@Generated(value="software.amazon.awssdk:codegen") public interface EmrContainersAsyncClient extends SdkClient
builder() method.
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 EKS Service Endpoints.
| Modifier and Type | Field and Description |
|---|---|
static String |
SERVICE_METADATA_ID
Value for looking up the service's metadata from the
ServiceMetadataProvider. |
static String |
SERVICE_NAME |
serviceNameclosestatic final String SERVICE_NAME
static final String SERVICE_METADATA_ID
ServiceMetadataProvider.static EmrContainersAsyncClient create()
EmrContainersAsyncClient with the region loaded from the
DefaultAwsRegionProviderChain and credentials loaded from the
DefaultCredentialsProvider.static EmrContainersAsyncClientBuilder builder()
EmrContainersAsyncClient.default CompletableFuture<CancelJobRunResponse> cancelJobRun(CancelJobRunRequest cancelJobRunRequest)
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.
cancelJobRunRequest - default CompletableFuture<CancelJobRunResponse> cancelJobRun(Consumer<CancelJobRunRequest.Builder> cancelJobRunRequest)
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.
This is a convenience which creates an instance of the CancelJobRunRequest.Builder avoiding the need to
create one manually via CancelJobRunRequest.builder()
cancelJobRunRequest - A Consumer that will call methods on CancelJobRunRequest.Builder to create a request.default CompletableFuture<CreateManagedEndpointResponse> createManagedEndpoint(CreateManagedEndpointRequest createManagedEndpointRequest)
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.
createManagedEndpointRequest - default CompletableFuture<CreateManagedEndpointResponse> createManagedEndpoint(Consumer<CreateManagedEndpointRequest.Builder> createManagedEndpointRequest)
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.
This is a convenience which creates an instance of the CreateManagedEndpointRequest.Builder avoiding the
need to create one manually via CreateManagedEndpointRequest.builder()
createManagedEndpointRequest - A Consumer that will call methods on CreateManagedEndpointRequest.Builder to create a
request.default CompletableFuture<CreateVirtualClusterResponse> createVirtualCluster(CreateVirtualClusterRequest createVirtualClusterRequest)
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.
createVirtualClusterRequest - default CompletableFuture<CreateVirtualClusterResponse> createVirtualCluster(Consumer<CreateVirtualClusterRequest.Builder> createVirtualClusterRequest)
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.
This is a convenience which creates an instance of the CreateVirtualClusterRequest.Builder avoiding the
need to create one manually via CreateVirtualClusterRequest.builder()
createVirtualClusterRequest - A Consumer that will call methods on CreateVirtualClusterRequest.Builder to create a
request.default CompletableFuture<DeleteManagedEndpointResponse> deleteManagedEndpoint(DeleteManagedEndpointRequest deleteManagedEndpointRequest)
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.
deleteManagedEndpointRequest - default CompletableFuture<DeleteManagedEndpointResponse> deleteManagedEndpoint(Consumer<DeleteManagedEndpointRequest.Builder> deleteManagedEndpointRequest)
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.
This is a convenience which creates an instance of the DeleteManagedEndpointRequest.Builder avoiding the
need to create one manually via DeleteManagedEndpointRequest.builder()
deleteManagedEndpointRequest - A Consumer that will call methods on DeleteManagedEndpointRequest.Builder to create a
request.default CompletableFuture<DeleteVirtualClusterResponse> deleteVirtualCluster(DeleteVirtualClusterRequest deleteVirtualClusterRequest)
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.
deleteVirtualClusterRequest - default CompletableFuture<DeleteVirtualClusterResponse> deleteVirtualCluster(Consumer<DeleteVirtualClusterRequest.Builder> deleteVirtualClusterRequest)
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.
This is a convenience which creates an instance of the DeleteVirtualClusterRequest.Builder avoiding the
need to create one manually via DeleteVirtualClusterRequest.builder()
deleteVirtualClusterRequest - A Consumer that will call methods on DeleteVirtualClusterRequest.Builder to create a
request.default CompletableFuture<DescribeJobRunResponse> describeJobRun(DescribeJobRunRequest describeJobRunRequest)
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.
describeJobRunRequest - default CompletableFuture<DescribeJobRunResponse> describeJobRun(Consumer<DescribeJobRunRequest.Builder> describeJobRunRequest)
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.
