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feat: add Dataproc Serverless for Spark Batches API (#290)
* feat: add Dataproc Serverless for Spark Batches API Committer: @medb PiperOrigin-RevId: 402631995 Source-Link: googleapis/googleapis@95af2e4 Source-Link: https://github.com/googleapis/googleapis-gen/commit/0ee7abd9ecd2951e958303681a4b251a948107b6 Copy-Tag: eyJwIjoiLmdpdGh1Yi8uT3dsQm90LnlhbWwiLCJoIjoiMGVlN2FiZDllY2QyOTUxZTk1ODMwMzY4MWE0YjI1MWE5NDgxMDdiNiJ9 * 🦉 Updates from OwlBot See https://github.com/googleapis/repo-automation-bots/blob/main/packages/owl-bot/README.md Co-authored-by: Owl Bot <gcf-owl-bot[bot]@users.noreply.github.com>
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‎google/cloud/dataproc/__init__.py‎

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from google.cloud.dataproc_v1.types.clusters import ClusterConfig
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from google.cloud.dataproc_v1.types.clusters import ClusterMetrics
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from google.cloud.dataproc_v1.types.clusters import ClusterStatus
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from google.cloud.dataproc_v1.types.clusters import ConfidentialInstanceConfig
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from google.cloud.dataproc_v1.types.clusters import CreateClusterRequest
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from google.cloud.dataproc_v1.types.clusters import DeleteClusterRequest
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from google.cloud.dataproc_v1.types.clusters import DiagnoseClusterRequest
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from google.cloud.dataproc_v1.types.jobs import SubmitJobRequest
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from google.cloud.dataproc_v1.types.jobs import UpdateJobRequest
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from google.cloud.dataproc_v1.types.jobs import YarnApplication
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from google.cloud.dataproc_v1.types.operations import BatchOperationMetadata
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from google.cloud.dataproc_v1.types.operations import ClusterOperationMetadata
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from google.cloud.dataproc_v1.types.operations import ClusterOperationStatus
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from google.cloud.dataproc_v1.types.shared import EnvironmentConfig
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from google.cloud.dataproc_v1.types.shared import ExecutionConfig
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from google.cloud.dataproc_v1.types.shared import PeripheralsConfig
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from google.cloud.dataproc_v1.types.shared import RuntimeConfig
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from google.cloud.dataproc_v1.types.shared import RuntimeInfo
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from google.cloud.dataproc_v1.types.shared import SparkHistoryServerConfig
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from google.cloud.dataproc_v1.types.shared import Component
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from google.cloud.dataproc_v1.types.shared import FailureAction
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from google.cloud.dataproc_v1.types.workflow_templates import ClusterOperation
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from google.cloud.dataproc_v1.types.workflow_templates import ClusterSelector
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from google.cloud.dataproc_v1.types.workflow_templates import (
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"ClusterConfig",
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"ClusterMetrics",
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"ClusterStatus",
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"ConfidentialInstanceConfig",
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"CreateClusterRequest",
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"DeleteClusterRequest",
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"DiagnoseClusterRequest",
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"SubmitJobRequest",
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"UpdateJobRequest",
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"YarnApplication",
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"BatchOperationMetadata",
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"ClusterOperationMetadata",
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"ClusterOperationStatus",
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"EnvironmentConfig",
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"ExecutionConfig",
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"PeripheralsConfig",
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"RuntimeConfig",
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"RuntimeInfo",
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"SparkHistoryServerConfig",
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"Component",
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"FailureAction",
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"ClusterOperation",
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"ClusterSelector",
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"CreateWorkflowTemplateRequest",

