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"""This module contains a Google Cloud Dataproc hook."""
from __future__ import annotations
import time
import uuid
from typing import TYPE_CHECKING, Any, Sequence
from google.api_core.client_options import ClientOptions
from google.api_core.exceptions import ServerError
from google.api_core.gapic_v1.method import DEFAULT, _MethodDefault
from google.cloud.dataproc_v1 import (
Batch,
BatchControllerAsyncClient,
BatchControllerClient,
Cluster,
ClusterControllerAsyncClient,
ClusterControllerClient,
Job,
JobControllerAsyncClient,
JobControllerClient,
JobStatus,
WorkflowTemplate,
WorkflowTemplateServiceAsyncClient,
WorkflowTemplateServiceClient,
)
from airflow.exceptions import AirflowException
from airflow.providers.google.common.consts import CLIENT_INFO
from airflow.providers.google.common.hooks.base_google import GoogleBaseHook
from airflow.version import version as airflow_version
if TYPE_CHECKING:
from google.api_core.operation import Operation
from google.api_core.operation_async import AsyncOperation
from google.api_core.operations_v1.operations_client import OperationsClient
from google.api_core.retry import Retry
from google.api_core.retry_async import AsyncRetry
from google.protobuf.duration_pb2 import Duration
from google.protobuf.field_mask_pb2 import FieldMask
[docs]class DataProcJobBuilder:
"""A helper class for building Dataproc job."""
def __init__(
self,
project_id: str,
task_id: str,
cluster_name: str,
job_type: str,
properties: dict[str, str] | None = None,
) -> None:
name = f"{task_id.replace('.', '_')}_{uuid.uuid4()!s:.8}"
self.job_type = job_type
self.job: dict[str, Any] = {
"job": {
"reference": {"project_id": project_id, "job_id": name},
"placement": {"cluster_name": cluster_name},
"labels": {"airflow-version": "v" + airflow_version.replace(".", "-").replace("+", "-")},
job_type: {},
}
}
if properties is not None:
self.job["job"][job_type]["properties"] = properties
[docs] def add_labels(self, labels: dict | None = None) -> None:
"""Set labels for Dataproc job.
:param labels: Labels for the job query.
"""
if labels:
self.job["job"]["labels"].update(labels)
[docs] def add_variables(self, variables: dict | None = None) -> None:
"""Set variables for Dataproc job.
:param variables: Variables for the job query.
"""
if variables is not None:
self.job["job"][self.job_type]["script_variables"] = variables
[docs] def add_args(self, args: list[str] | None = None) -> None:
"""Set args for Dataproc job.
:param args: Args for the job query.
"""
if args is not None:
self.job["job"][self.job_type]["args"] = args
[docs] def add_query(self, query: str) -> None:
"""Set query for Dataproc job.
:param query: query for the job.
"""
self.job["job"][self.job_type]["query_list"] = {"queries": [query]}
[docs] def add_query_uri(self, query_uri: str) -> None:
"""Set query uri for Dataproc job.
:param query_uri: URI for the job query.
"""
self.job["job"][self.job_type]["query_file_uri"] = query_uri
[docs] def add_jar_file_uris(self, jars: list[str] | None = None) -> None:
"""Set jars uris for Dataproc job.
:param jars: List of jars URIs
"""
if jars is not None:
self.job["job"][self.job_type]["jar_file_uris"] = jars
[docs] def add_archive_uris(self, archives: list[str] | None = None) -> None:
"""Set archives uris for Dataproc job.
:param archives: List of archives URIs
"""
if archives is not None:
self.job["job"][self.job_type]["archive_uris"] = archives
[docs] def add_file_uris(self, files: list[str] | None = None) -> None:
"""Set file uris for Dataproc job.
:param files: List of files URIs
"""
if files is not None:
self.job["job"][self.job_type]["file_uris"] = files
[docs] def add_python_file_uris(self, pyfiles: list[str] | None = None) -> None:
"""Set python file uris for Dataproc job.
:param pyfiles: List of python files URIs
"""
if pyfiles is not None:
self.job["job"][self.job_type]["python_file_uris"] = pyfiles
[docs] def set_main(self, main_jar: str | None = None, main_class: str | None = None) -> None:
"""Set Dataproc main class.
:param main_jar: URI for the main file.
:param main_class: Name of the main class.
:raises: Exception
"""
if main_class is not None and main_jar is not None:
raise Exception("Set either main_jar or main_class")
if main_jar:
self.job["job"][self.job_type]["main_jar_file_uri"] = main_jar
else:
self.job["job"][self.job_type]["main_class"] = main_class
[docs] def set_python_main(self, main: str) -> None:
"""Set Dataproc main python file uri.
:param main: URI for the python main file.
"""
self.job["job"][self.job_type]["main_python_file_uri"] = main
[docs] def set_job_name(self, name: str) -> None:
"""Set Dataproc job name.
Job name is sanitized, replacing dots by underscores.
:param name: Job name.
