TobKed commented on a change in pull request #12814: URL: https://github.com/apache/airflow/pull/12814#discussion_r537742145
########## File path: airflow/providers/apache/beam/operators/beam.py ########## @@ -0,0 +1,407 @@ +# +# 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. +"""This module contains Apache Beam operators.""" +import copy +import re +from contextlib import ExitStack +from typing import List, Optional + +from airflow.models import BaseOperator +from airflow.providers.apache.beam.hooks.beam import BeamHook +from airflow.providers.google.cloud.hooks.dataflow import DataflowHook +from airflow.providers.google.cloud.hooks.gcs import GCSHook +from airflow.utils.decorators import apply_defaults +from airflow.version import version + + +class BeamRunPythonPipelineOperator(BaseOperator): + """ + Launching Apache Beam pipelines written in Python. Note that both + ``default_pipeline_options`` and ``pipeline_options`` will be merged to specify pipeline + execution parameter, and ``default_pipeline_options`` is expected to save + high-level options, for instances, project and zone information, which + apply to all beam operators in the DAG. + + .. code-block:: python + + default_args = { + 'default_pipeline_options': + { + 'labels': 'example-label' + } + } + + with models.DAG( + "example_beam_native_python", + default_args=default_args, + start_date=days_ago(1), + schedule_interval=None, + tags=['example'], + ) as dag_native_python: + + start_python_job_local_direct_runner = BeamRunPythonPipelineOperator( + task_id="start_python_job_local_direct_runner", + runner="DirectRunner", + py_file='apache_beam.examples.wordcount', + py_options=['-m'], + py_requirements=['apache-beam[gcp]==2.21.0'], + py_interpreter='python3', + py_system_site_packages=False, + ) + + .. seealso:: + For more detail on Apache Beam have a look at the reference: + https://beam.apache.org/documentation/ + + :param py_file: Reference to the python Apache Beam pipeline file.py, e.g., + /some/local/file/path/to/your/python/pipeline/file. (templated) + :type py_file: str + :param runner: Runner on which pipeline will be run. By default "DirectRunner" is being used. + See: + https://beam.apache.org/documentation/runners/capability-matrix/ + If you use Dataflow runner check dedicated operator: + :class:`~providers.google.cloud.operators.dataflow.DataflowCreatePythonJobOperator` + :type runner: str + :param py_options: Additional python options, e.g., ["-m", "-v"]. + :type py_options: list[str] + :param default_pipeline_options: Map of default pipeline options. + :type default_pipeline_options: dict + :param pipeline_options: Map of pipeline options.The key must be a dictionary. + The value can contain different types: + + * If the value is None, the single option - ``--key`` (without value) will be added. + * If the value is False, this option will be skipped + * If the value is True, the single option - ``--key`` (without value) will be added. + * If the value is list, the many options will be added for each key. + If the value is ``['A', 'B']`` and the key is ``key`` then the ``--key=A --key-B`` options + will be left + * Other value types will be replaced with the Python textual representation. + + When defining labels (``labels`` option), you can also provide a dictionary. + :type pipeline_options: dict + :param py_interpreter: Python version of the beam pipeline. + If None, this defaults to the python3. + To track python versions supported by beam and related + issues check: https://issues.apache.org/jira/browse/BEAM-1251 + :type py_interpreter: str + :param py_requirements: Additional python package(s) to install. + If a value is passed to this parameter, a new virtual environment has been created with + additional packages installed. + + You could also install the apache_beam package if it is not installed on your system or you want + to use a different version. + :type py_requirements: List[str] + :param py_system_site_packages: Whether to include system_site_packages in your virtualenv. + See virtualenv documentation for more information. + + This option is only relevant if the ``py_requirements`` parameter is not None. + :param project_id: (DataflowRunner) Optional, + the Google Cloud project ID in which to start a job. + If set to None or missing, the default project_id from the Google Cloud connection is used. + :type project_id: str + :param gcp_conn_id: (DataflowRunner) Optional. + The connection ID to use connecting to Google Cloud. + :type gcp_conn_id: str + :param job_name: (DataflowRunner) Optional. + The 'job_name' to use when executing the DataFlow job (templated). + This ends up being set in the pipeline options, so any entry + with key ``'jobName'`` or ``'job_name'`` in ``options`` will be overwritten. + :type job_name: str + :param delegate_to: (DataflowRunner) Optional. + The account to impersonate using domain-wide delegation of authority, + if any. For this to work, the service account making the request must have + domain-wide delegation enabled. + :type delegate_to: str + """ + + template_fields = ["py_file", "runner", "pipeline_options", "default_pipeline_options", "job_name"] + + @apply_defaults + def __init__( + self, + *, + py_file: str, + runner: str = "DirectRunner", + default_pipeline_options: Optional[dict] = None, + pipeline_options: Optional[dict] = None, + py_interpreter: str = "python3", + py_options: Optional[List[str]] = None, + py_requirements: Optional[List[str]] = None, + py_system_site_packages: bool = False, + gcp_conn_id: str = "google_cloud_default", + project_id: Optional[str] = None, + job_name: str = "{{task.task_id}}", + delegate_to: Optional[str] = None, + **kwargs, + ) -> None: + super().__init__(**kwargs) + + self.py_file = py_file + self.runner = runner + self.py_options = py_options or [] + self.default_pipeline_options = default_pipeline_options or {} + self.pipeline_options = pipeline_options or {} + self.pipeline_options.setdefault("labels", {}).update( + {"airflow-version": "v" + version.replace(".", "-").replace("+", "-")} + ) + self.py_interpreter = py_interpreter + self.py_requirements = py_requirements + self.py_system_site_packages = py_system_site_packages + self.gcp_conn_id = gcp_conn_id + self.job_name = job_name + self.project_id = project_id + self.job_id = None + self.delegate_to = delegate_to + self.hook: Optional[DataflowHook] = None + + def execute(self, context): + """Execute the Apache Beam Pipeline.""" + pipeline_options = self.default_pipeline_options.copy() + pipeline_options.update(self.pipeline_options) + # Convert argument names from lowerCamelCase to snake case. + camel_to_snake = lambda name: re.sub(r"[A-Z]", lambda x: "_" + x.group(0).lower(), name) + formatted_pipeline_options = {camel_to_snake(key): pipeline_options[key] for key in pipeline_options} + + with ExitStack() as exit_stack: + if self.py_file.lower().startswith("gs://"): + gcs_hook = GCSHook(self.gcp_conn_id, self.delegate_to) + tmp_gcs_file = exit_stack.enter_context( # pylint: disable=no-member + gcs_hook.provide_file(object_url=self.py_file) + ) + self.py_file = tmp_gcs_file.name + + if self.runner == "DataflowRunner": Review comment: I am not sure did I understand your comment correctly. AFAIK the behavior from user perspective will be the same, just if user wants to use more detaflow specific features available in DataflowOperator will be informed about it. Could you elaborate more? ---------------------------------------------------------------- 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. For queries about this service, please contact Infrastructure at: [email protected]
