Source code for airflow.providers.amazon.aws.sensors.glue
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from __future__ import annotations
from functools import cached_property
from typing import TYPE_CHECKING, Sequence
from airflow.exceptions import AirflowException, AirflowSkipException
from airflow.providers.amazon.aws.hooks.glue import GlueJobHook
from airflow.sensors.base import BaseSensorOperator
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class GlueJobSensor(BaseSensorOperator):
"""
Waits for an AWS Glue Job to reach any of the status below.
'FAILED', 'STOPPED', 'SUCCEEDED'
.. seealso::
For more information on how to use this sensor, take a look at the guide:
:ref:`howto/sensor:GlueJobSensor`
:param job_name: The AWS Glue Job unique name
:param run_id: The AWS Glue current running job identifier
:param verbose: If True, more Glue Job Run logs show in the Airflow Task Logs. (default: False)
"""
[docs] template_fields: Sequence[str] = ("job_name", "run_id")
def __init__(
self,
*,
job_name: str,
run_id: str,
verbose: bool = False,
aws_conn_id: str | None = "aws_default",
**kwargs,
):
super().__init__(**kwargs)
self.job_name = job_name
self.run_id = run_id
self.verbose = verbose
self.aws_conn_id = aws_conn_id
self.success_states: list[str] = ["SUCCEEDED"]
self.errored_states: list[str] = ["FAILED", "STOPPED", "TIMEOUT"]
self.next_log_tokens = GlueJobHook.LogContinuationTokens()
@cached_property
[docs] def hook(self):
return GlueJobHook(aws_conn_id=self.aws_conn_id)
[docs] def poke(self, context: Context):
self.log.info("Poking for job run status :for Glue Job %s and ID %s", self.job_name, self.run_id)
job_state = self.hook.get_job_state(job_name=self.job_name, run_id=self.run_id)
try:
if job_state in self.success_states:
self.log.info("Exiting Job %s Run State: %s", self.run_id, job_state)
return True
elif job_state in self.errored_states:
job_error_message = "Exiting Job %s Run State: %s", self.run_id, job_state
self.log.info(job_error_message)
# TODO: remove this if block when min_airflow_version is set to higher than 2.7.1
if self.soft_fail:
raise AirflowSkipException(job_error_message)
raise AirflowException(job_error_message)
else:
return False
finally:
if self.verbose:
self.hook.print_job_logs(
job_name=self.job_name,
run_id=self.run_id,
continuation_tokens=self.next_log_tokens,
)