"""
sanitized_name = f"{name.replace('.', '_')}_{uuid.uuid4()!s:.8}"
self.job["job"]["reference"]["job_id"] = sanitized_name
[docs] def build(self) -> dict:
"""Return Dataproc job.
:return: Dataproc job
"""
return self.job
[docs]class DataprocHook(GoogleBaseHook):
"""Google Cloud Dataproc APIs.
All the methods in the hook where project_id is used must be called with
keyword arguments rather than positional.
"""
def __init__(
self,
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
) -> None:
if kwargs.get("delegate_to") is not None:
raise RuntimeError(
"The `delegate_to` parameter has been deprecated before and finally removed in this version"
" of Google Provider. You MUST convert it to `impersonate_chain`"
)
super().__init__(gcp_conn_id=gcp_conn_id, impersonation_chain=impersonation_chain)
[docs] def get_cluster_client(self, region: str | None = None) -> ClusterControllerClient:
"""Create a ClusterControllerClient."""
client_options = None
if region and region != "global":
client_options = ClientOptions(api_endpoint=f"{region}-dataproc.googleapis.com:443")
return ClusterControllerClient(
credentials=self.get_credentials(), client_info=CLIENT_INFO, client_options=client_options
)
[docs] def get_template_client(self, region: str | None = None) -> WorkflowTemplateServiceClient:
"""Create a WorkflowTemplateServiceClient."""
client_options = None
if region and region != "global":
client_options = ClientOptions(api_endpoint=f"{region}-dataproc.googleapis.com:443")
return WorkflowTemplateServiceClient(
credentials=self.get_credentials(), client_info=CLIENT_INFO, client_options=client_options
)
[docs] def get_job_client(self, region: str | None = None) -> JobControllerClient:
"""Create a JobControllerClient."""
client_options = None
if region and region != "global":
client_options = ClientOptions(api_endpoint=f"{region}-dataproc.googleapis.com:443")
return JobControllerClient(
credentials=self.get_credentials(), client_info=CLIENT_INFO, client_options=client_options
)
[docs] def get_batch_client(self, region: str | None = None) -> BatchControllerClient:
"""Create a BatchControllerClient."""
client_options = None
if region and region != "global":
client_options = ClientOptions(api_endpoint=f"{region}-dataproc.googleapis.com:443")
return BatchControllerClient(
credentials=self.get_credentials(), client_info=CLIENT_INFO, client_options=client_options
)
[docs] def get_operations_client(self, region: str | None):
"""Create a OperationsClient."""
return self.get_batch_client(region=region).transport.operations_client
[docs] def wait_for_operation(
self,
operation: Operation,
timeout: float | None = None,
result_retry: AsyncRetry | _MethodDefault = DEFAULT,
) -> Any:
"""Wait for a long-lasting operation to complete."""
try:
return operation.result(timeout=timeout, retry=result_retry)
except Exception:
error = operation.exception(timeout=timeout)
raise AirflowException(error)
@GoogleBaseHook.fallback_to_default_project_id
[docs] def create_cluster(
self,
region: str,
project_id: str,
cluster_name: str,
cluster_config: dict | Cluster | None = None,
virtual_cluster_config: dict | None = None,
labels: dict[str, str] | None = None,
request_id: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Operation:
"""Create a cluster in a specified project.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region in which to handle the request.
:param cluster_name: Name of the cluster to create.
:param labels: Labels that will be assigned to created cluster.
:param cluster_config: The cluster config to create. If a dict is
provided, it must be of the same form as the protobuf message
:class:`~google.cloud.dataproc_v1.types.ClusterConfig`.
:param virtual_cluster_config: The virtual cluster config, used when
creating a Dataproc cluster that does not directly control the
underlying compute resources, for example, when creating a
Dataproc-on-GKE cluster with
:class:`~google.cloud.dataproc_v1.types.VirtualClusterConfig`.
:param request_id: A unique id used to identify the request. If the
server receives two *CreateClusterRequest* requests with the same
ID, the second request will be ignored, and an operation created
for the first one and stored in the backend is returned.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
# Dataproc labels must conform to the following regex:
# [a-z]([-a-z0-9]*[a-z0-9])? (current airflow version string follows
# semantic versioning spec: x.y.z).
labels = labels or {}
labels.update({"airflow-version": "v" + airflow_version.replace(".", "-").replace("+", "-")})
cluster = {
"project_id": project_id,
"cluster_name": cluster_name,
}
if virtual_cluster_config is not None:
cluster["virtual_cluster_config"] = virtual_cluster_config # type: ignore
if cluster_config is not None:
cluster["config"] = cluster_config # type: ignore
cluster["labels"] = labels # type: ignore
client = self.get_cluster_client(region=region)
result = client.create_cluster(
request={
"project_id": project_id,
"region": region,
"cluster": cluster,
"request_id": request_id,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] def delete_cluster(
self,
region: str,
cluster_name: str,
project_id: str,
cluster_uuid: str | None = None,
request_id: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Operation:
"""Delete a cluster in a project.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region in which to handle the request.
