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from airflow.sensors.base_sensor_operator import BaseSensorOperator
from airflow.contrib.hooks.bigquery_hook import BigQueryHook
from airflow.utils.decorators import apply_defaults
[docs]class BigQueryTableSensor(BaseSensorOperator):
"""
Checks for the existence of a table in Google Bigquery.
:param project_id: The Google cloud project in which to look for the table.
The connection supplied to the hook must provide
access to the specified project.
:type project_id: string
:param dataset_id: The name of the dataset in which to look for the table.
storage bucket.
:type dataset_id: string
:param table_id: The name of the table to check the existence of.
:type table_id: string
:param bigquery_conn_id: The connection ID to use when connecting to
Google BigQuery.
:type bigquery_conn_id: string
: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: string
"""
template_fields = ('project_id', 'dataset_id', 'table_id',)
ui_color = '#f0eee4'
@apply_defaults
def __init__(self,
project_id,
dataset_id,
table_id,
bigquery_conn_id='bigquery_default_conn',
delegate_to=None,
*args, **kwargs):
super(BigQueryTableSensor, self).__init__(*args, **kwargs)
self.project_id = project_id
self.dataset_id = dataset_id
self.table_id = table_id
self.bigquery_conn_id = bigquery_conn_id
self.delegate_to = delegate_to
[docs] def poke(self, context):
table_uri = '{0}:{1}.{2}'.format(self.project_id, self.dataset_id, self.table_id)
self.log.info('Sensor checks existence of table: %s', table_uri)
hook = BigQueryHook(
bigquery_conn_id=self.bigquery_conn_id,
delegate_to=self.delegate_to)
return hook.table_exists(self.project_id, self.dataset_id, self.table_id)