Class ClusterControllerClient (5.0.1)

ClusterControllerClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.dataproc_v1.services.cluster_controller.transports.base.ClusterControllerTransport]] = None, client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

The ClusterControllerService provides methods to manage clusters of Compute Engine instances.

Inheritance

builtins.object > ClusterControllerClient

Properties

transport

Returns the transport used by the client instance.

Returns
TypeDescription
ClusterControllerTransportThe transport used by the client instance.

Methods

ClusterControllerClient

ClusterControllerClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.dataproc_v1.services.cluster_controller.transports.base.ClusterControllerTransport]] = None, client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

Instantiates the cluster controller client.

Parameters
NameDescription
credentials Optional[google.auth.credentials.Credentials]

The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment.

transport Union[str, ClusterControllerTransport]

The transport to use. If set to None, a transport is chosen automatically.

client_options google.api_core.client_options.ClientOptions

Custom options for the client. It won't take effect if a transport instance is provided. (1) The api_endpoint property can be used to override the default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT environment variable can also be used to override the endpoint: "always" (always use the default mTLS endpoint), "never" (always use the default regular endpoint) and "auto" (auto switch to the default mTLS endpoint if client certificate is present, this is the default value). However, the api_endpoint property takes precedence if provided. (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "true", then the client_cert_source property can be used to provide client certificate for mutual TLS transport. If not provided, the default SSL client certificate will be used if present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not set, no client certificate will be used.

client_info google.api_core.gapic_v1.client_info.ClientInfo

The client info used to send a user-agent string along with API requests. If None, then default info will be used. Generally, you only need to set this if you're developing your own client library.

Exceptions
TypeDescription
google.auth.exceptions.MutualTLSChannelErrorIf mutual TLS transport creation failed for any reason.

__exit__

__exit__(type, value, traceback)

Releases underlying transport's resources.

common_billing_account_path

common_billing_account_path(billing_account: str)

Returns a fully-qualified billing_account string.

common_folder_path

common_folder_path(folder: str)

Returns a fully-qualified folder string.

common_location_path

common_location_path(project: str, location: str)

Returns a fully-qualified location string.

common_organization_path

common_organization_path(organization: str)

Returns a fully-qualified organization string.

common_project_path

common_project_path(project: str)

Returns a fully-qualified project string.

create_cluster

create_cluster(request: Optional[Union[google.cloud.dataproc_v1.types.clusters.CreateClusterRequest, dict]] = None, *, project_id: Optional[str] = None, region: Optional[str] = None, cluster: Optional[google.cloud.dataproc_v1.types.clusters.Cluster] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Creates a cluster in a project. The returned Operation.metadata][google.longrunning.Operation.metadata] will be ClusterOperationMetadata <https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#clusteroperationmetadata>__.

from google.cloud import dataproc_v1

def sample_create_cluster():
    # Create a client
    client = dataproc_v1.ClusterControllerClient()

    # Initialize request argument(s)
    cluster = dataproc_v1.Cluster()
    cluster.project_id = "project_id_value"
    cluster.cluster_name = "cluster_name_value"

    request = dataproc_v1.CreateClusterRequest(
        project_id="project_id_value",
        region="region_value",
        cluster=cluster,
    )

    # Make the request
    operation = client.create_cluster(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.dataproc_v1.types.CreateClusterRequest, dict]

The request object. A request to create a cluster.

project_id str

Required. The ID of the Google Cloud Platform project that the cluster belongs to. This corresponds to the project_id field on the request instance; if request is provided, this should not be set.

region str

Required. The Dataproc region in which to handle the request. This corresponds to the region field on the request instance; if request is provided, this should not be set.

cluster google.cloud.dataproc_v1.types.Cluster

Required. The cluster to create. This corresponds to the cluster field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation.OperationAn object representing a long-running operation. The result type for the operation will be Cluster Describes the identifying information, config, and status of a Dataproc cluster

delete_cluster

delete_cluster(request: Optional[Union[google.cloud.dataproc_v1.types.clusters.DeleteClusterRequest, dict]] = None, *, project_id: Optional[str] = None, region: Optional[str] = None, cluster_name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Deletes a cluster in a project. The returned Operation.metadata][google.longrunning.Operation.metadata] will be ClusterOperationMetadata <https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#clusteroperationmetadata>__.