:param cluster_name: Name of the cluster to delete.
:param cluster_uuid: If specified, the RPC should fail if cluster with
the UUID does not exist.
:param request_id: A unique id used to identify the request. If the
server receives two *DeleteClusterRequest* requests with the same
ID, the second request will be ignored, and an operation created
for the first one and stored in the backend is returned.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
client = self.get_cluster_client(region=region)
result = client.delete_cluster(
request={
"project_id": project_id,
"region": region,
"cluster_name": cluster_name,
"cluster_uuid": cluster_uuid,
"request_id": request_id,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] def diagnose_cluster(
self,
region: str,
cluster_name: str,
project_id: str,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> str:
"""Get cluster diagnostic information.
After the operation completes, the GCS URI to diagnose is returned.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region in which to handle the request.
:param cluster_name: Name of the cluster.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
client = self.get_cluster_client(region=region)
operation = client.diagnose_cluster(
request={"project_id": project_id, "region": region, "cluster_name": cluster_name},
retry=retry,
timeout=timeout,
metadata=metadata,
)
operation.result()
gcs_uri = str(operation.operation.response.value)
return gcs_uri
@GoogleBaseHook.fallback_to_default_project_id
[docs] def get_cluster(
self,
region: str,
cluster_name: str,
project_id: str,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Cluster:
"""Get the resource representation for a cluster in a project.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param cluster_name: The cluster name.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
client = self.get_cluster_client(region=region)
result = client.get_cluster(
request={"project_id": project_id, "region": region, "cluster_name": cluster_name},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] def list_clusters(
self,
region: str,
filter_: str,
project_id: str,
page_size: int | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
):
"""List all regions/{region}/clusters in a project.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param filter_: To constrain the clusters to. Case-sensitive.
:param page_size: The maximum number of resources contained in the
underlying API response. If page streaming is performed
per-resource, this parameter does not affect the return value. If
page streaming is performed per-page, this determines the maximum
number of resources in a page.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
client = self.get_cluster_client(region=region)
result = client.list_clusters(
request={"project_id": project_id, "region": region, "filter": filter_, "page_size": page_size},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] def update_cluster(
self,
cluster_name: str,
cluster: dict | Cluster,
update_mask: dict | FieldMask,
project_id: str,
region: str,
graceful_decommission_timeout: dict | Duration | None = None,
request_id: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Operation:
"""Update a cluster in a project.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param cluster_name: The cluster name.
:param cluster: Changes to the cluster. If a dict is provided, it must
be of the same form as the protobuf message
:class:`~google.cloud.dataproc_v1.types.Cluster`.
:param update_mask: Specifies the path, relative to ``Cluster``, of the
field to update. For example, to change the number of workers in a
cluster to 5, this would be specified as
``config.worker_config.num_instances``, and the ``PATCH`` request
body would specify the new value:
.. code-block:: python
{"config": {"workerConfig": {"numInstances": "5"}}}
Similarly, to change the number of preemptible workers in a cluster
to 5, this would be ``config.secondary_worker_config.num_instances``
and the ``PATCH`` request body would be:
.. code-block:: python
{"config": {"secondaryWorkerConfig": {"numInstances": "5"}}}
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.dataproc_v1.types.FieldMask`.
:param graceful_decommission_timeout: Timeout for graceful YARN
decommissioning. Graceful decommissioning allows removing nodes from
the cluster without interrupting jobs in progress. Timeout specifies
how long to wait for jobs in progress to finish before forcefully
removing nodes (and potentially interrupting jobs). Default timeout
is 0 (for forceful decommission), and the maximum allowed timeout is
one day.
Only supported on Dataproc image versions 1.2 and higher.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.dataproc_v1.types.Duration`.
:param request_id: A unique id used to identify the request. If the
server receives two *UpdateClusterRequest* requests with the same
ID, the second request will be ignored, and an operation created
for the first one and stored in the backend is returned.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
if region is None:
raise TypeError("missing 1 required keyword argument: 'region'")
client = self.get_cluster_client(region=region)
operation = client.update_cluster(
request={
"project_id": project_id,
"region": region,
"cluster_name": cluster_name,
"cluster": cluster,
"update_mask": update_mask,
"graceful_decommission_timeout": graceful_decommission_timeout,
"request_id": request_id,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return operation
@GoogleBaseHook.fallback_to_default_project_id
[docs] def create_workflow_template(
self,
template: dict | WorkflowTemplate,
project_id: str,
region: str,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> WorkflowTemplate:
"""Create a new workflow template.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param template: The Dataproc workflow template to create. If a dict is
provided, it must be of the same form as the protobuf message
WorkflowTemplate.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
if region is None:
raise TypeError("missing 1 required keyword argument: 'region'")
metadata = metadata or ()
client = self.get_template_client(region)
parent = f"projects/{project_id}/regions/{region}"
return client.create_workflow_template(
request={"parent": parent, "template": template}, retry=retry, timeout=timeout, metadata=metadata
)
@GoogleBaseHook.fallback_to_default_project_id
[docs] def instantiate_workflow_template(
self,
template_name: str,
project_id: str,
region: str,
version: int | None = None,
request_id: str | None = None,
parameters: dict[str, str] | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Operation:
"""Instantiate a template and begins execution.