This is a convenience which creates an instance of the DescribeJobRunRequest.Builder avoiding the need to
create one manually via DescribeJobRunRequest.builder()
describeJobRunRequest - A Consumer that will call methods on DescribeJobRunRequest.Builder to create a request.default CompletableFuture<DescribeManagedEndpointResponse> describeManagedEndpoint(DescribeManagedEndpointRequest describeManagedEndpointRequest)
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.
describeManagedEndpointRequest - default CompletableFuture<DescribeManagedEndpointResponse> describeManagedEndpoint(Consumer<DescribeManagedEndpointRequest.Builder> describeManagedEndpointRequest)
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.
This is a convenience which creates an instance of the DescribeManagedEndpointRequest.Builder avoiding
the need to create one manually via DescribeManagedEndpointRequest.builder()
describeManagedEndpointRequest - A Consumer that will call methods on DescribeManagedEndpointRequest.Builder to create a
request.default CompletableFuture<DescribeVirtualClusterResponse> describeVirtualCluster(DescribeVirtualClusterRequest describeVirtualClusterRequest)
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.
describeVirtualClusterRequest - default CompletableFuture<DescribeVirtualClusterResponse> describeVirtualCluster(Consumer<DescribeVirtualClusterRequest.Builder> describeVirtualClusterRequest)
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.
This is a convenience which creates an instance of the DescribeVirtualClusterRequest.Builder avoiding the
need to create one manually via DescribeVirtualClusterRequest.builder()
describeVirtualClusterRequest - A Consumer that will call methods on DescribeVirtualClusterRequest.Builder to create a
request.default CompletableFuture<ListJobRunsResponse> listJobRuns(ListJobRunsRequest listJobRunsRequest)
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.
listJobRunsRequest - default CompletableFuture<ListJobRunsResponse> listJobRuns(Consumer<ListJobRunsRequest.Builder> listJobRunsRequest)
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.
This is a convenience which creates an instance of the ListJobRunsRequest.Builder avoiding the need to
create one manually via ListJobRunsRequest.builder()
listJobRunsRequest - A Consumer that will call methods on ListJobRunsRequest.Builder to create a request.default ListJobRunsPublisher listJobRunsPaginator(ListJobRunsRequest listJobRunsRequest)
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.
This is a variant of listJobRuns(software.amazon.awssdk.services.emrcontainers.model.ListJobRunsRequest)
operation. The return type is a custom publisher that can be subscribed to request a stream of response pages.
SDK will internally handle making service calls for you.
When the operation is called, an instance of this class is returned. At this point, no service calls are made yet
and so there is no guarantee that the request is valid. If there are errors in your request, you will see the
failures only after you start streaming the data. The subscribe method should be called as a request to start
streaming data. For more info, see
Publisher.subscribe(org.reactivestreams.Subscriber). Each call to the subscribe
method will result in a new Subscription i.e., a new contract to stream data from the
starting request.
The following are few ways to use the response class:
1) Using the subscribe helper method
software.amazon.awssdk.services.emrcontainers.paginators.ListJobRunsPublisher publisher = client.listJobRunsPaginator(request);
CompletableFuture<Void> future = publisher.subscribe(res -> { // Do something with the response });
future.get();
2) Using a custom subscriber
software.amazon.awssdk.services.emrcontainers.paginators.ListJobRunsPublisher publisher = client.listJobRunsPaginator(request);
publisher.subscribe(new Subscriber<software.amazon.awssdk.services.emrcontainers.model.ListJobRunsResponse>() {
public void onSubscribe(org.reactivestreams.Subscriber subscription) { //... };
public void onNext(software.amazon.awssdk.services.emrcontainers.model.ListJobRunsResponse response) { //... };
});
As the response is a publisher, it can work well with third party reactive streams implementations like RxJava2.
Please notice that the configuration of maxResults won't limit the number of results you get with the paginator. It only limits the number of results in each page.
Note: If you prefer to have control on service calls, use the
listJobRuns(software.amazon.awssdk.services.emrcontainers.model.ListJobRunsRequest) operation.
listJobRunsRequest - default ListJobRunsPublisher listJobRunsPaginator(Consumer<ListJobRunsRequest.Builder> listJobRunsRequest)
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.
This is a variant of listJobRuns(software.amazon.awssdk.services.emrcontainers.model.ListJobRunsRequest)
operation. The return type is a custom publisher that can be subscribed to request a stream of response pages.
SDK will internally handle making service calls for you.
When the operation is called, an instance of this class is returned. At this point, no service calls are made yet
and so there is no guarantee that the request is valid. If there are errors in your request, you will see the
failures only after you start streaming the data. The subscribe method should be called as a request to start
streaming data. For more info, see
Publisher.subscribe(org.reactivestreams.Subscriber). Each call to the subscribe
method will result in a new Subscription i.e., a new contract to stream data from the
starting request.