‎google/cloud/dataproc_v1/__init__.py‎

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from .types.clusters import ClusterConfig
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from .types.clusters import ClusterMetrics
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from .types.clusters import ClusterStatus
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from .types.clusters import ConfidentialInstanceConfig
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from .types.clusters import CreateClusterRequest
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from .types.clusters import DeleteClusterRequest
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from .types.clusters import DiagnoseClusterRequest
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from .types.jobs import SubmitJobRequest
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from .types.jobs import UpdateJobRequest
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from .types.jobs import YarnApplication
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from .types.operations import BatchOperationMetadata
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from .types.operations import ClusterOperationMetadata
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from .types.operations import ClusterOperationStatus
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from .types.shared import EnvironmentConfig
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from .types.shared import ExecutionConfig
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from .types.shared import PeripheralsConfig
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from .types.shared import RuntimeConfig
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from .types.shared import RuntimeInfo
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from .types.shared import SparkHistoryServerConfig
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from .types.shared import Component
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from .types.shared import FailureAction
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from .types.workflow_templates import ClusterOperation
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from .types.workflow_templates import ClusterSelector
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from .types.workflow_templates import CreateWorkflowTemplateRequest
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"AutoscalingPolicyServiceClient",
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"BasicAutoscalingAlgorithm",
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"BasicYarnAutoscalingConfig",
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"BatchOperationMetadata",
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"CancelJobRequest",
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"Cluster",
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"ClusterConfig",
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"ClusterSelector",
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"ClusterStatus",
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"Component",
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"ConfidentialInstanceConfig",
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"CreateAutoscalingPolicyRequest",
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"CreateClusterRequest",
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"CreateWorkflowTemplateRequest",
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"DiskConfig",
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"EncryptionConfig",
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"EndpointConfig",
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"EnvironmentConfig",
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"ExecutionConfig",
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"FailureAction",
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"GceClusterConfig",
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"GetAutoscalingPolicyRequest",
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"GetClusterRequest",
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"NodeInitializationAction",
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"OrderedJob",
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"ParameterValidation",
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"PeripheralsConfig",
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"PigJob",
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"PrestoJob",
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"PySparkJob",
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"QueryList",
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"RegexValidation",
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"ReservationAffinity",
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"RuntimeConfig",
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"RuntimeInfo",
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"SecurityConfig",
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"ShieldedInstanceConfig",
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"SoftwareConfig",
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"SparkHistoryServerConfig",
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"SparkJob",
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"SparkRJob",
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"SparkSqlJob",

‎google/cloud/dataproc_v1/services/cluster_controller/async_client.py‎

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An object representing a long-running operation.
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The result type for the operation will be :class:`google.cloud.dataproc_v1.types.Cluster` Describes the identifying information, config, and status of
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a cluster of Compute Engine instances.
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a Dataproc cluster
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"""
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# Create or coerce a protobuf request object.
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[Operation.metadata][google.longrunning.Operation.metadata] will
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be
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`ClusterOperationMetadata <https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#clusteroperationmetadata>`__.
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The cluster must be in a
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[``RUNNING``][google.cloud.dataproc.v1.ClusterStatus.State]
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state or an error is returned.
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Args:
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request (:class:`google.cloud.dataproc_v1.types.UpdateClusterRequest`):
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An object representing a long-running operation.
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The result type for the operation will be :class:`google.cloud.dataproc_v1.types.Cluster` Describes the identifying information, config, and status of
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a cluster of Compute Engine instances.
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a Dataproc cluster
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"""
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# Create or coerce a protobuf request object.
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An object representing a long-running operation.
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The result type for the operation will be :class:`google.cloud.dataproc_v1.types.Cluster` Describes the identifying information, config, and status of
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a cluster of Compute Engine instances.
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a Dataproc cluster
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"""
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# Create or coerce a protobuf request object.
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An object representing a long-running operation.
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The result type for the operation will be :class:`google.cloud.dataproc_v1.types.Cluster` Describes the identifying information, config, and status of
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a cluster of Compute Engine instances.
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a Dataproc cluster
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"""
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# Create or coerce a protobuf request object.
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google.cloud.dataproc_v1.types.Cluster:
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Describes the identifying
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cluster of Compute Engine instances.
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Dataproc cluster
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"""
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# Create or coerce a protobuf request object.

‎google/cloud/dataproc_v1/services/cluster_controller/client.py‎

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An object representing a long-running operation.
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The result type for the operation will be :class:`google.cloud.dataproc_v1.types.Cluster` Describes the identifying information, config, and status of
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a cluster of Compute Engine instances.
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a Dataproc cluster
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"""
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# Create or coerce a protobuf request object.
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[Operation.metadata][google.longrunning.Operation.metadata] will
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`ClusterOperationMetadata <https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#clusteroperationmetadata>`__.
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The cluster must be in a
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[``RUNNING``][google.cloud.dataproc.v1.ClusterStatus.State]
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state or an error is returned.
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Args:
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request (Union[google.cloud.dataproc_v1.types.UpdateClusterRequest, dict]):
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An object representing a long-running operation.
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The result type for the operation will be :class:`google.cloud.dataproc_v1.types.Cluster` Describes the identifying information, config, and status of
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a cluster of Compute Engine instances.
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a Dataproc cluster
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"""
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# Create or coerce a protobuf request object.
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An object representing a long-running operation.
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The result type for the operation will be :class:`google.cloud.dataproc_v1.types.Cluster` Describes the identifying information, config, and status of
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a Dataproc cluster
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"""
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# Create or coerce a protobuf request object.
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An object representing a long-running operation.
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The result type for the operation will be :class:`google.cloud.dataproc_v1.types.Cluster` Describes the identifying information, config, and status of
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a cluster of Compute Engine instances.
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a Dataproc cluster
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"""
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# Create or coerce a protobuf request object.
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google.cloud.dataproc_v1.types.Cluster:
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Describes the identifying
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information, config, and status of a
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Dataproc cluster
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# Create or coerce a protobuf request object.

