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"""This module contains Google Cloud Bigtable sensor."""
from typing import Optional, Sequence, Union

import google.api_core.exceptions
from import ClusterState
from import enums

from import BigtableHook
from import BigtableValidationMixin
from airflow.sensors.base import BaseSensorOperator

[docs]class BigtableTableReplicationCompletedSensor(BaseSensorOperator, BigtableValidationMixin): """ Sensor that waits for Cloud Bigtable table to be fully replicated to its clusters. No exception will be raised if the instance or the table does not exist. For more details about cluster states for a table, have a look at the reference: .. seealso:: For more information on how to use this operator, take a look at the guide: :ref:`howto/operator:BigtableTableReplicationCompletedSensor` :type instance_id: str :param instance_id: The ID of the Cloud Bigtable instance. :type table_id: str :param table_id: The ID of the table to check replication status. :type project_id: str :param project_id: Optional, the ID of the Google Cloud project. :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). :type impersonation_chain: Union[str, Sequence[str]] """
[docs] REQUIRED_ATTRIBUTES = ('instance_id', 'table_id')
[docs] template_fields = [ 'project_id', 'instance_id', 'table_id', 'impersonation_chain',
] def __init__( self, *, instance_id: str, table_id: str, project_id: Optional[str] = None, gcp_conn_id: str = 'google_cloud_default', impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: self.project_id = project_id self.instance_id = instance_id self.table_id = table_id self.gcp_conn_id = gcp_conn_id self._validate_inputs() self.impersonation_chain = impersonation_chain super().__init__(**kwargs)
[docs] def poke(self, context: dict) -> bool: hook = BigtableHook( gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain, ) instance = hook.get_instance(project_id=self.project_id, instance_id=self.instance_id) if not instance:"Dependency: instance '%s' does not exist.", self.instance_id) return False try: cluster_states = hook.get_cluster_states_for_table(instance=instance, table_id=self.table_id) except google.api_core.exceptions.NotFound: "Dependency: table '%s' does not exist in instance '%s'.", self.table_id, self.instance_id ) return False ready_state = ClusterState(enums.Table.ClusterState.ReplicationState.READY) is_table_replicated = True for cluster_id in cluster_states.keys(): if cluster_states[cluster_id] != ready_state:"Table '%s' is not yet replicated on cluster '%s'.", self.table_id, cluster_id) is_table_replicated = False if not is_table_replicated: return False"Table '%s' is replicated.", self.table_id) return True

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