The following are few ways to use the response class:
1) Using the subscribe helper method
software.amazon.awssdk.services.emrcontainers.paginators.ListJobRunsPublisher publisher = client.listJobRunsPaginator(request);
CompletableFuture<Void> future = publisher.subscribe(res -> { // Do something with the response });
future.get();
2) Using a custom subscriber
software.amazon.awssdk.services.emrcontainers.paginators.ListJobRunsPublisher publisher = client.listJobRunsPaginator(request);
publisher.subscribe(new Subscriber<software.amazon.awssdk.services.emrcontainers.model.ListJobRunsResponse>() {
public void onSubscribe(org.reactivestreams.Subscriber subscription) { //... };
public void onNext(software.amazon.awssdk.services.emrcontainers.model.ListJobRunsResponse response) { //... };
});
As the response is a publisher, it can work well with third party reactive streams implementations like RxJava2.
Please notice that the configuration of maxResults won't limit the number of results you get with the paginator. It only limits the number of results in each page.
Note: If you prefer to have control on service calls, use the
listJobRuns(software.amazon.awssdk.services.emrcontainers.model.ListJobRunsRequest) operation.
This is a convenience which creates an instance of the ListJobRunsRequest.Builder avoiding the need to
create one manually via ListJobRunsRequest.builder()
listJobRunsRequest - A Consumer that will call methods on ListJobRunsRequest.Builder to create a request.default CompletableFuture<ListManagedEndpointsResponse> listManagedEndpoints(ListManagedEndpointsRequest listManagedEndpointsRequest)
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.
listManagedEndpointsRequest - default CompletableFuture<ListManagedEndpointsResponse> listManagedEndpoints(Consumer<ListManagedEndpointsRequest.Builder> listManagedEndpointsRequest)
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.
This is a convenience which creates an instance of the ListManagedEndpointsRequest.Builder avoiding the
need to create one manually via ListManagedEndpointsRequest.builder()
listManagedEndpointsRequest - A Consumer that will call methods on ListManagedEndpointsRequest.Builder to create a
request.default ListManagedEndpointsPublisher listManagedEndpointsPaginator(ListManagedEndpointsRequest listManagedEndpointsRequest)
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.
This is a variant of
listManagedEndpoints(software.amazon.awssdk.services.emrcontainers.model.ListManagedEndpointsRequest)
operation. The return type is a custom publisher that can be subscribed to request a stream of response pages.
SDK will internally handle making service calls for you.
When the operation is called, an instance of this class is returned. At this point, no service calls are made yet
and so there is no guarantee that the request is valid. If there are errors in your request, you will see the
failures only after you start streaming the data. The subscribe method should be called as a request to start
streaming data. For more info, see
Publisher.subscribe(org.reactivestreams.Subscriber). Each call to the subscribe
method will result in a new Subscription i.e., a new contract to stream data from the
starting request.
The following are few ways to use the response class:
1) Using the subscribe helper method
software.amazon.awssdk.services.emrcontainers.paginators.ListManagedEndpointsPublisher publisher = client.listManagedEndpointsPaginator(request);
CompletableFuture<Void> future = publisher.subscribe(res -> { // Do something with the response });
future.get();
2) Using a custom subscriber
software.amazon.awssdk.services.emrcontainers.paginators.ListManagedEndpointsPublisher publisher = client.listManagedEndpointsPaginator(request);
publisher.subscribe(new Subscriber<software.amazon.awssdk.services.emrcontainers.model.ListManagedEndpointsResponse>() {
public void onSubscribe(org.reactivestreams.Subscriber subscription) { //... };
public void onNext(software.amazon.awssdk.services.emrcontainers.model.ListManagedEndpointsResponse response) { //... };
});
As the response is a publisher, it can work well with third party reactive streams implementations like RxJava2.
Please notice that the configuration of maxResults won't limit the number of results you get with the paginator. It only limits the number of results in each page.
Note: If you prefer to have control on service calls, use the
listManagedEndpoints(software.amazon.awssdk.services.emrcontainers.model.ListManagedEndpointsRequest)
operation.
listManagedEndpointsRequest - default ListManagedEndpointsPublisher listManagedEndpointsPaginator(Consumer<ListManagedEndpointsRequest.Builder> listManagedEndpointsRequest)
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.
This is a variant of
listManagedEndpoints(software.amazon.awssdk.services.emrcontainers.model.ListManagedEndpointsRequest)
operation. The return type is a custom publisher that can be subscribed to request a stream of response pages.