:param template_name: Name of template to instantiate.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param version: Version of workflow template to instantiate. If
specified, the workflow will be instantiated only if the current
version of the workflow template has the supplied version. This
option cannot be used to instantiate a previous version of workflow
template.
:param request_id: A tag that prevents multiple concurrent workflow
instances with the same tag from running. This mitigates risk of
concurrent instances started due to retries.
:param parameters: Map from parameter names to values that should be
used for those parameters. Values may not exceed 100 characters.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
if region is None:
raise TypeError("missing 1 required keyword argument: 'region'")
metadata = metadata or ()
client = self.get_template_client(region)
name = f"projects/{project_id}/regions/{region}/workflowTemplates/{template_name}"
operation = client.instantiate_workflow_template(
request={"name": name, "version": version, "request_id": request_id, "parameters": parameters},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return operation
@GoogleBaseHook.fallback_to_default_project_id
[docs] def instantiate_inline_workflow_template(
self,
template: dict | WorkflowTemplate,
project_id: str,
region: str,
request_id: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Operation:
"""Instantiate a template and begin execution.
:param template: The workflow template to instantiate. If a dict is
provided, it must be of the same form as the protobuf message
WorkflowTemplate.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param request_id: A tag that prevents multiple concurrent workflow
instances with the same tag from running. This mitigates risk of
concurrent instances started due to retries.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
if region is None:
raise TypeError("missing 1 required keyword argument: 'region'")
metadata = metadata or ()
client = self.get_template_client(region)
parent = f"projects/{project_id}/regions/{region}"
operation = client.instantiate_inline_workflow_template(
request={"parent": parent, "template": template, "request_id": request_id},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return operation
@GoogleBaseHook.fallback_to_default_project_id
[docs] def wait_for_job(
self,
job_id: str,
project_id: str,
region: str,
wait_time: int = 10,
timeout: int | None = None,
) -> None:
"""Poll a job to check if it has finished.
:param job_id: Dataproc job ID.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param wait_time: Number of seconds between checks.
:param timeout: How many seconds wait for job to be ready.
"""
if region is None:
raise TypeError("missing 1 required keyword argument: 'region'")
state = None
start = time.monotonic()
while state not in (JobStatus.State.ERROR, JobStatus.State.DONE, JobStatus.State.CANCELLED):
if timeout and start + timeout < time.monotonic():
raise AirflowException(f"Timeout: dataproc job {job_id} is not ready after {timeout}s")
time.sleep(wait_time)
try:
job = self.get_job(project_id=project_id, region=region, job_id=job_id)
state = job.status.state
except ServerError as err:
self.log.info("Retrying. Dataproc API returned server error when waiting for job: %s", err)
if state == JobStatus.State.ERROR:
raise AirflowException(f"Job failed:\n{job}")
if state == JobStatus.State.CANCELLED:
raise AirflowException(f"Job was cancelled:\n{job}")
@GoogleBaseHook.fallback_to_default_project_id
[docs] def get_job(
self,
job_id: str,
project_id: str,
region: str,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Job:
"""Get the resource representation for a job in a project.
:param job_id: Dataproc job ID.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
if region is None:
raise TypeError("missing 1 required keyword argument: 'region'")
client = self.get_job_client(region=region)
job = client.get_job(
request={"project_id": project_id, "region": region, "job_id": job_id},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return job
@GoogleBaseHook.fallback_to_default_project_id
[docs] def submit_job(
self,
job: dict | Job,
project_id: str,
region: str,
request_id: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Job:
"""Submit a job to a cluster.
:param job: The job resource. If a dict is provided, it must be of the
same form as the protobuf message Job.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param request_id: A tag that prevents multiple concurrent workflow
instances with the same tag from running. This mitigates risk of
concurrent instances started due to retries.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
if region is None:
raise TypeError("missing 1 required keyword argument: 'region'")
client = self.get_job_client(region=region)
return client.submit_job(
request={"project_id": project_id, "region": region, "job": job, "request_id": request_id},
retry=retry,
timeout=timeout,
metadata=metadata,
)
@GoogleBaseHook.fallback_to_default_project_id
[docs] def cancel_job(
self,
job_id: str,
project_id: str,
region: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Job:
"""Start a job cancellation request.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param job_id: The job ID.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
client = self.get_job_client(region=region)
job = client.cancel_job(
request={"project_id": project_id, "region": region, "job_id": job_id},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return job
@GoogleBaseHook.fallback_to_default_project_id
[docs] def create_batch(
self,
region: str,
project_id: str,
batch: dict | Batch,
batch_id: str | None = None,
request_id: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Operation:
"""Create a batch workload.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param batch: The batch to create.
