Source code for airflow.providers.amazon.aws.sensors.glue_catalog_partition

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from __future__ import annotations

from datetime import timedelta
from typing import TYPE_CHECKING, Any, Sequence

from airflow.configuration import conf
from airflow.exceptions import AirflowException
from airflow.providers.amazon.aws.hooks.glue_catalog import GlueCatalogHook
from airflow.providers.amazon.aws.sensors.base_aws import AwsBaseSensor
from airflow.providers.amazon.aws.triggers.glue import GlueCatalogPartitionTrigger
from airflow.providers.amazon.aws.utils import validate_execute_complete_event
from airflow.providers.amazon.aws.utils.mixins import aws_template_fields

if TYPE_CHECKING:
    from airflow.utils.context import Context


[docs]class GlueCatalogPartitionSensor(AwsBaseSensor[GlueCatalogHook]): """ Waits for a partition to show up in AWS Glue Catalog. .. seealso:: For more information on how to use this sensor, take a look at the guide: :ref:`howto/sensor:GlueCatalogPartitionSensor` :param table_name: The name of the table to wait for, supports the dot notation (my_database.my_table) :param expression: The partition clause to wait for. This is passed as is to the AWS Glue Catalog API's get_partitions function, and supports SQL like notation as in ``ds='2015-01-01' AND type='value'`` and comparison operators as in ``"ds>=2015-01-01"``. See https://docs.aws.amazon.com/glue/latest/dg/aws-glue-api-catalog-partitions.html #aws-glue-api-catalog-partitions-GetPartitions :param database_name: The name of the catalog database where the partitions reside. :param poke_interval: Time in seconds that the job should wait in between each tries :param deferrable: If true, then the sensor will wait asynchronously for the partition to show up in the AWS Glue Catalog. (default: False, but can be overridden in config file by setting default_deferrable to True) :param aws_conn_id: The Airflow connection used for AWS credentials. If this is ``None`` or empty then the default boto3 behaviour is used. If running Airflow in a distributed manner and aws_conn_id is None or empty, then default boto3 configuration would be used (and must be maintained on each worker node). :param region_name: AWS region_name. If not specified then the default boto3 behaviour is used. :param verify: Whether or not to verify SSL certificates. See: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html :param botocore_config: Configuration dictionary (key-values) for botocore client. See: https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html """
[docs] aws_hook_class = GlueCatalogHook
[docs] template_fields: Sequence[str] = aws_template_fields( "database_name", "table_name", "expression", )
[docs] ui_color = "#C5CAE9"
def __init__( self, *, table_name: str, expression: str = "ds='{{ ds }}'", database_name: str = "default", poke_interval: int = 60 * 3, deferrable: bool = conf.getboolean("operators", "default_deferrable", fallback=False), **kwargs, ): super().__init__(**kwargs) self.table_name = table_name self.expression = expression self.database_name = database_name self.poke_interval = poke_interval self.deferrable = deferrable
[docs] def execute(self, context: Context) -> Any: if self.deferrable: self.defer( trigger=GlueCatalogPartitionTrigger( database_name=self.database_name, table_name=self.table_name, expression=self.expression, aws_conn_id=self.aws_conn_id, region_name=self.region_name, waiter_delay=int(self.poke_interval), verify=self.verify, botocore_config=self.botocore_config, ), method_name="execute_complete", timeout=timedelta(seconds=self.timeout), ) else: super().execute(context=context)
[docs] def poke(self, context: Context): """Check for existence of the partition in the AWS Glue Catalog table.""" if "." in self.table_name: self.database_name, self.table_name = self.table_name.split(".") self.log.info( "Poking for table %s. %s, expression %s", self.database_name, self.table_name, self.expression ) return self.hook.check_for_partition(self.database_name, self.table_name, self.expression)
[docs] def execute_complete(self, context: Context, event: dict | None = None) -> None: event = validate_execute_complete_event(event) if event["status"] != "success": raise AirflowException(f"Trigger error: event is {event}") self.log.info("Partition exists in the Glue Catalog")

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