SDK will internally handle making service calls for you.
When the operation is called, an instance of this class is returned. At this point, no service calls are made yet
and so there is no guarantee that the request is valid. If there are errors in your request, you will see the
failures only after you start streaming the data. The subscribe method should be called as a request to start
streaming data. For more info, see
Publisher.subscribe(org.reactivestreams.Subscriber). Each call to the subscribe
method will result in a new Subscription i.e., a new contract to stream data from the
starting request.
The following are few ways to use the response class:
1) Using the subscribe helper method
software.amazon.awssdk.services.emrcontainers.paginators.ListManagedEndpointsPublisher publisher = client.listManagedEndpointsPaginator(request);
CompletableFuture<Void> future = publisher.subscribe(res -> { // Do something with the response });
future.get();
2) Using a custom subscriber
software.amazon.awssdk.services.emrcontainers.paginators.ListManagedEndpointsPublisher publisher = client.listManagedEndpointsPaginator(request);
publisher.subscribe(new Subscriber<software.amazon.awssdk.services.emrcontainers.model.ListManagedEndpointsResponse>() {
public void onSubscribe(org.reactivestreams.Subscriber subscription) { //... };
public void onNext(software.amazon.awssdk.services.emrcontainers.model.ListManagedEndpointsResponse response) { //... };
});
As the response is a publisher, it can work well with third party reactive streams implementations like RxJava2.
Please notice that the configuration of maxResults won't limit the number of results you get with the paginator. It only limits the number of results in each page.
Note: If you prefer to have control on service calls, use the
listManagedEndpoints(software.amazon.awssdk.services.emrcontainers.model.ListManagedEndpointsRequest)
operation.
This is a convenience which creates an instance of the ListManagedEndpointsRequest.Builder avoiding the
need to create one manually via ListManagedEndpointsRequest.builder()
listManagedEndpointsRequest - A Consumer that will call methods on ListManagedEndpointsRequest.Builder to create a
request.default CompletableFuture<ListTagsForResourceResponse> listTagsForResource(ListTagsForResourceRequest listTagsForResourceRequest)
Lists the tags assigned to the resources.
listTagsForResourceRequest - default CompletableFuture<ListTagsForResourceResponse> listTagsForResource(Consumer<ListTagsForResourceRequest.Builder> listTagsForResourceRequest)
Lists the tags assigned to the resources.
This is a convenience which creates an instance of the ListTagsForResourceRequest.Builder avoiding the
need to create one manually via ListTagsForResourceRequest.builder()
listTagsForResourceRequest - A Consumer that will call methods on ListTagsForResourceRequest.Builder to create a
request.default CompletableFuture<ListVirtualClustersResponse> listVirtualClusters(ListVirtualClustersRequest listVirtualClustersRequest)
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.
listVirtualClustersRequest - default CompletableFuture<ListVirtualClustersResponse> listVirtualClusters(Consumer<ListVirtualClustersRequest.Builder> listVirtualClustersRequest)
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.
This is a convenience which creates an instance of the ListVirtualClustersRequest.Builder avoiding the
need to create one manually via ListVirtualClustersRequest.builder()
listVirtualClustersRequest - A Consumer that will call methods on ListVirtualClustersRequest.Builder to create a
request.default ListVirtualClustersPublisher listVirtualClustersPaginator(ListVirtualClustersRequest listVirtualClustersRequest)
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.
This is a variant of
listVirtualClusters(software.amazon.awssdk.services.emrcontainers.model.ListVirtualClustersRequest)
operation. The return type is a custom publisher that can be subscribed to request a stream of response pages.
SDK will internally handle making service calls for you.
When the operation is called, an instance of this class is returned. At this point, no service calls are made yet
and so there is no guarantee that the request is valid. If there are errors in your request, you will see the
failures only after you start streaming the data. The subscribe method should be called as a request to start
streaming data. For more info, see
Publisher.subscribe(org.reactivestreams.Subscriber). Each call to the subscribe
method will result in a new Subscription i.e., a new contract to stream data from the
starting request.
The following are few ways to use the response class:
1) Using the subscribe helper method
software.amazon.awssdk.services.emrcontainers.paginators.ListVirtualClustersPublisher publisher = client.listVirtualClustersPaginator(request);
CompletableFuture<Void> future = publisher.subscribe(res -> { // Do something with the response });
future.get();
2) Using a custom subscriber
software.amazon.awssdk.services.emrcontainers.paginators.ListVirtualClustersPublisher publisher = client.listVirtualClustersPaginator(request);
publisher.subscribe(new Subscriber<software.amazon.awssdk.services.emrcontainers.model.ListVirtualClustersResponse>() {
public void onSubscribe(org.reactivestreams.Subscriber subscription) { //... };
public void onNext(software.amazon.awssdk.services.emrcontainers.model.ListVirtualClustersResponse response) { //... };
});
As the response is a publisher, it can work well with third party reactive streams implementations like RxJava2.
