) ⇒ Types::ListManagedEndpointsResponse
Lists managed endpoints based on a set of parameters.
-
#list_tags_for_resource(params = {}) ⇒ Types::ListTagsForResourceResponse
Lists the tags assigned to the resources.
-
#list_virtual_clusters(params = {}) ⇒ Types::ListVirtualClustersResponse
Lists information about the specified virtual cluster.
-
#start_job_run(params = {}) ⇒ Types::StartJobRunResponse
Starts a job run.
-
#tag_resource(params = {}) ⇒ Struct
Assigns tags to resources.
-
#untag_resource(params = {}) ⇒ Struct
Removes tags from resources.
Instance Method Summary collapse
-
#initialize(options) ⇒ Client
constructor
A new instance of Client.
Methods included from ClientStubs
#api_requests, #stub_data, #stub_responses
Methods inherited from Seahorse::Client::Base
add_plugin, api, clear_plugins, define, new, #operation_names, plugins, remove_plugin, set_api, set_plugins
Methods included from Seahorse::Client::HandlerBuilder
#handle, #handle_request, #handle_response
Constructor Details
#initialize(options) ⇒ Client
Returns a new instance of Client.
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# File 'gems/aws-sdk-emrcontainers/lib/aws-sdk-emrcontainers/client.rb', line 348 def initialize(*args) super end |
Instance Method Details
#cancel_job_run(params = {}) ⇒ Types::CancelJobRunResponse
Cancels a job run. A job run is a unit of work, such as a Spark jar, PySpark script, or SparkSQL query, that you submit to Amazon EMR on EKS.
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# File 'gems/aws-sdk-emrcontainers/lib/aws-sdk-emrcontainers/client.rb', line 385 def cancel_job_run(params = {}, = {}) req = build_request(:cancel_job_run, params) req.send_request() end |
#create_managed_endpoint(params = {}) ⇒ Types::CreateManagedEndpointResponse
Creates a managed endpoint. A managed endpoint is a gateway that connects EMR Studio to Amazon EMR on EKS so that EMR Studio can communicate with your virtual cluster.
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# File 'gems/aws-sdk-emrcontainers/lib/aws-sdk-emrcontainers/client.rb', line 482 def create_managed_endpoint(params = {}, = {}) req = build_request(:create_managed_endpoint, params) req.send_request() end |
#create_virtual_cluster(params = {}) ⇒ Types::CreateVirtualClusterResponse
Creates a virtual cluster. Virtual cluster is a managed entity on Amazon EMR on EKS. You can create, describe, list and delete virtual clusters. They do not consume any additional resource in your system. A single virtual cluster maps to a single Kubernetes namespace. Given this relationship, you can model virtual clusters the same way you model Kubernetes namespaces to meet your requirements.
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# File 'gems/aws-sdk-emrcontainers/lib/aws-sdk-emrcontainers/client.rb', line 544 def create_virtual_cluster(params = {}, = {}) req = build_request(:create_virtual_cluster, params) req.send_request() end |
#delete_managed_endpoint(params = {}) ⇒ Types::DeleteManagedEndpointResponse
Deletes a managed endpoint. A managed endpoint is a gateway that connects EMR Studio to Amazon EMR on EKS so that EMR Studio can communicate with your virtual cluster.
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# File 'gems/aws-sdk-emrcontainers/lib/aws-sdk-emrcontainers/client.rb', line 580 def delete_managed_endpoint(params = {}, = {}) req = build_request(:delete_managed_endpoint, params) req.send_request() end |
#delete_virtual_cluster(params = {}) ⇒ Types::DeleteVirtualClusterResponse
Deletes a virtual cluster. Virtual cluster is a managed entity on Amazon EMR on EKS. You can create, describe, list and delete virtual clusters. They do not consume any additional resource in your system. A single virtual cluster maps to a single Kubernetes namespace. Given this relationship, you can model virtual clusters the same way you model Kubernetes namespaces to meet your requirements.
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# File 'gems/aws-sdk-emrcontainers/lib/aws-sdk-emrcontainers/client.rb', line 613 def delete_virtual_cluster(params = {}, = {}) req = build_request(:delete_virtual_cluster, params) req.send_request() end |
#describe_job_run(params = {}) ⇒ Types::DescribeJobRunResponse
Displays detailed information about a job run. A job run is a unit of work, such as a Spark jar, PySpark script, or SparkSQL query, that you submit to Amazon EMR on EKS.