from google.cloud import dataproc_v1

def sample_delete_cluster():
    # Create a client
    client = dataproc_v1.ClusterControllerClient()

    # Initialize request argument(s)
    request = dataproc_v1.DeleteClusterRequest(
        project_id="project_id_value",
        region="region_value",
        cluster_name="cluster_name_value",
    )

    # Make the request
    operation = client.delete_cluster(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.dataproc_v1.types.DeleteClusterRequest, dict]

The request object. A request to delete a cluster.

project_id str

Required. The ID of the Google Cloud Platform project that the cluster belongs to. This corresponds to the project_id field on the request instance; if request is provided, this should not be set.

region str

Required. The Dataproc region in which to handle the request. This corresponds to the region field on the request instance; if request is provided, this should not be set.

cluster_name str

Required. The cluster name. This corresponds to the cluster_name field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation.OperationAn object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }

diagnose_cluster

diagnose_cluster(request: Optional[Union[google.cloud.dataproc_v1.types.clusters.DiagnoseClusterRequest, dict]] = None, *, project_id: Optional[str] = None, region: Optional[str] = None, cluster_name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Gets cluster diagnostic information. The returned Operation.metadata][google.longrunning.Operation.metadata] will be ClusterOperationMetadata <https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#clusteroperationmetadata>. After the operation completes, Operation.response][google.longrunning.Operation.response] contains DiagnoseClusterResults <https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#diagnoseclusterresults>.

from google.cloud import dataproc_v1

def sample_diagnose_cluster():
    # Create a client
    client = dataproc_v1.ClusterControllerClient()

    # Initialize request argument(s)
    request = dataproc_v1.DiagnoseClusterRequest(
        project_id="project_id_value",
        region="region_value",
        cluster_name="cluster_name_value",
    )

    # Make the request
    operation = client.diagnose_cluster(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.dataproc_v1.types.DiagnoseClusterRequest, dict]

The request object. A request to collect cluster diagnostic information.

project_id str

Required. The ID of the Google Cloud Platform project that the cluster belongs to. This corresponds to the project_id field on the request instance; if request is provided, this should not be set.

region str

Required. The Dataproc region in which to handle the request. This corresponds to the region field on the request instance; if request is provided, this should not be set.

cluster_name str

Required. The cluster name. This corresponds to the cluster_name field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation.OperationAn object representing a long-running operation. The result type for the operation will be DiagnoseClusterResults The location of diagnostic output.

from_service_account_file

from_service_account_file(filename: str, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameter
NameDescription
filename str

The path to the service account private key json file.

Returns
TypeDescription
ClusterControllerClientThe constructed client.

from_service_account_info

from_service_account_info(info: dict, *args, **kwargs)

Creates an instance of this client using the provided credentials info.

Parameter
NameDescription
info dict

The service account private key info.

Returns
TypeDescription
ClusterControllerClientThe constructed client.

from_service_account_json

from_service_account_json(filename: str, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameter
NameDescription
filename str

The path to the service account private key json file.

Returns
TypeDescription
ClusterControllerClientThe constructed client.

get_cluster

get_cluster(request: Optional[Union[google.cloud.dataproc_v1.types.clusters.GetClusterRequest, dict]] = None, *, project_id: Optional[str] = None, region: Optional[str] = None, cluster_name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Gets the resource representation for a cluster in a project.

from google.cloud import dataproc_v1

def sample_get_cluster():
    # Create a client
    client = dataproc_v1.ClusterControllerClient()

    # Initialize request argument(s)
    request = dataproc_v1.GetClusterRequest(
        project_id="project_id_value",
        region="region_value",
        cluster_name="cluster_name_value",
    )

    # Make the request
    response = client.get_cluster(request=request)

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.dataproc_v1.types.GetClusterRequest, dict]

The request object. Request to get the resource representation for a cluster in a project.