:param batch_id: The ID to use for the batch, which will become the
final component of the batch's resource name. This value must be of
4-63 characters. Valid characters are ``[a-z][0-9]-``.
:param request_id: A unique id used to identify the request. If the
server receives two *CreateBatchRequest* requests with the same
ID, the second request will be ignored, and an operation created
for the first one and stored in the backend is returned.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
client = self.get_batch_client(region)
parent = f"projects/{project_id}/regions/{region}"
result = client.create_batch(
request={
"parent": parent,
"batch": batch,
"batch_id": batch_id,
"request_id": request_id,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] def delete_batch(
self,
batch_id: str,
region: str,
project_id: str,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> None:
"""Delete the batch workload resource.
:param batch_id: The batch ID.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
client = self.get_batch_client(region)
name = f"projects/{project_id}/locations/{region}/batches/{batch_id}"
client.delete_batch(
request={
"name": name,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
@GoogleBaseHook.fallback_to_default_project_id
[docs] def get_batch(
self,
batch_id: str,
region: str,
project_id: str,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Batch:
"""Get the batch workload resource representation.
:param batch_id: The batch ID.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
client = self.get_batch_client(region)
name = f"projects/{project_id}/locations/{region}/batches/{batch_id}"
result = client.get_batch(
request={
"name": name,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] def list_batches(
self,
region: str,
project_id: str,
page_size: int | None = None,
page_token: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
filter: str | None = None,
order_by: str | None = None,
):
"""List batch workloads.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param page_size: The maximum number of batches to return in each
response. The service may return fewer than this value. The default
page size is 20; the maximum page size is 1000.
:param page_token: A page token received from a previous ``ListBatches``
call. Provide this token to retrieve the subsequent page.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
:param filter: Result filters as specified in ListBatchesRequest
:param order_by: How to order results as specified in ListBatchesRequest
"""
client = self.get_batch_client(region)
parent = f"projects/{project_id}/regions/{region}"
result = client.list_batches(
request={
"parent": parent,
"page_size": page_size,
"page_token": page_token,
"filter": filter,
"order_by": order_by,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] def wait_for_batch(
self,
batch_id: str,
region: str,
project_id: str,
wait_check_interval: int = 10,
retry: AsyncRetry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Batch:
"""Wait for a batch job to complete.
After submission of a batch job, the operator waits for the job to
complete. This hook is, however, useful in the case when Airflow is
restarted or the task pid is killed for any reason. In this case, the
creation would happen again, catching the raised AlreadyExists, and fail
to this function for waiting on completion.
:param batch_id: The batch ID.
:param region: Cloud Dataproc region to handle the request.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param wait_check_interval: The amount of time to pause between checks
for job completion.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
state = None
first_loop: bool = True
while state not in [
Batch.State.CANCELLED,
Batch.State.FAILED,
Batch.State.SUCCEEDED,
Batch.State.STATE_UNSPECIFIED,
]:
try:
if not first_loop:
time.sleep(wait_check_interval)
first_loop = False
self.log.debug("Waiting for batch %s", batch_id)
result = self.get_batch(
batch_id=batch_id,
region=region,
project_id=project_id,
retry=retry,
timeout=timeout,
metadata=metadata,
)
state = result.state
except ServerError as err:
self.log.info(
"Retrying. Dataproc API returned server error when waiting for batch id %s: %s",
batch_id,
err,
)
return result
[docs]class DataprocAsyncHook(GoogleBaseHook):
"""Asynchronous interaction with Google Cloud Dataproc APIs.
All the methods in the hook where project_id is used must be called with
keyword arguments rather than positional.
"""
def __init__(
self,
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
) -> None:
if kwargs.get("delegate_to") is not None:
raise RuntimeError(
"The `delegate_to` parameter has been deprecated before and finally removed in this version"
" of Google Provider. You MUST convert it to `impersonate_chain`"
)
super().__init__(gcp_conn_id=gcp_conn_id, impersonation_chain=impersonation_chain)
self._cached_client: JobControllerAsyncClient | None = None
[docs] def get_cluster_client(self, region: str | None = None) -> ClusterControllerAsyncClient:
"""Create a ClusterControllerAsyncClient."""
client_options = None
if region and region != "global":
client_options = ClientOptions(api_endpoint=f"{region}-dataproc.googleapis.com:443")
return ClusterControllerAsyncClient(
credentials=self.get_credentials(), client_info=CLIENT_INFO, client_options=client_options
)
[docs] def get_template_client(self, region: str | None = None) -> WorkflowTemplateServiceAsyncClient:
"""Create a WorkflowTemplateServiceAsyncClient."""
client_options = None
if region and region != "global":
client_options = ClientOptions(api_endpoint=f"{region}-dataproc.googleapis.com:443")
return WorkflowTemplateServiceAsyncClient(
credentials=self.get_credentials(), client_info=CLIENT_INFO, client_options=client_options
)
[docs] def get_job_client(self, region: str | None = None) -> JobControllerAsyncClient:
"""Create a JobControllerAsyncClient."""
