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from airflow.contrib.hooks.bigquery_hook import BigQueryHook
from airflow.models import BaseOperator
from airflow.utils.decorators import apply_defaults
[docs]class BigQueryToCloudStorageOperator(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)
:type source_project_dataset_table: str
: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
:type destination_cloud_storage_uris: list
:param compression: Type of compression to use.
:type compression: str
:param export_format: File format to export.
:type export_format: str
:param field_delimiter: The delimiter to use when extracting to a CSV.
:type field_delimiter: str
:param print_header: Whether to print a header for a CSV file extract.
:type print_header: bool
:param bigquery_conn_id: reference to a specific BigQuery hook.
:type bigquery_conn_id: str
:param delegate_to: The account to impersonate, if any.
For this to work, the service account making the request must have domain-wide
delegation enabled.
:type delegate_to: str
:param labels: a dictionary containing labels for the job/query,
passed to BigQuery
:type labels: dict
"""
[docs] template_fields = ('source_project_dataset_table',
'destination_cloud_storage_uris', 'labels')
[docs] template_ext = ('.sql',)
@apply_defaults
def __init__(self,
source_project_dataset_table,
destination_cloud_storage_uris,
compression='NONE',
export_format='CSV',
field_delimiter=',',
print_header=True,
bigquery_conn_id='bigquery_default',
delegate_to=None,
labels=None,
*args,
**kwargs):
super(BigQueryToCloudStorageOperator, self).__init__(*args, **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.bigquery_conn_id = bigquery_conn_id
self.delegate_to = delegate_to
self.labels = labels
[docs] def execute(self, context):
self.log.info('Executing extract of %s into: %s',
self.source_project_dataset_table,
self.destination_cloud_storage_uris)
hook = BigQueryHook(bigquery_conn_id=self.bigquery_conn_id,
delegate_to=self.delegate_to)
conn = hook.get_conn()
cursor = conn.cursor()
cursor.run_extract(
self.source_project_dataset_table,
self.destination_cloud_storage_uris,
self.compression,
self.export_format,
self.field_delimiter,
self.print_header,
self.labels)