project_id str

Required. The ID of the Google Cloud Platform project that the cluster belongs to. This corresponds to the project_id field on the request instance; if request is provided, this should not be set.

region str

Required. The Dataproc region in which to handle the request. This corresponds to the region field on the request instance; if request is provided, this should not be set.

cluster_name str

Required. The cluster name. This corresponds to the cluster_name field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.dataproc_v1.types.ClusterDescribes the identifying information, config, and status of a Dataproc cluster

get_mtls_endpoint_and_cert_source

get_mtls_endpoint_and_cert_source(
    client_options: Optional[google.api_core.client_options.ClientOptions] = None,
)

Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not "true", the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "always", use the default mTLS endpoint; if the environment variabel is "never", use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Parameter
NameDescription
client_options google.api_core.client_options.ClientOptions

Custom options for the client. Only the api_endpoint and client_cert_source properties may be used in this method.

Exceptions
TypeDescription
google.auth.exceptions.MutualTLSChannelErrorIf any errors happen.
Returns
TypeDescription
Tuple[str, Callable[[], Tuple[bytes, bytes]]]returns the API endpoint and the client cert source to use.

list_clusters

list_clusters(request: Optional[Union[google.cloud.dataproc_v1.types.clusters.ListClustersRequest, dict]] = None, *, project_id: Optional[str] = None, region: Optional[str] = None, filter: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Lists all regions/{region}/clusters in a project alphabetically.

from google.cloud import dataproc_v1

def sample_list_clusters():
    # Create a client
    client = dataproc_v1.ClusterControllerClient()

    # Initialize request argument(s)
    request = dataproc_v1.ListClustersRequest(
        project_id="project_id_value",
        region="region_value",
    )

    # Make the request
    page_result = client.list_clusters(request=request)

    # Handle the response
    for response in page_result:
        print(response)
Parameters
NameDescription
request Union[google.cloud.dataproc_v1.types.ListClustersRequest, dict]

The request object. A request to list the clusters in a project.

project_id str

Required. The ID of the Google Cloud Platform project that the cluster belongs to. This corresponds to the project_id field on the request instance; if request is provided, this should not be set.

region str

Required. The Dataproc region in which to handle the request. This corresponds to the region field on the request instance; if request is provided, this should not be set.

filter str

Optional. A filter constraining the clusters to list. Filters are case-sensitive and have the following syntax: field = value [AND [field = value]] ... where field is one of status.state, clusterName, or labels.[KEY], and [KEY] is a label key. value can be * to match all values. status.state can be one of the following: ACTIVE, INACTIVE, CREATING, RUNNING, ERROR, DELETING, or UPDATING. ACTIVE contains the CREATING, UPDATING, and RUNNING states. INACTIVE contains the DELETING and ERROR states. clusterName is the name of the cluster provided at creation time. Only the logical AND operator is supported; space-separated items are treated as having an implicit AND operator. Example filter: status.state = ACTIVE AND clusterName = mycluster AND labels.env = staging AND labels.starred = * This corresponds to the filter field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.dataproc_v1.services.cluster_controller.pagers.ListClustersPagerThe list of all clusters in a project. Iterating over this object will yield results and resolve additional pages automatically.

parse_common_billing_account_path

parse_common_billing_account_path(path: str)

Parse a billing_account path into its component segments.

parse_common_folder_path

parse_common_folder_path(path: str)

Parse a folder path into its component segments.

parse_common_location_path

parse_common_location_path(path: str)

Parse a location path into its component segments.

parse_common_organization_path

parse_common_organization_path(path: str)

Parse a organization path into its component segments.

parse_common_project_path

parse_common_project_path(path: str)

Parse a project path into its component segments.

parse_service_path

parse_service_path(path: str)

Parses a service path into its component segments.

service_path

service_path(project: str, location: str, service: str)

Returns a fully-qualified service string.

start_cluster

start_cluster(request: Optional[Union[google.cloud.dataproc_v1.types.clusters.StartClusterRequest, dict]] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Starts a cluster in a project.

