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Posted to commits@airflow.apache.org by GitBox <gi...@apache.org> on 2022/04/25 07:08:59 UTC
[GitHub] [airflow] ephraimbuddy opened a new pull request, #23209: Update doc for DAG file processing
ephraimbuddy opened a new pull request, #23209:
URL: https://github.com/apache/airflow/pull/23209
We can now run the ``DagFileProcessorProcess`` in a separate process and it's not fully documented
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[GitHub] [airflow] ephraimbuddy merged pull request #23209: Update doc for DAG file processing
Posted by GitBox <gi...@apache.org>.
ephraimbuddy merged PR #23209:
URL: https://github.com/apache/airflow/pull/23209
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[GitHub] [airflow] github-actions[bot] commented on pull request #23209: Update doc for DAG file processing
Posted by GitBox <gi...@apache.org>.
github-actions[bot] commented on PR #23209:
URL: https://github.com/apache/airflow/pull/23209#issuecomment-1108355783
The PR is likely ready to be merged. No tests are needed as no important environment files, nor python files were modified by it. However, committers might decide that full test matrix is needed and add the 'full tests needed' label. Then you should rebase it to the latest main or amend the last commit of the PR, and push it with --force-with-lease.
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[GitHub] [airflow] uranusjr commented on a diff in pull request #23209: Update doc for DAG file processing
Posted by GitBox <gi...@apache.org>.
uranusjr commented on code in PR #23209:
URL: https://github.com/apache/airflow/pull/23209#discussion_r857351814
##########
docs/apache-airflow/concepts/dagfile-processing.rst:
##########
@@ -0,0 +1,46 @@
+ .. 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.
+
+DAG File Processing
+-------------------
+
+DAG File Processing refers to the process of turning Python files contained in the DAGs folder into DAG objects that contain tasks to be scheduled.
+
+There are two primary components involved in DAG file processing. The ``DagFileProcessorManager`` is a process executing an infinite loop that determines which files need
+to be processed, and the ``DagFileProcessorProcess`` is a separate process that is started to convert an individual file into one or more DAG objects.
+
+The ``DagFileProcessorManager`` runs user codes. As a result, you can decide to run it as a standalone process in a different host than the scheduler process.
+If you decide to run it as a standalone process, you need to set this configuration: ``AIRFLOW__SCHEDULER__STANDALONE_DAG_PROCESSOR=True`` and
+run the ``airflow dag-processor`` CLI command, otherwise, starting the ``Scheduler`` process will start the ``DagFileProcessorManager``.
+
+.. image:: /img/dag_file_processing_diagram.png
+
+``DagFileProcessorManager`` has the following steps:
+
+1. Check for new files: If the elapsed time since the DAG was last refreshed is > :ref:`config:scheduler__dag_dir_list_interval` then update the file paths list
+2. Exclude recently processed files: Exclude files that have been processed more recently than :ref:`min_file_process_interval<config:scheduler__min_file_process_interval>` and have not been modified
+3. Queue file paths: Add files discovered to the file path queue
+4. Process files: Start a new ``DagFileProcessorProcess`` for each file, up to a maximum of :ref:`config:scheduler__parsing_processes`
+5. Collect results: Collect the result from any finished DAG processors
+6. Log statistics: Print statistics and emit ``dag_processing.total_parse_time``
+
+``DagFileProcessorProcess`` has the following steps:
+
+1. Process file: The entire process must complete within :ref:`dag_file_processor_timeout<config:core__dag_file_processor_timeout>`
+2. Load modules from file: Uses Python imp command, must complete within :ref:`dagbag_import_timeout<config:core__dagbag_import_timeout>`
Review Comment:
This can be potentially confusing since DagGileProcessorProcess does not actually use `imp` (the module is deprecated) but `importlib` instead. We probably don’t need to get into the implementation details too much; it should be enough to simply mention the DAG files are loaded as a Python module. https://docs.python.org/3/glossary.html#term-module
##########
docs/apache-airflow/concepts/dagfile-processing.rst:
##########
@@ -0,0 +1,46 @@
+ .. 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.
+
+DAG File Processing
+-------------------
+
+DAG File Processing refers to the process of turning Python files contained in the DAGs folder into DAG objects that contain tasks to be scheduled.
+
+There are two primary components involved in DAG file processing. The ``DagFileProcessorManager`` is a process executing an infinite loop that determines which files need
+to be processed, and the ``DagFileProcessorProcess`` is a separate process that is started to convert an individual file into one or more DAG objects.
+
+The ``DagFileProcessorManager`` runs user codes. As a result, you can decide to run it as a standalone process in a different host than the scheduler process.
+If you decide to run it as a standalone process, you need to set this configuration: ``AIRFLOW__SCHEDULER__STANDALONE_DAG_PROCESSOR=True`` and
+run the ``airflow dag-processor`` CLI command, otherwise, starting the ``Scheduler`` process will start the ``DagFileProcessorManager``.
Review Comment:
```suggestion
run the ``airflow dag-processor`` CLI command, otherwise, starting the scheduler process (``airflow scheduler``) also starts the ``DagFileProcessorManager``.
```
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