@Generated(value="com.amazonaws:aws-java-sdk-code-generator") public class AbstractAmazonEMRContainers extends Object implements AmazonEMRContainers
AmazonEMRContainers
. Convenient method forms pass through to the corresponding
overload that takes a request object, which throws an UnsupportedOperationException
.ENDPOINT_PREFIX
public CancelJobRunResult cancelJobRun(CancelJobRunRequest request)
AmazonEMRContainers
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.
cancelJobRun
in interface AmazonEMRContainers
public CreateManagedEndpointResult createManagedEndpoint(CreateManagedEndpointRequest request)
AmazonEMRContainers
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.
createManagedEndpoint
in interface AmazonEMRContainers
public CreateVirtualClusterResult createVirtualCluster(CreateVirtualClusterRequest request)
AmazonEMRContainers
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.
createVirtualCluster
in interface AmazonEMRContainers
public DeleteManagedEndpointResult deleteManagedEndpoint(DeleteManagedEndpointRequest request)
AmazonEMRContainers
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.
deleteManagedEndpoint
in interface AmazonEMRContainers
public DeleteVirtualClusterResult deleteVirtualCluster(DeleteVirtualClusterRequest request)
AmazonEMRContainers
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.
deleteVirtualCluster
in interface AmazonEMRContainers
public DescribeJobRunResult describeJobRun(DescribeJobRunRequest request)
AmazonEMRContainers
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.
describeJobRun
in interface AmazonEMRContainers
public DescribeManagedEndpointResult describeManagedEndpoint(DescribeManagedEndpointRequest request)
AmazonEMRContainers
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.
describeManagedEndpoint
in interface AmazonEMRContainers
public DescribeVirtualClusterResult describeVirtualCluster(DescribeVirtualClusterRequest request)
AmazonEMRContainers
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.
describeVirtualCluster
in interface AmazonEMRContainers
public ListJobRunsResult listJobRuns(ListJobRunsRequest request)
AmazonEMRContainers
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.
listJobRuns
in interface AmazonEMRContainers
public ListManagedEndpointsResult listManagedEndpoints(ListManagedEndpointsRequest request)
AmazonEMRContainers
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.
listManagedEndpoints
in interface AmazonEMRContainers
public ListTagsForResourceResult listTagsForResource(ListTagsForResourceRequest request)
AmazonEMRContainers
Lists the tags assigned to the resources.
listTagsForResource
in interface AmazonEMRContainers
public ListVirtualClustersResult listVirtualClusters(ListVirtualClustersRequest request)
AmazonEMRContainers
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.
listVirtualClusters
in interface AmazonEMRContainers
public StartJobRunResult startJobRun(StartJobRunRequest request)
AmazonEMRContainers
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.
startJobRun
in interface AmazonEMRContainers
public TagResourceResult tagResource(TagResourceRequest request)
AmazonEMRContainers
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.
tagResource
in interface AmazonEMRContainers
public UntagResourceResult untagResource(UntagResourceRequest request)
AmazonEMRContainers
Removes tags from resources.
untagResource
in interface AmazonEMRContainers
public void shutdown()
AmazonEMRContainers
shutdown
in interface AmazonEMRContainers
public ResponseMetadata getCachedResponseMetadata(AmazonWebServiceRequest request)
AmazonEMRContainers
Response metadata is only cached for a limited period of time, so if you need to access this extra diagnostic information for an executed request, you should use this method to retrieve it as soon as possible after executing a request.
getCachedResponseMetadata
in interface AmazonEMRContainers
request
- The originally executed request.