‎google/cloud/dataproc_v1/services/cluster_controller/transports/grpc.py‎

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[Operation.metadata][google.longrunning.Operation.metadata] will
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`ClusterOperationMetadata <https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#clusteroperationmetadata>`__.
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The cluster must be in a
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[``RUNNING``][google.cloud.dataproc.v1.ClusterStatus.State]
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state or an error is returned.
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Returns:
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Callable[[~.UpdateClusterRequest],

‎google/cloud/dataproc_v1/services/cluster_controller/transports/grpc_asyncio.py‎

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[Operation.metadata][google.longrunning.Operation.metadata] will
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be
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`ClusterOperationMetadata <https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#clusteroperationmetadata>`__.
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The cluster must be in a
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[``RUNNING``][google.cloud.dataproc.v1.ClusterStatus.State]
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state or an error is returned.
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Returns:
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Callable[[~.UpdateClusterRequest],

‎google/cloud/dataproc_v1/types/__init__.py‎

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ClusterConfig,
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ClusterMetrics,
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ClusterStatus,
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ConfidentialInstanceConfig,
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CreateClusterRequest,
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DeleteClusterRequest,
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DiagnoseClusterRequest,
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YarnApplication,
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)
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from .operations import (
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BatchOperationMetadata,
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ClusterOperationMetadata,
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ClusterOperationStatus,
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)
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from .shared import (
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EnvironmentConfig,
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ExecutionConfig,
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PeripheralsConfig,
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RuntimeConfig,
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RuntimeInfo,
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SparkHistoryServerConfig,
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Component,
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FailureAction,
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)
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from .workflow_templates import (
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ClusterOperation,
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ClusterSelector,
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"ClusterConfig",
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"ClusterMetrics",
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"ClusterStatus",
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"ConfidentialInstanceConfig",
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"CreateClusterRequest",
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"DeleteClusterRequest",
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"DiagnoseClusterRequest",
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"SubmitJobRequest",
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"UpdateJobRequest",
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"YarnApplication",
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"BatchOperationMetadata",
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"ClusterOperationMetadata",
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"ClusterOperationStatus",
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"EnvironmentConfig",
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"ExecutionConfig",
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"PeripheralsConfig",
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"RuntimeConfig",
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"RuntimeInfo",
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"SparkHistoryServerConfig",
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"Component",
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"FailureAction",
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"ClusterOperation",
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"ClusterSelector",
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"CreateWorkflowTemplateRequest",

‎google/cloud/dataproc_v1/types/autoscaling_policies.py‎

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secondary_worker_config (google.cloud.dataproc_v1.types.InstanceGroupAutoscalingPolicyConfig):
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Optional. Describes how the autoscaler will
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operate for secondary workers.
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labels (Sequence[google.cloud.dataproc_v1.types.AutoscalingPolicy.LabelsEntry]):
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Optional. The labels to associate with this autoscaling
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policy. Label **keys** must contain 1 to 63 characters, and
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must conform to `RFC
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1035 <https://www.ietf.org/rfc/rfc1035.txt>`__. Label
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**values** may be empty, but, if present, must contain 1 to
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63 characters, and must conform to `RFC
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1035 <https://www.ietf.org/rfc/rfc1035.txt>`__. No more than
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32 labels can be associated with an autoscaling policy.
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"""
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id = proto.Field(proto.STRING, number=1,)
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secondary_worker_config = proto.Field(
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proto.MESSAGE, number=5, message="InstanceGroupAutoscalingPolicyConfig",
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)
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labels = proto.MapField(proto.STRING, proto.STRING, number=6,)
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class BasicAutoscalingAlgorithm(proto.Message):

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