Cloud Dataproc V1 API - Class Google::Cloud::Dataproc::V1::VirtualClusterConfig (v0.9.0)

Version 0.9.0

• 1.1.0 (latest)
• 1.0.2
• 0.26.0
• 0.25.0
• 0.24.1
• 0.23.1
• 0.22.0
• 0.21.0
• 0.20.0
• 0.19.0
• 0.18.1
• 0.17.0
• 0.16.0
• 0.15.0
• 0.14.0
• 0.13.0
• 0.12.0
• 0.11.0
• 0.10.0
• 0.9.0
• 0.8.0
• 0.7.1

Reference documentation and code samples for the Cloud Dataproc V1 API class Google::Cloud::Dataproc::V1::VirtualClusterConfig.

Dataproc cluster config for a cluster that does not directly control the underlying compute resources, such as a Dataproc-on-GKE cluster.

Inherits

• Object

Extended By

• Google::Protobuf::MessageExts::ClassMethods

Includes

• Google::Protobuf::MessageExts

Methods

#auxiliary_services_config

def auxiliary_services_config() -> ::Google::Cloud::Dataproc::V1::AuxiliaryServicesConfig

Returns

• (::Google::Cloud::Dataproc::V1::AuxiliaryServicesConfig) — Optional. Configuration of auxiliary services used by this cluster.

#auxiliary_services_config=

def auxiliary_services_config=(value) -> ::Google::Cloud::Dataproc::V1::AuxiliaryServicesConfig

Parameter

• value (::Google::Cloud::Dataproc::V1::AuxiliaryServicesConfig) — Optional. Configuration of auxiliary services used by this cluster.

Returns

• (::Google::Cloud::Dataproc::V1::AuxiliaryServicesConfig) — Optional. Configuration of auxiliary services used by this cluster.

#kubernetes_cluster_config

def kubernetes_cluster_config() -> ::Google::Cloud::Dataproc::V1::KubernetesClusterConfig

Returns

• (::Google::Cloud::Dataproc::V1::KubernetesClusterConfig) — Required. The configuration for running the Dataproc cluster on Kubernetes.

#kubernetes_cluster_config=

def kubernetes_cluster_config=(value) -> ::Google::Cloud::Dataproc::V1::KubernetesClusterConfig

Parameter

• value (::Google::Cloud::Dataproc::V1::KubernetesClusterConfig) — Required. The configuration for running the Dataproc cluster on Kubernetes.

Returns

• (::Google::Cloud::Dataproc::V1::KubernetesClusterConfig) — Required. The configuration for running the Dataproc cluster on Kubernetes.

#staging_bucket

def staging_bucket() -> ::String

Returns

• (::String) — Optional. A Storage bucket used to stage job dependencies, config files, and job driver console output. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location (US, ASIA, or EU) for your cluster's staging bucket according to the Compute Engine zone where your cluster is deployed, and then create and manage this project-level, per-location bucket (see Dataproc staging and temp buckets). This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.

#staging_bucket=

def staging_bucket=(value) -> ::String

Parameter

• value (::String) — Optional. A Storage bucket used to stage job dependencies, config files, and job driver console output. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location (US, ASIA, or EU) for your cluster's staging bucket according to the Compute Engine zone where your cluster is deployed, and then create and manage this project-level, per-location bucket (see Dataproc staging and temp buckets). This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.

Returns

• (::String) — Optional. A Storage bucket used to stage job dependencies, config files, and job driver console output. If you do not specify a staging bucket, Cloud Dataproc will determine a Cloud Storage location (US, ASIA, or EU) for your cluster's staging bucket according to the Compute Engine zone where your cluster is deployed, and then create and manage this project-level, per-location bucket (see Dataproc staging and temp buckets). This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.

#temp_bucket

def temp_bucket() -> ::String

Returns

• (::String) — Optional. A Cloud Storage bucket used to store ephemeral cluster and jobs data, such as Spark and MapReduce history files. If you do not specify a temp bucket, Dataproc will determine a Cloud Storage location (US, ASIA, or EU) for your cluster's temp bucket according to the Compute Engine zone where your cluster is deployed, and then create and manage this project-level, per-location bucket. The default bucket has a TTL of 90 days, but you can use any TTL (or none) if you specify a bucket (see Dataproc staging and temp buckets). This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.

#temp_bucket=

def temp_bucket=(value) -> ::String

Parameter

• value (::String) — Optional. A Cloud Storage bucket used to store ephemeral cluster and jobs data, such as Spark and MapReduce history files. If you do not specify a temp bucket, Dataproc will determine a Cloud Storage location (US, ASIA, or EU) for your cluster's temp bucket according to the Compute Engine zone where your cluster is deployed, and then create and manage this project-level, per-location bucket. The default bucket has a TTL of 90 days, but you can use any TTL (or none) if you specify a bucket (see Dataproc staging and temp buckets). This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.

Returns

• (::String) — Optional. A Cloud Storage bucket used to store ephemeral cluster and jobs data, such as Spark and MapReduce history files. If you do not specify a temp bucket, Dataproc will determine a Cloud Storage location (US, ASIA, or EU) for your cluster's temp bucket according to the Compute Engine zone where your cluster is deployed, and then create and manage this project-level, per-location bucket. The default bucket has a TTL of 90 days, but you can use any TTL (or none) if you specify a bucket (see Dataproc staging and temp buckets). This field requires a Cloud Storage bucket name, not a gs://... URI to a Cloud Storage bucket.