GetClusterResult

data class GetClusterResult(val clusterName: String, val clusterUuid: String, val config: ClusterConfigResponse, val labels: Map<String, String>, val metrics: ClusterMetricsResponse, val project: String, val status: ClusterStatusResponse, val statusHistory: List<ClusterStatusResponse>, val virtualClusterConfig: VirtualClusterConfigResponse)

Constructors

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fun GetClusterResult(clusterName: String, clusterUuid: String, config: ClusterConfigResponse, labels: Map<String, String>, metrics: ClusterMetricsResponse, project: String, status: ClusterStatusResponse, statusHistory: List<ClusterStatusResponse>, virtualClusterConfig: VirtualClusterConfigResponse)

Types

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object Companion

Properties

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The cluster name, which must be unique within a project. The name must start with a lowercase letter, and can contain up to 51 lowercase letters, numbers, and hyphens. It cannot end with a hyphen. The name of a deleted cluster can be reused.

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A cluster UUID (Unique Universal Identifier). Dataproc generates this value when it creates the cluster.

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Optional. The cluster config for a cluster of Compute Engine Instances. Note that Dataproc may set default values, and values may change when clusters are updated.Exactly one of ClusterConfig or VirtualClusterConfig must be specified.

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Optional. The labels to associate with this cluster. Label keys must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). Label values may be empty, but, if present, must contain 1 to 63 characters, and must conform to RFC 1035 (https://www.ietf.org/rfc/rfc1035.txt). No more than 32 labels can be associated with a cluster.

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Contains cluster daemon metrics such as HDFS and YARN stats.Beta Feature: This report is available for testing purposes only. It may be changed before final release.

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The Google Cloud Platform project ID that the cluster belongs to.

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Cluster status.

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The previous cluster status.

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Optional. The virtual cluster config is used when creating a Dataproc cluster that does not directly control the underlying compute resources, for example, when creating a Dataproc-on-GKE cluster (https://cloud.google.com/dataproc/docs/guides/dpgke/dataproc-gke-overview). Dataproc may set default values, and values may change when clusters are updated. Exactly one of config or virtual_cluster_config must be specified.