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from __future__ import annotations
import itertools
import json
import time
from typing import TYPE_CHECKING, Iterable, Sequence
from google.cloud.batch import ListJobsRequest, ListTasksRequest
from google.cloud.batch_v1 import (
BatchServiceAsyncClient,
BatchServiceClient,
CreateJobRequest,
Job,
JobStatus,
Task,
)
from airflow.exceptions import AirflowException
from airflow.providers.google.common.consts import CLIENT_INFO
from airflow.providers.google.common.hooks.base_google import PROVIDE_PROJECT_ID, GoogleBaseHook
if TYPE_CHECKING:
from google.api_core import operation
from google.cloud.batch_v1.services.batch_service import pagers
[docs]class CloudBatchHook(GoogleBaseHook):
"""
Hook for the Google Cloud Batch service.
:param gcp_conn_id: The connection ID to use when fetching connection info.
:param impersonation_chain: Optional service account to impersonate using short-term
credentials, or chained list of accounts required to get the access_token
of the last account in the list, which will be impersonated in the request.
If set as a string, the account must grant the originating account
the Service Account Token Creator IAM role.
If set as a sequence, the identities from the list must grant
Service Account Token Creator IAM role to the directly preceding identity, with first
account from the list granting this role to the originating account.
"""
def __init__(
self,
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
) -> None:
super().__init__(gcp_conn_id=gcp_conn_id, impersonation_chain=impersonation_chain)
self._client: BatchServiceClient | None = None
[docs] def get_conn(self):
"""
Retrieve connection to GCE Batch.
:return: Google Batch Service client object.
"""
if self._client is None:
self._client = BatchServiceClient(credentials=self.get_credentials(), client_info=CLIENT_INFO)
return self._client
@GoogleBaseHook.fallback_to_default_project_id
[docs] def submit_batch_job(
self, job_name: str, job: Job, region: str, project_id: str = PROVIDE_PROJECT_ID
) -> Job:
if isinstance(job, dict):
job = Job.from_json(json.dumps(job))
create_request = CreateJobRequest()
create_request.job = job
create_request.job_id = job_name
create_request.parent = f"projects/{project_id}/locations/{region}"
return self.get_conn().create_job(create_request)
@GoogleBaseHook.fallback_to_default_project_id
[docs] def delete_job(
self, job_name: str, region: str, project_id: str = PROVIDE_PROJECT_ID
) -> operation.Operation:
return self.get_conn().delete_job(name=f"projects/{project_id}/locations/{region}/jobs/{job_name}")
@GoogleBaseHook.fallback_to_default_project_id
[docs] def list_jobs(
self,
region: str,
project_id: str = PROVIDE_PROJECT_ID,
filter: str | None = None,
limit: int | None = None,
) -> Iterable[Job]:
if limit is not None and limit < 0:
raise AirflowException("The limit for the list jobs request should be greater or equal to zero")
list_jobs_request: ListJobsRequest = ListJobsRequest(
parent=f"projects/{project_id}/locations/{region}", filter=filter
)
jobs: pagers.ListJobsPager = self.get_conn().list_jobs(request=list_jobs_request)
return list(itertools.islice(jobs, limit))
@GoogleBaseHook.fallback_to_default_project_id
[docs] def list_tasks(
self,
region: str,
job_name: str,
project_id: str = PROVIDE_PROJECT_ID,
group_name: str = "group0",
filter: str | None = None,
limit: int | None = None,
) -> Iterable[Task]:
if limit is not None and limit < 0:
raise AirflowException("The limit for the list tasks request should be greater or equal to zero")
list_tasks_request: ListTasksRequest = ListTasksRequest(
parent=f"projects/{project_id}/locations/{region}/jobs/{job_name}/taskGroups/{group_name}",
filter=filter,
)
tasks: pagers.ListTasksPager = self.get_conn().list_tasks(request=list_tasks_request)
return list(itertools.islice(tasks, limit))
[docs] def wait_for_job(
self, job_name: str, polling_period_seconds: float = 10, timeout: float | None = None
) -> Job:
client = self.get_conn()
while timeout is None or timeout > 0:
try:
job = client.get_job(name=f"{job_name}")
status: JobStatus.State = job.status.state
if (
status == JobStatus.State.SUCCEEDED
or status == JobStatus.State.FAILED
or status == JobStatus.State.DELETION_IN_PROGRESS
):
return job
else:
time.sleep(polling_period_seconds)
except Exception as e:
self.log.exception("Exception occurred while checking for job completion.")
raise e
if timeout is not None:
timeout -= polling_period_seconds
raise AirflowException(f"Job with name [{job_name}] timed out")
[docs] def get_job(self, job_name) -> Job:
return self.get_conn().get_job(name=job_name)
[docs]class CloudBatchAsyncHook(GoogleBaseHook):
"""
Async hook for the Google Cloud Batch service.
:param gcp_conn_id: The connection ID to use when fetching connection info.
:param impersonation_chain: Optional service account to impersonate using short-term
credentials, or chained list of accounts required to get the access_token
of the last account in the list, which will be impersonated in the request.
If set as a string, the account must grant the originating account
the Service Account Token Creator IAM role.
If set as a sequence, the identities from the list must grant
Service Account Token Creator IAM role to the directly preceding identity, with first
account from the list granting this role to the originating account.
"""
def __init__(
self,
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
):
self._client: BatchServiceAsyncClient | None = None
super().__init__(gcp_conn_id=gcp_conn_id, impersonation_chain=impersonation_chain)
[docs] def get_conn(self):
if self._client is None:
self._client = BatchServiceAsyncClient(
credentials=self.get_credentials(), client_info=CLIENT_INFO
)
return self._client
[docs] async def get_batch_job(
self,
job_name: str,
) -> Job:
client = self.get_conn()
return await client.get_job(name=f"{job_name}")