Please notice that the configuration of maxResults won't limit the number of results you get with the paginator. It only limits the number of results in each page.
Note: If you prefer to have control on service calls, use the
listVirtualClusters(software.amazon.awssdk.services.emrcontainers.model.ListVirtualClustersRequest)
operation.
listVirtualClustersRequest - default ListVirtualClustersPublisher listVirtualClustersPaginator(Consumer<ListVirtualClustersRequest.Builder> listVirtualClustersRequest)
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.
This is a variant of
listVirtualClusters(software.amazon.awssdk.services.emrcontainers.model.ListVirtualClustersRequest)
operation. The return type is a custom publisher that can be subscribed to request a stream of response pages.
SDK will internally handle making service calls for you.
When the operation is called, an instance of this class is returned. At this point, no service calls are made yet
and so there is no guarantee that the request is valid. If there are errors in your request, you will see the
failures only after you start streaming the data. The subscribe method should be called as a request to start
streaming data. For more info, see
Publisher.subscribe(org.reactivestreams.Subscriber). Each call to the subscribe
method will result in a new Subscription i.e., a new contract to stream data from the
starting request.
The following are few ways to use the response class:
1) Using the subscribe helper method
software.amazon.awssdk.services.emrcontainers.paginators.ListVirtualClustersPublisher publisher = client.listVirtualClustersPaginator(request);
CompletableFuture<Void> future = publisher.subscribe(res -> { // Do something with the response });
future.get();
2) Using a custom subscriber
software.amazon.awssdk.services.emrcontainers.paginators.ListVirtualClustersPublisher publisher = client.listVirtualClustersPaginator(request);
publisher.subscribe(new Subscriber<software.amazon.awssdk.services.emrcontainers.model.ListVirtualClustersResponse>() {
public void onSubscribe(org.reactivestreams.Subscriber subscription) { //... };
public void onNext(software.amazon.awssdk.services.emrcontainers.model.ListVirtualClustersResponse response) { //... };
});
As the response is a publisher, it can work well with third party reactive streams implementations like RxJava2.
Please notice that the configuration of maxResults won't limit the number of results you get with the paginator. It only limits the number of results in each page.
Note: If you prefer to have control on service calls, use the
listVirtualClusters(software.amazon.awssdk.services.emrcontainers.model.ListVirtualClustersRequest)
operation.
This is a convenience which creates an instance of the ListVirtualClustersRequest.Builder avoiding the
need to create one manually via ListVirtualClustersRequest.builder()
listVirtualClustersRequest - A Consumer that will call methods on ListVirtualClustersRequest.Builder to create a
request.default CompletableFuture<StartJobRunResponse> startJobRun(StartJobRunRequest startJobRunRequest)
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.
startJobRunRequest - default CompletableFuture<StartJobRunResponse> startJobRun(Consumer<StartJobRunRequest.Builder> startJobRunRequest)
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.
This is a convenience which creates an instance of the StartJobRunRequest.Builder avoiding the need to
create one manually via StartJobRunRequest.builder()
startJobRunRequest - A Consumer that will call methods on StartJobRunRequest.Builder to create a request.default CompletableFuture<TagResourceResponse> tagResource(TagResourceRequest tagResourceRequest)
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.
tagResourceRequest - default CompletableFuture<TagResourceResponse> tagResource(Consumer<TagResourceRequest.Builder> tagResourceRequest)
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.
This is a convenience which creates an instance of the TagResourceRequest.Builder avoiding the need to
create one manually via TagResourceRequest.builder()
tagResourceRequest - A Consumer that will call methods on TagResourceRequest.Builder to create a request.default CompletableFuture<UntagResourceResponse> untagResource(UntagResourceRequest untagResourceRequest)
Removes tags from resources.
untagResourceRequest - default CompletableFuture<UntagResourceResponse> untagResource(Consumer<UntagResourceRequest.Builder> untagResourceRequest)
Removes tags from resources.
This is a convenience which creates an instance of the UntagResourceRequest.Builder avoiding the need to
create one manually via UntagResourceRequest.builder()
untagResourceRequest - A Consumer that will call methods on UntagResourceRequest.Builder to create a request.