from google.cloud import dataproc_v1

def sample_start_cluster():
    # Create a client
    client = dataproc_v1.ClusterControllerClient()

    # Initialize request argument(s)
    request = dataproc_v1.StartClusterRequest(
        project_id="project_id_value",
        region="region_value",
        cluster_name="cluster_name_value",
    )

    # Make the request
    operation = client.start_cluster(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.dataproc_v1.types.StartClusterRequest, dict]

The request object. A request to start a cluster.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation.OperationAn object representing a long-running operation. The result type for the operation will be Cluster Describes the identifying information, config, and status of a Dataproc cluster

stop_cluster

stop_cluster(request: Optional[Union[google.cloud.dataproc_v1.types.clusters.StopClusterRequest, dict]] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Stops a cluster in a project.

from google.cloud import dataproc_v1

def sample_stop_cluster():
    # Create a client
    client = dataproc_v1.ClusterControllerClient()

    # Initialize request argument(s)
    request = dataproc_v1.StopClusterRequest(
        project_id="project_id_value",
        region="region_value",
        cluster_name="cluster_name_value",
    )

    # Make the request
    operation = client.stop_cluster(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.dataproc_v1.types.StopClusterRequest, dict]

The request object. A request to stop a cluster.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation.OperationAn object representing a long-running operation. The result type for the operation will be Cluster Describes the identifying information, config, and status of a Dataproc cluster

update_cluster

update_cluster(request: Optional[Union[google.cloud.dataproc_v1.types.clusters.UpdateClusterRequest, dict]] = None, *, project_id: Optional[str] = None, region: Optional[str] = None, cluster_name: Optional[str] = None, cluster: Optional[google.cloud.dataproc_v1.types.clusters.Cluster] = None, update_mask: Optional[google.protobuf.field_mask_pb2.FieldMask] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

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

from google.cloud import dataproc_v1

def sample_update_cluster():
    # Create a client
    client = dataproc_v1.ClusterControllerClient()

    # Initialize request argument(s)
    cluster = dataproc_v1.Cluster()
    cluster.project_id = "project_id_value"
    cluster.cluster_name = "cluster_name_value"

    request = dataproc_v1.UpdateClusterRequest(
        project_id="project_id_value",
        region="region_value",
        cluster_name="cluster_name_value",
        cluster=cluster,
    )

    # Make the request
    operation = client.update_cluster(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.dataproc_v1.types.UpdateClusterRequest, dict]

The request object. A request to update a cluster.

project_id str

Required. The ID of the Google Cloud Platform project the cluster belongs to. This corresponds to the project_id field on the request instance; if request is provided, this should not be set.

region str

Required. The Dataproc region in which to handle the request. This corresponds to the region field on the request instance; if request is provided, this should not be set.

cluster_name str

Required. The cluster name. This corresponds to the cluster_name field on the request instance; if request is provided, this should not be set.

cluster google.cloud.dataproc_v1.types.Cluster

Required. The changes to the cluster. This corresponds to the cluster field on the request instance; if request is provided, this should not be set.

update_mask google.protobuf.field_mask_pb2.FieldMask

Required. Specifies the path, relative to Cluster, of the field to update. For example, to change the number of workers in a cluster to 5, the update_mask parameter would be specified as config.worker_config.num_instances, and the PATCH request body would specify the new value, as follows: :: { "config":{ "workerConfig":{ "numInstances":"5" } } } Similarly, to change the number of preemptible workers in a cluster to 5, the update_mask parameter would be config.secondary_worker_config.num_instances, and the PATCH request body would be set as follows: :: { "config":{ "secondaryWorkerConfig":{ "numInstances":"5" } } } Note: Currently, only the following fields can be updated: .. raw:: html

MaskPurpose
labelsUpdate labels
config.worker_config.num_instancesResize primary worker group
config.secondary_worker_config.num_instancesResize secondary worker group
config.autoscaling_config.policy_uriUse, stop using, or change autoscaling policies
This corresponds to the update_mask field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation.OperationAn object representing a long-running operation. The result type for the operation will be Cluster Describes the identifying information, config, and status of a Dataproc cluster