[GitHub] [airflow] nuclearpinguin commented on a change in pull request #6725: [AIRFLOW-6157] Support for multiple executors
nuclearpinguin commented on a change in pull request #6725: [AIRFLOW-6157]
Support for multiple executors
URL: https://github.com/apache/airflow/pull/6725#discussion_r353689795
##
File path: airflow/executors/executor_loader.py
##
@@ -31,47 +32,108 @@ class ExecutorLoader:
DASK_EXECUTOR = "DaskExecutor"
KUBERNETES_EXECUTOR = "KubernetesExecutor"
-_default_executor: Optional[BaseExecutor] = None
+_default_executor: Optional[BaseExecutorProtocol] = None
+
+_all_executors: Dict[str, BaseExecutor] = dict()
@classmethod
-def get_default_executor(cls) -> BaseExecutor:
+def get_default_executor(cls) -> BaseExecutorProtocol:
"""Creates a new instance of the configured executor if none exists
and returns it"""
if cls._default_executor is not None:
return cls._default_executor
from airflow.configuration import conf
-executor_name = conf.get('core', 'EXECUTOR')
+main_executor_name = conf.get('core', 'EXECUTOR')
-cls._default_executor = ExecutorLoader._get_executor(executor_name)
+main_executor = cls._get_executor(main_executor_name)
+additional_executor_specs = conf.get('core', "ADDITIONAL_EXECUTORS")
+if additional_executor_specs:
+executor_array = additional_executor_specs.split(' ')
+additional_executors_dict: Dict[str, BaseExecutor] = {}
+for executor_spec in executor_array:
+executor_name, queue_array_string = executor_spec.split(':')
+executor = cls._get_executor(executor_name)
+queue_array = queue_array_string.split(",")
+for queue_name in queue_array:
+additional_executors_dict[queue_name] = executor
+cls._default_executor = MultipleExecutors(
+main_executor=main_executor,
+additional_executors_dict=additional_executors_dict)
+else:
+cls._default_executor = main_executor
from airflow import LoggingMixin
log = LoggingMixin().log
-log.info("Using executor %s", executor_name)
+if additional_executor_specs:
+log.info("Using MultipleExecutor with main executor %s and
additional executors %s",
+ main_executor_name, additional_executor_specs)
+else:
+log.info("Using executor %s", main_executor_name)
return cls._default_executor
+@classmethod
+def get_or_create_executor(cls, executor_name: str,
+ create_executor: Callable[[], BaseExecutor]) ->
BaseExecutor:
+"""Retrieves (and creates if needed) an executor with the name
specified"""
+if executor_name in cls._all_executors:
+return cls._all_executors[executor_name]
+executor = create_executor()
+cls._all_executors[executor_name] = executor
+return executor
+
+@staticmethod
+def create_local_executor() -> BaseExecutor:
+"""Creates LocalExecutor"""
+from airflow.executors.local_executor import LocalExecutor
+return LocalExecutor()
+
@staticmethod
-def _get_executor(executor_name: str) -> BaseExecutor:
+def create_sequential_executor() -> BaseExecutor:
+"""Creates SequentialExecutor"""
+from airflow.executors.sequential_executor import SequentialExecutor
+return SequentialExecutor()
+
+@staticmethod
+def create_celery_executor() -> BaseExecutor:
+"""Creates CeleryExecutor"""
+from airflow.executors.celery_executor import CeleryExecutor
+return CeleryExecutor()
+
+@staticmethod
+def create_dask_executor() -> BaseExecutor:
+"""Creates DaskExecutor"""
+from airflow.executors.dask_executor import DaskExecutor
+return DaskExecutor()
+
+@staticmethod
+def create_kubernetes_executor() -> BaseExecutor:
+"""Creates KubernetesExecutor"""
+from airflow.executors.kubernetes_executor import KubernetesExecutor
+return KubernetesExecutor()
+
+@classmethod
+def _get_executor(cls, executor_name: str) -> BaseExecutor:
"""
Creates a new instance of the named executor.
In case the executor name is unknown in airflow,
-look for it in the plugins
+look for it in the plugins.
"""
if executor_name == ExecutorLoader.LOCAL_EXECUTOR:
-from airflow.executors.local_executor import LocalExecutor
-return LocalExecutor()
+return cls.get_or_create_executor(executor_name=executor_name,
+
create_executor=ExecutorLoader.create_local_executor)
elif executor_name == ExecutorLoader.SEQUENTIAL_EXECUTOR:
-from airflow.executors.sequential_executor import
SequentialExecutor
-return SequentialExecutor()
+return cls.get_or_create_exe
[GitHub] [airflow] nuclearpinguin commented on a change in pull request #6725: [AIRFLOW-6157] Support for multiple executors
nuclearpinguin commented on a change in pull request #6725: [AIRFLOW-6157]
Support for multiple executors
URL: https://github.com/apache/airflow/pull/6725#discussion_r353691352
##
File path: airflow/executors/multiple_executors.py
##
@@ -0,0 +1,117 @@
+#
+# 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.
+"""Multiple executor."""
+from itertools import chain
+from typing import Any, Dict, Iterable, Optional, Set
+
+from airflow.executors.base_executor import BaseExecutor,
BaseExecutorProtocol, CommandType
+from airflow.models import TaskInstance
+from airflow.models.taskinstance import SimpleTaskInstance, TaskInstanceKeyType
+
+
+class MultipleExecutors(BaseExecutorProtocol):
+"""
+This executor can run multiple executors under the hood.
+"""
+def __init__(self, main_executor: BaseExecutor, additional_executors_dict:
Dict[str, BaseExecutor]):
+super().__init__()
+self.main_executor = main_executor
+self.additional_executors_dict = additional_executors_dict
+self.executor_set: Set[BaseExecutor] =
set(additional_executors_dict.values())
+self.executor_set.add(main_executor)
+self.log.info("Multiple executor")
+self.log.info("Main executor %s", str(main_executor))
+self.log.info("Additional executor dict %s",
str(self.additional_executors_dict))
+self.log.info("Executor set %s", str(self.executor_set))
+
+def _get_executor_for_queue(self, queue: Optional[str]) -> BaseExecutor:
+executor = None
+if queue:
+executor = self.additional_executors_dict.get(queue)
+return self.main_executor if not executor else executor
+
+def start(self):
+for executor in self.executor_set:
+executor.start()
+
+def has_task(self, task_instance: TaskInstance) -> bool:
+executor = self._get_executor_for_queue(task_instance.queue)
+return executor.has_task(task_instance=task_instance)
+
+def sync(self) -> None:
+for executor in self.executor_set:
+executor.sync()
Review comment:
I just wonder if we should use try / except in such loops? Because now when
first executor fails everything fails. But using exception handling we can
"execute as much as possible" and then throw an exception. WDYT?
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