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"""This module contains Google BigQuery to Google Cloud Storage operator."""
from typing import TYPE_CHECKING, Dict, List, Optional, Sequence, Union
from airflow.models import BaseOperator
from airflow.providers.google.cloud.hooks.bigquery import BigQueryHook
from airflow.providers.google.cloud.links.bigquery import BigQueryTableLink
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class BigQueryToGCSOperator(BaseOperator):
"""
Transfers a BigQuery table to a Google Cloud Storage bucket.
.. seealso::
For more details about these parameters:
https://cloud.google.com/bigquery/docs/reference/v2/jobs
:param source_project_dataset_table: The dotted
``(<project>.|<project>:)<dataset>.<table>`` BigQuery table to use as the
source data. If ``<project>`` is not included, project will be the project
defined in the connection json. (templated)
:param destination_cloud_storage_uris: The destination Google Cloud
Storage URI (e.g. gs://some-bucket/some-file.txt). (templated) Follows
convention defined here:
https://cloud.google.com/bigquery/exporting-data-from-bigquery#exportingmultiple
:param compression: Type of compression to use.
:param export_format: File format to export.
:param field_delimiter: The delimiter to use when extracting to a CSV.
:param print_header: Whether to print a header for a CSV file extract.
:param gcp_conn_id: (Optional) The connection ID used to connect to Google Cloud.
:param delegate_to: The account to impersonate using domain-wide delegation of authority,
if any. For this to work, the service account making the request must have
domain-wide delegation enabled.
:param labels: a dictionary containing labels for the job/query,
passed to BigQuery
:param location: The location used for the operation.
: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 (templated).
"""
[docs] template_fields: Sequence[str] = (
'source_project_dataset_table',
'destination_cloud_storage_uris',
'labels',
'impersonation_chain',
)
[docs] template_ext: Sequence[str] = ()
def __init__(
self,
*,
source_project_dataset_table: str,
destination_cloud_storage_uris: List[str],
compression: str = 'NONE',
export_format: str = 'CSV',
field_delimiter: str = ',',
print_header: bool = True,
gcp_conn_id: str = 'google_cloud_default',
delegate_to: Optional[str] = None,
labels: Optional[Dict] = None,
location: Optional[str] = None,
impersonation_chain: Optional[Union[str, Sequence[str]]] = None,
**kwargs,
) -> None:
super().__init__(**kwargs)
self.source_project_dataset_table = source_project_dataset_table
self.destination_cloud_storage_uris = destination_cloud_storage_uris
self.compression = compression
self.export_format = export_format
self.field_delimiter = field_delimiter
self.print_header = print_header
self.gcp_conn_id = gcp_conn_id
self.delegate_to = delegate_to
self.labels = labels
self.location = location
self.impersonation_chain = impersonation_chain
[docs] def execute(self, context: 'Context'):
self.log.info(
'Executing extract of %s into: %s',
self.source_project_dataset_table,
self.destination_cloud_storage_uris,
)
hook = BigQueryHook(
gcp_conn_id=self.gcp_conn_id,
delegate_to=self.delegate_to,
location=self.location,
impersonation_chain=self.impersonation_chain,
)
job_id = hook.run_extract(
source_project_dataset_table=self.source_project_dataset_table,
destination_cloud_storage_uris=self.destination_cloud_storage_uris,
compression=self.compression,
export_format=self.export_format,
field_delimiter=self.field_delimiter,
print_header=self.print_header,
labels=self.labels,
)
job = hook.get_job(job_id=job_id).to_api_repr()
conf = job["configuration"]["extract"]["sourceTable"]
dataset_id, project_id, table_id = conf["datasetId"], conf["projectId"], conf["tableId"]
BigQueryTableLink.persist(
context=context,
task_instance=self,
dataset_id=dataset_id,
project_id=project_id,
table_id=table_id,
)