if self._cached_client is None:
client_options = None
if region and region != "global":
client_options = ClientOptions(api_endpoint=f"{region}-dataproc.googleapis.com:443")
self._cached_client = JobControllerAsyncClient(
credentials=self.get_credentials(),
client_info=CLIENT_INFO,
client_options=client_options,
)
return self._cached_client
[docs] def get_batch_client(self, region: str | None = None) -> BatchControllerAsyncClient:
"""Create a BatchControllerAsyncClient."""
client_options = None
if region and region != "global":
client_options = ClientOptions(api_endpoint=f"{region}-dataproc.googleapis.com:443")
return BatchControllerAsyncClient(
credentials=self.get_credentials(), client_info=CLIENT_INFO, client_options=client_options
)
[docs] def get_operations_client(self, region: str) -> OperationsClient:
"""Create a OperationsClient."""
return self.get_template_client(region=region).transport.operations_client
@GoogleBaseHook.fallback_to_default_project_id
[docs] async def create_cluster(
self,
region: str,
project_id: str,
cluster_name: str,
cluster_config: dict | Cluster | None = None,
virtual_cluster_config: dict | None = None,
labels: dict[str, str] | None = None,
request_id: str | None = None,
retry: AsyncRetry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> AsyncOperation:
"""Create a cluster in a project.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region in which to handle the request.
:param cluster_name: Name of the cluster to create.
:param labels: Labels that will be assigned to created cluster.
:param cluster_config: The cluster config to create. If a dict is
provided, it must be of the same form as the protobuf message
:class:`~google.cloud.dataproc_v1.types.ClusterConfig`.
:param virtual_cluster_config: The virtual cluster config, used when
creating a Dataproc cluster that does not directly control the
underlying compute resources, for example, when creating a
Dataproc-on-GKE cluster with
:class:`~google.cloud.dataproc_v1.types.VirtualClusterConfig`.
:param request_id: A unique id used to identify the request. If the
server receives two *CreateClusterRequest* requests with the same
ID, the second request will be ignored, and an operation created
for the first one and stored in the backend is returned.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
# Dataproc labels must conform to the following regex:
# [a-z]([-a-z0-9]*[a-z0-9])? (current airflow version string follows
# semantic versioning spec: x.y.z).
labels = labels or {}
labels.update({"airflow-version": "v" + airflow_version.replace(".", "-").replace("+", "-")})
cluster = {
"project_id": project_id,
"cluster_name": cluster_name,
}
if virtual_cluster_config is not None:
cluster["virtual_cluster_config"] = virtual_cluster_config # type: ignore
if cluster_config is not None:
cluster["config"] = cluster_config # type: ignore
cluster["labels"] = labels # type: ignore
client = self.get_cluster_client(region=region)
result = await client.create_cluster(
request={
"project_id": project_id,
"region": region,
"cluster": cluster,
"request_id": request_id,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] async def delete_cluster(
self,
region: str,
cluster_name: str,
project_id: str,
cluster_uuid: str | None = None,
request_id: str | None = None,
retry: AsyncRetry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> AsyncOperation:
"""Delete a cluster in a project.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region in which to handle the request.
:param cluster_name: Name of the cluster to delete.
:param cluster_uuid: If specified, the RPC should fail if cluster with
the UUID does not exist.
:param request_id: A unique id used to identify the request. If the
server receives two *DeleteClusterRequest* requests with the same
ID, the second request will be ignored, and an operation created
for the first one and stored in the backend is returned.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
client = self.get_cluster_client(region=region)
result = await client.delete_cluster(
request={
"project_id": project_id,
"region": region,
"cluster_name": cluster_name,
"cluster_uuid": cluster_uuid,
"request_id": request_id,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] async def diagnose_cluster(
self,
region: str,
cluster_name: str,
project_id: str,
retry: AsyncRetry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> str:
"""Get cluster diagnostic information.
After the operation completes, the GCS URI to diagnose is returned.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region in which to handle the request.
:param cluster_name: Name of the cluster.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
client = self.get_cluster_client(region=region)
operation = await client.diagnose_cluster(
request={"project_id": project_id, "region": region, "cluster_name": cluster_name},
retry=retry,
timeout=timeout,
metadata=metadata,
)
operation.result()
gcs_uri = str(operation.operation.response.value)
return gcs_uri
@GoogleBaseHook.fallback_to_default_project_id
[docs] async def get_cluster(
self,
region: str,
cluster_name: str,
project_id: str,
retry: AsyncRetry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Cluster:
"""Get the resource representation for a cluster in a project.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param cluster_name: The cluster name.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
client = self.get_cluster_client(region=region)
result = await client.get_cluster(
request={"project_id": project_id, "region": region, "cluster_name": cluster_name},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] async def list_clusters(
self,
region: str,
filter_: str,
project_id: str,
page_size: int | None = None,
retry: AsyncRetry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
):
"""List all regions/{region}/clusters in a project.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param filter_: To constrain the clusters to. Case-sensitive.
