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Change logical_date back to execution_date, this can be done as anoth…
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105 changes: 105 additions & 0 deletions
105
observatory-platform/observatory/platform/refactor/sensors.py
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| # Copyright 2020, 2021 Curtin University | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
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| # Author: Tuan Chien, Keegan Smith, Jamie Diprose | ||
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| from __future__ import annotations | ||
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| from datetime import timedelta | ||
| from functools import partial | ||
| from typing import Callable, List, Optional | ||
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| import pendulum | ||
| from airflow.models import DagRun | ||
| from airflow.sensors.external_task import ExternalTaskSensor | ||
| from airflow.utils.db import provide_session | ||
| from sqlalchemy.orm.scoping import scoped_session | ||
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| class DagCompleteSensor(ExternalTaskSensor): | ||
| """ | ||
| A sensor that awaits the completion of an external dag by default. Wait functionality can be customised by | ||
| providing a different execution_date_fn. | ||
| The sensor checks for completion of a dag with "external_dag_id" on the logical date returned by the | ||
| execution_date_fn. | ||
| """ | ||
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| def __init__( | ||
| self, | ||
| task_id: str, | ||
| external_dag_id: str, | ||
| mode: str = "reschedule", | ||
| poke_interval: int = 1200, # Check if dag run is ready every 20 minutes | ||
| timeout: int = int(timedelta(days=1).total_seconds()), # Sensor will fail after 1 day of waiting | ||
| check_existence: bool = True, | ||
| execution_date_fn: Optional[Callable] = None, | ||
| **kwargs, | ||
| ): | ||
| """ | ||
| :param task_id: the id of the sensor task to create | ||
| :param external_dag_id: the id of the external dag to check | ||
| :param mode: The mode of the scheduler. Can be reschedule or poke. | ||
| :param poke_interval: how often to check if the external dag run is complete | ||
| :param timeout: how long to check before the sensor fails | ||
| :param check_existence: whether to check that the provided dag_id exists | ||
| :param execution_date_fn: a function that returns the logical date(s) of the external DAG runs to query for, | ||
| since you need a logical date and a DAG ID to find a particular DAG run to wait for. | ||
| """ | ||
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| if execution_date_fn is None: | ||
| execution_date_fn = partial(get_logical_dates, external_dag_id) | ||
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| super().__init__( | ||
| task_id=task_id, | ||
| external_dag_id=external_dag_id, | ||
| mode=mode, | ||
| poke_interval=poke_interval, | ||
| timeout=timeout, | ||
| check_existence=check_existence, | ||
| execution_date_fn=execution_date_fn, | ||
| **kwargs, | ||
| ) | ||
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| @provide_session | ||
| def get_logical_dates( | ||
| external_dag_id: str, logical_date: pendulum.DateTime, session: scoped_session = None, **context | ||
| ) -> List[pendulum.DateTime]: | ||
| """Get the logical dates for a given external dag that fall between and returns its data_interval_start (logical date) | ||
| :param external_dag_id: the DAG ID of the external DAG we are waiting for. | ||
| :param logical_date: the logic date of the waiting DAG. | ||
| :param session: the SQL Alchemy session. | ||
| :param context: the Airflow context. | ||
| :return: the last logical date of the external DAG that falls before the data interval end of the waiting DAG. | ||
| """ | ||
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| data_interval_end = context["data_interval_end"] | ||
| dag_runs = ( | ||
| session.query(DagRun) | ||
| .filter( | ||
| DagRun.dag_id == external_dag_id, | ||
| DagRun.data_interval_end <= data_interval_end, | ||
| ) | ||
| .all() | ||
| ) | ||
| dates = [d.logical_date for d in dag_runs] | ||
| dates.sort(reverse=True) | ||
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| # If more than 1 date return first date | ||
| if len(dates) >= 2: | ||
| dates = [dates[0]] | ||
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| return dates |
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