jscheffl commented on code in PR #42048: URL: https://github.com/apache/airflow/pull/42048#discussion_r1764016685
########## airflow/providers/edge/executors/edge_executor.py: ########## @@ -0,0 +1,175 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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. + +from __future__ import annotations + +from datetime import datetime, timedelta +from typing import TYPE_CHECKING, Any + +from sqlalchemy import delete + +from airflow.cli.cli_config import GroupCommand +from airflow.configuration import conf +from airflow.executors.base_executor import BaseExecutor +from airflow.models.abstractoperator import DEFAULT_QUEUE +from airflow.models.taskinstance import TaskInstanceState +from airflow.providers.edge.models.edge_job import EdgeJobModel +from airflow.providers.edge.models.edge_logs import EdgeLogsModel +from airflow.providers.edge.models.edge_worker import EdgeWorkerModel +from airflow.utils.db import DBLocks, create_global_lock +from airflow.utils.session import NEW_SESSION, provide_session + +if TYPE_CHECKING: + import argparse + + from sqlalchemy.orm import Session + + from airflow.executors.base_executor import CommandType + from airflow.models.taskinstance import TaskInstance + from airflow.models.taskinstancekey import TaskInstanceKey + +PARALLELISM: int = conf.getint("core", "PARALLELISM") + + +class EdgeExecutor(BaseExecutor): + """Implementation of the EdgeExecutor to distribute work to Edge Workers via HTTP.""" + + def __init__(self, parallelism: int = PARALLELISM): + super().__init__(parallelism=parallelism) + self.last_reported_state: dict[TaskInstanceKey, TaskInstanceState] = {} + + @provide_session + def start(self, session: Session = NEW_SESSION): + """If EdgeExecutor provider is loaded first time, ensure table exists.""" + with create_global_lock(session=session, lock=DBLocks.MIGRATIONS): + engine = session.get_bind().engine + EdgeJobModel.metadata.create_all(engine) + EdgeLogsModel.metadata.create_all(engine) + EdgeWorkerModel.metadata.create_all(engine) + + @provide_session + def execute_async( + self, + key: TaskInstanceKey, + command: CommandType, + queue: str | None = None, + executor_config: Any | None = None, + session: Session = NEW_SESSION, + ) -> None: + """Execute asynchronously.""" + self.validate_airflow_tasks_run_command(command) + session.add( + EdgeJobModel( + dag_id=key.dag_id, + task_id=key.task_id, + run_id=key.run_id, + map_index=key.map_index, + try_number=key.try_number, + state=TaskInstanceState.QUEUED, + queue=queue or DEFAULT_QUEUE, + command=str(command), + ) + ) + + @provide_session + def sync(self, session: Session = NEW_SESSION) -> None: + """Sync will get called periodically by the heartbeat method.""" + jobs: list[EdgeJobModel] = session.query(EdgeJobModel).all() + for job in jobs: + if job.key in self.running: + if job.state == TaskInstanceState.RUNNING: + if ( + job.key not in self.last_reported_state + or self.last_reported_state[job.key] != job.state + ): + self.running_state(job.key) + self.last_reported_state[job.key] = job.state + elif job.state == TaskInstanceState.SUCCESS: + if job.key in self.last_reported_state: + del self.last_reported_state[job.key] + self.success(job.key) + elif job.state == TaskInstanceState.FAILED: + if job.key in self.last_reported_state: + del self.last_reported_state[job.key] + self.fail(job.key) + else: + self.last_reported_state[job.key] = job.state + job_success_purge = conf.getint("edge", "job_success_purge") + job_fail_purge = conf.getint("edge", "job_fail_purge") + if ( + job.state == TaskInstanceState.SUCCESS + and job.last_update_t < (datetime.now() - timedelta(minutes=job_success_purge)).timestamp() + ) or ( + job.state == TaskInstanceState.FAILED + and job.last_update_t < (datetime.now() - timedelta(minutes=job_fail_purge)).timestamp() + ): + if job.key in self.last_reported_state: + del self.last_reported_state[job.key] + session.delete(job) + session.execute( + delete(EdgeLogsModel).where( + EdgeLogsModel.dag_id == job.dag_id, + EdgeLogsModel.run_id == job.run_id, + EdgeLogsModel.task_id == job.task_id, + EdgeLogsModel.map_index == job.map_index, + EdgeLogsModel.try_number == job.try_number, + ) + ) + session.commit() + + def end(self) -> None: + """End the executor.""" + self.log.info("Shutting down EdgeExecutor") Review Comment: I was also thinking about this. From the position of (potentially) multiple scheduler instances and the structure that open jobs are in the DB table... actually all schedulers contribute to the queue of jobs. No scheduler "owns" a job but just distributes them. I understand that a graceful stop is needed for a Local Executor. But in the case of Edge the jobs are running remote. Stopping the scheduler will just end adding new jobs, existing (queued) jobs can continue also after stopping the scheduler. Is it a required interface to wait for all tasks? What if another scheduler is adding more jobs... then the scheduler going to stop would potentially never terminate. Or we need to tag which were the tasks created by this scheduler instance to know when which instance is eligible to "end". For sake of simplicity I thought we can just stop. If you think I need to drain all jobs started, then I would need to add a draining of (remote running) jobs. In my tests stopping the scheduler did not harm the completion (async). Let me know. (I am not an expert on the scheduler interface... (Following the docs in https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/executor/index.html the implementation is optional though) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