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# File 'gems/aws-sdk-emrcontainers/lib/aws-sdk-emrcontainers/client.rb', line 674 def describe_job_run(params = {}, = {}) req = build_request(:describe_job_run, params) req.send_request() end |
#describe_managed_endpoint(params = {}) ⇒ Types::DescribeManagedEndpointResponse
Displays detailed information about a managed endpoint. A managed endpoint is a gateway that connects EMR Studio to Amazon EMR on EKS so that EMR Studio can communicate with your virtual cluster.
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# File 'gems/aws-sdk-emrcontainers/lib/aws-sdk-emrcontainers/client.rb', line 736 def describe_managed_endpoint(params = {}, = {}) req = build_request(:describe_managed_endpoint, params) req.send_request() end |
#describe_virtual_cluster(params = {}) ⇒ Types::DescribeVirtualClusterResponse
Displays detailed information about a specified virtual cluster. Virtual cluster is a managed entity on Amazon EMR on EKS. You can create, describe, list and delete virtual clusters. They do not consume any additional resource in your system. A single virtual cluster maps to a single Kubernetes namespace. Given this relationship, you can model virtual clusters the same way you model Kubernetes namespaces to meet your requirements.
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# File 'gems/aws-sdk-emrcontainers/lib/aws-sdk-emrcontainers/client.rb', line 779 def describe_virtual_cluster(params = {}, = {}) req = build_request(:describe_virtual_cluster, params) req.send_request() end |
#list_job_runs(params = {}) ⇒ Types::ListJobRunsResponse
Lists job runs based on a set of parameters. A job run is a unit of work, such as a Spark jar, PySpark script, or SparkSQL query, that you submit to Amazon EMR on EKS.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-emrcontainers/lib/aws-sdk-emrcontainers/client.rb', line 865 def list_job_runs(params = {}, = {}) req = build_request(:list_job_runs, params) req.send_request() end |
#list_managed_endpoints(params = {}) ⇒ Types::ListManagedEndpointsResponse
Lists managed endpoints based on a set of parameters. A managed endpoint is a gateway that connects EMR Studio to Amazon EMR on EKS so that EMR Studio can communicate with your virtual cluster.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-emrcontainers/lib/aws-sdk-emrcontainers/client.rb', line 952 def list_managed_endpoints(params = {}, = {}) req = build_request(:list_managed_endpoints, params) req.send_request() end |
#list_tags_for_resource(params = {}) ⇒ Types::ListTagsForResourceResponse
Lists the tags assigned to the resources.
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# File 'gems/aws-sdk-emrcontainers/lib/aws-sdk-emrcontainers/client.rb', line 981 def (params = {}, = {}) req = build_request(:list_tags_for_resource, params) req.send_request() end |
#list_virtual_clusters(params = {}) ⇒ Types::ListVirtualClustersResponse
Lists information about the specified virtual cluster. Virtual cluster is a managed entity on Amazon EMR on EKS. You can create, describe, list and delete virtual clusters. They do not consume any additional resource in your system. A single virtual cluster maps to a single Kubernetes namespace. Given this relationship, you can model virtual clusters the same way you model Kubernetes namespaces to meet your requirements.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-emrcontainers/lib/aws-sdk-emrcontainers/client.rb', line 1054 def list_virtual_clusters(params = {}, = {}) req = build_request(:list_virtual_clusters, params) req.send_request() end |
#start_job_run(params = {}) ⇒ Types::StartJobRunResponse
Starts a job run. A job run is a unit of work, such as a Spark jar, PySpark script, or SparkSQL query, that you submit to Amazon EMR on EKS.
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# File 'gems/aws-sdk-emrcontainers/lib/aws-sdk-emrcontainers/client.rb', line 1151 def start_job_run(params = {}, = {}) req = build_request(:start_job_run, params) req.send_request() end |
#tag_resource(params = {}) ⇒ Struct
Assigns tags to resources. A tag is a label that you assign to an AWS resource. Each tag consists of a key and an optional value, both of which you define. Tags enable you to categorize your AWS resources by attributes such as purpose, owner, or environment. When you have many resources of the same type, you can quickly identify a specific resource based on the tags you've assigned to it. For example, you can define a set of tags for your Amazon EMR on EKS clusters to help you track each cluster's owner and stack level. We recommend that you devise a consistent set of tag keys for each resource type. You can then search and filter the resources based on the tags that you add.
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# File 'gems/aws-sdk-emrcontainers/lib/aws-sdk-emrcontainers/client.rb', line 1188 def tag_resource(params = {}, = {}) req = build_request(:tag_resource, params) req.send_request() end |
#untag_resource(params = {}) ⇒ Struct
Removes tags from resources.
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# File 'gems/aws-sdk-emrcontainers/lib/aws-sdk-emrcontainers/client.rb', line 1214 def untag_resource(params = {}, = {}) req = build_request(:untag_resource, params) req.send_request() end |