:param page_size: The maximum number of resources contained in the
underlying API response. If page streaming is performed
per-resource, this parameter does not affect the return value. If
page streaming is performed per-page, this determines the maximum
number of resources in a page.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
client = self.get_cluster_client(region=region)
result = await client.list_clusters(
request={"project_id": project_id, "region": region, "filter": filter_, "page_size": page_size},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] async def update_cluster(
self,
cluster_name: str,
cluster: dict | Cluster,
update_mask: dict | FieldMask,
project_id: str,
region: str,
graceful_decommission_timeout: dict | Duration | None = None,
request_id: str | None = None,
retry: AsyncRetry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> AsyncOperation:
"""Update a cluster in a project.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param cluster_name: The cluster name.
:param cluster: Changes to the cluster. If a dict is provided, it must
be of the same form as the protobuf message
:class:`~google.cloud.dataproc_v1.types.Cluster`.
:param update_mask: Specifies the path, relative to ``Cluster``, of the
field to update. For example, to change the number of workers in a
cluster to 5, this would be specified as
``config.worker_config.num_instances``, and the ``PATCH`` request
body would specify the new value:
.. code-block:: python
{"config": {"workerConfig": {"numInstances": "5"}}}
Similarly, to change the number of preemptible workers in a cluster
to 5, this would be ``config.secondary_worker_config.num_instances``
and the ``PATCH`` request body would be:
.. code-block:: python
{"config": {"secondaryWorkerConfig": {"numInstances": "5"}}}
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.dataproc_v1.types.FieldMask`.
:param graceful_decommission_timeout: Timeout for graceful YARN
decommissioning. Graceful decommissioning allows removing nodes from
the cluster without interrupting jobs in progress. Timeout specifies
how long to wait for jobs in progress to finish before forcefully
removing nodes (and potentially interrupting jobs). Default timeout
is 0 (for forceful decommission), and the maximum allowed timeout is
one day.
Only supported on Dataproc image versions 1.2 and higher.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.dataproc_v1.types.Duration`.
:param request_id: A unique id used to identify the request. If the
server receives two *UpdateClusterRequest* requests with the same
ID, the second request will be ignored, and an operation created
for the first one and stored in the backend is returned.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
if region is None:
raise TypeError("missing 1 required keyword argument: 'region'")
client = self.get_cluster_client(region=region)
operation = await client.update_cluster(
request={
"project_id": project_id,
"region": region,
"cluster_name": cluster_name,
"cluster": cluster,
"update_mask": update_mask,
"graceful_decommission_timeout": graceful_decommission_timeout,
"request_id": request_id,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return operation
@GoogleBaseHook.fallback_to_default_project_id
[docs] async def create_workflow_template(
self,
template: dict | WorkflowTemplate,
project_id: str,
region: str,
retry: AsyncRetry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> WorkflowTemplate:
"""Create a new workflow template.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param template: The Dataproc workflow template to create. If a dict is
provided, it must be of the same form as the protobuf message
WorkflowTemplate.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
if region is None:
raise TypeError("missing 1 required keyword argument: 'region'")
metadata = metadata or ()
client = self.get_template_client(region)
parent = f"projects/{project_id}/regions/{region}"
return await client.create_workflow_template(
request={"parent": parent, "template": template}, retry=retry, timeout=timeout, metadata=metadata
)
@GoogleBaseHook.fallback_to_default_project_id
[docs] async def instantiate_workflow_template(
self,
template_name: str,
project_id: str,
region: str,
version: int | None = None,
request_id: str | None = None,
parameters: dict[str, str] | None = None,
retry: AsyncRetry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> AsyncOperation:
"""Instantiate a template and begins execution.
:param template_name: Name of template to instantiate.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param version: Version of workflow template to instantiate. If
specified, the workflow will be instantiated only if the current
version of the workflow template has the supplied version. This
option cannot be used to instantiate a previous version of workflow
template.
:param request_id: A tag that prevents multiple concurrent workflow
instances with the same tag from running. This mitigates risk of
concurrent instances started due to retries.
:param parameters: Map from parameter names to values that should be
used for those parameters. Values may not exceed 100 characters.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
if region is None:
raise TypeError("missing 1 required keyword argument: 'region'")
metadata = metadata or ()
client = self.get_template_client(region)
name = f"projects/{project_id}/regions/{region}/workflowTemplates/{template_name}"
operation = await client.instantiate_workflow_template(
request={"name": name, "version": version, "request_id": request_id, "parameters": parameters},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return operation
@GoogleBaseHook.fallback_to_default_project_id
[docs] async def instantiate_inline_workflow_template(
self,
template: dict | WorkflowTemplate,
project_id: str,
region: str,
request_id: str | None = None,
retry: AsyncRetry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> AsyncOperation:
"""Instantiate a template and begin execution.
:param template: The workflow template to instantiate. If a dict is
provided, it must be of the same form as the protobuf message
WorkflowTemplate.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param request_id: A tag that prevents multiple concurrent workflow
instances with the same tag from running. This mitigates risk of
concurrent instances started due to retries.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
if region is None:
raise TypeError("missing 1 required keyword argument: 'region'")
metadata = metadata or ()
client = self.get_template_client(region)
parent = f"projects/{project_id}/regions/{region}"
operation = await client.instantiate_inline_workflow_template(
request={"parent": parent, "template": template, "request_id": request_id},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return operation
[docs] async def get_operation(self, region, operation_name):
return await self.get_operations_client(region).get_operation(name=operation_name)
@GoogleBaseHook.fallback_to_default_project_id
[docs] async def get_job(
self,
job_id: str,
project_id: str,
region: str,
retry: AsyncRetry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Job:
"""Get the resource representation for a job in a project.
:param job_id: Dataproc job ID.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
if region is None:
raise TypeError("missing 1 required keyword argument: 'region'")
client = self.get_job_client(region=region)
job = await client.get_job(
request={"project_id": project_id, "region": region, "job_id": job_id},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return job
@GoogleBaseHook.fallback_to_default_project_id
[docs] async def submit_job(
self,
job: dict | Job,
project_id: str,
region: str,
request_id: str | None = None,
retry: AsyncRetry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Job:
"""Submit a job to a cluster.
:param job: The job resource. If a dict is provided, it must be of the
same form as the protobuf message Job.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param request_id: A tag that prevents multiple concurrent workflow
instances with the same tag from running. This mitigates risk of
concurrent instances started due to retries.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
if region is None:
raise TypeError("missing 1 required keyword argument: 'region'")
client = self.get_job_client(region=region)
return await client.submit_job(
request={"project_id": project_id, "region": region, "job": job, "request_id": request_id},
retry=retry,
timeout=timeout,
metadata=metadata,
)
@GoogleBaseHook.fallback_to_default_project_id
[docs] async def cancel_job(
self,
job_id: str,
project_id: str,
region: str | None = None,
retry: AsyncRetry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Job:
"""Start a job cancellation request.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param job_id: The job ID.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
client = self.get_job_client(region=region)
job = await client.cancel_job(
request={"project_id": project_id, "region": region, "job_id": job_id},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return job
@GoogleBaseHook.fallback_to_default_project_id
[docs] async def create_batch(
self,
region: str,
project_id: str,
batch: dict | Batch,
batch_id: str | None = None,
request_id: str | None = None,
retry: AsyncRetry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> AsyncOperation:
"""Create a batch workload.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param batch: The batch to create.
:param batch_id: The ID to use for the batch, which will become the
final component of the batch's resource name. This value must be of
4-63 characters. Valid characters are ``[a-z][0-9]-``.
:param request_id: A unique id used to identify the request. If the
server receives two *CreateBatchRequest* requests with the same
ID, the second request will be ignored, and an operation created
for the first one and stored in the backend is returned.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
client = self.get_batch_client(region)
parent = f"projects/{project_id}/regions/{region}"
result = await client.create_batch(
request={
"parent": parent,
"batch": batch,
"batch_id": batch_id,
"request_id": request_id,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] async def delete_batch(
self,
batch_id: str,
region: str,
project_id: str,
retry: AsyncRetry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> None:
"""Delete the batch workload resource.
:param batch_id: The batch ID.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
client = self.get_batch_client(region)
name = f"projects/{project_id}/locations/{region}/batches/{batch_id}"
await client.delete_batch(
request={
"name": name,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
@GoogleBaseHook.fallback_to_default_project_id
[docs] async def get_batch(
self,
batch_id: str,
region: str,
project_id: str,
retry: AsyncRetry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Batch:
"""Get the batch workload resource representation.
:param batch_id: The batch ID.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
"""
client = self.get_batch_client(region)
name = f"projects/{project_id}/locations/{region}/batches/{batch_id}"
result = await client.get_batch(
request={
"name": name,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] async def list_batches(
self,
region: str,
project_id: str,
page_size: int | None = None,
page_token: str | None = None,
retry: AsyncRetry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
filter: str | None = None,
order_by: str | None = None,
):
"""List batch workloads.
:param project_id: Google Cloud project ID that the cluster belongs to.
:param region: Cloud Dataproc region to handle the request.
:param page_size: The maximum number of batches to return in each
response. The service may return fewer than this value. The default
page size is 20; the maximum page size is 1000.
:param page_token: A page token received from a previous ``ListBatches``
call. Provide this token to retrieve the subsequent page.
:param retry: A retry object used to retry requests. If *None*, requests
will not be retried.
:param timeout: The amount of time, in seconds, to wait for the request
to complete. If *retry* is specified, the timeout applies to each
individual attempt.
:param metadata: Additional metadata that is provided to the method.
:param filter: Result filters as specified in ListBatchesRequest
:param order_by: How to order results as specified in ListBatchesRequest
"""
client = self.get_batch_client(region)
parent = f"projects/{project_id}/regions/{region}"
result = await client.list_batches(
request={
"parent": parent,
"page_size": page_size,
"page_token": page_token,
"filter": filter,
"order_by": order_by,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
