Experimental BQ support to run dbt models with `ExecutionMode.AIRFLOW_ASYNC` #1230

pankajastro · 2024-09-29T18:53:25Z

This work has been inspired by the talk "Airflow at Monzo: Evolving our data platform as the bank scales" by @jonathanrainer @ed-sparkes given at Airflow Summit 2023: https://airflowsummit.org/sessions/2023/airflow-at-monzo-evolving-our-data-platform-as-the-bank-scales/.

Enable BQ users to run dbt models (full_refresh) asynchronously. This releases the Airflow worker node from waiting while the transformation (I/O) happens in the dataware house (some of which can take hours, according to customers), increasing the overall Airflow task throughput (more information: https://airflow.apache.org/docs/apache-airflow/stable/authoring-and-scheduling/deferring.html). As part of this change, we introduce the capability of not using the dbt command to run actual SQL transformations. This also avoids creating subprocesses in the worker node (ExecutionMode.LOCAL with InvocationMode. SUBPROCESS and ExecutionMode.VIRTUALENV) or the overhead of creating a Kubernetes Pod to execute the actual dbt command (ExecutionMode.KUBERNETES). This can avoid issues related to memory and CPU usage.

This PR takes advantage of an already implemented async operator in the Airflow repo by extending it in the Cosmos async operator. It also utilizes the pre-compiled SQL generated as part of the PR #1224. It downloads the generated SQL from a remote location (S3/GCS), which allows us to decouple from dbt during task execution.

Details

Expose get_profile_type on ProfileConfig: This aids in database selection
~~Add async_op_args: A high-level parameter to forward arguments to the upstream operator (Airflow operator). (This may change in this PR itself)~~ The async operator params are process as kwargs in the operator_args parameter
Implement DbtRunAirflowAsyncOperator: This initializes the Airflow Operator, retrieves the SQL query at task runtime from a remote location, modifies the query as needed, and triggers the upstream execute method.

Limitations

This feature only works when using Airflow 2.8 and above
The async execution only works for BigQuery
The async execution only supports running dbt models (other dbt resources, such as seeds, sources, snapshots, tests, are run using the ExecutionMode.LOCAL)
This will work only if the user provides sets full_refresh=True in operator_args (which means tables will be dropped before being populated, as implemented in dbt-core)
Users need to use ProfileMapping in ProfileConfig, since Cosmos relies on having the connection (credentials) to be able to run the transformation in BQ without dbt-core
Users must provide the BQ location in operator_args (this is a limitation from the BigQueryInsertJobOperator that is being used to implement the native Airflow asynchronous support)

Testing

We have added a new dbt project to the repository to facilitate asynchronous task execution. The goal is to accelerate development without disrupting or requiring fixes for the existing tests. Also, we have added DAG for end-to-end testing https://github.com/astronomer/astronomer-cosmos/blob/bd6657a29b111510fc34b2baf0bcc0d65ec0e5b9/dev/dags/simple_dag_async.py

Configuration

Users need to configure the below param to execute deferrable tasks in the Cosmos

Example DAG: https://github.com/astronomer/astronomer-cosmos/blob/bd6657a29b111510fc34b2baf0bcc0d65ec0e5b9/dev/dags/simple_dag_async.py

Installation

You can leverage async operator support by installing an additional dependency

astronomer-cosmos[dbt-bigquery, google]

Documentation

The PR also document the limitations and uses of Airflow async execution in the Cosmos.

Related Issue(s)

Related to: #1120
Closes: #1134

Breaking Change?

No

Notes

This is an experimental feature, and as such, it may undergo breaking changes. We encourage users to share their experiences and feedback to improve it further.

We'd love support and feedback so we can define the next steps.

Checklist

I have made corresponding changes to the documentation (if required)
I have added tests that prove my fix is effective or that my feature works

Credits

This was a result of teamwork and effort:

Co-authored-by: Pankaj Koti pankajkoti699@gmail.com
Co-authored-by: Tatiana Al-Chueyr tatiana.alchueyr@gmail.com

Future Work

Design interface to facilitate the easy addition of new asynchronous databases operators [async] Design ExecutionMode.AIRFLOW_ASYNC interface to incorporate additional database #1238
Improve the test coverage [async] Improve test coverage for BigQuery Async task #1239
Address the limitations (we need to log these issues)

Remove print stmt Fix query Fix query Remove oss execute method code

…L from

This PR is the groundwork for the implementation of `ExecutionMode.AIRFLOW_ASYNC` (#1120), which - once all other epic tasks are completed - will enable asynchronous execution of dbt resources using Apache Airflow’s deferrable operators. As part of this work, this PR introduces a new option to the enum `ExecutionMode` : `AIRFLOW_ASYNC`. When this execution mode is used, Cosmos now creates a setup task that will pre-compile the dbt project SQL and make it available to the remaining dbt tasks. This PR, however, does not yet leverage Airflow's deferrable operators. If users use `ExecutionMode.AIRFLOW_ASYNC` they will actually be running `ExecutionMode.LOCAL` operators with this change. The PR (#1230) has a first experimental version of using deferrable operators for task execution. ## Setup task as the ground work for a new Execution Mode: `ExecutionMode.AIRFLOW_ASYNC`: - Adds a new operator, `DbtCompileAirflowAsyncOperator`, as a root task(analogous to a setup task) in the DAG, running the dbt compile command and uploading the compiled SQL files to a remote storage location for subsequent tasks that fetch these compiled SQL files from the remote storage and run them asynchronously using Airflow's deferrable operators. ## Airflow Configurations: - `remote_target_path`: Introduces a configurable path to store dbt-generated files remotely, supporting any storage scheme that works with Airflow’s Object Store (e.g., S3, GCS, Azure Blob). - `remote_target_path_conn_id`: Allows specifying a custom connection ID for the remote target path, defaulting to the scheme’s associated Airflow connection if not set. ## Example DAG for CI Testing: Introduces an example DAG (`simple_dag_async.py`) demonstrating how to use the new execution mode(The execution like mentioned earlier would still run like Execution Mode LOCAL operators at the moment with this PR alone) This DAG is integrated into the CI pipeline to run integration tests and aims at verifying the functionality of the `ExecutionMode.AIRFLOW_ASYNC` as and when implementation gets added starting with the experimental implementation in #1230 . ## Unit & Integration Tests: - Adds comprehensive unit and integration tests to ensure correct behavior. - Tests include validation for successful uploads, error handling for misconfigured remote paths, and scenarios where `remote_target_path` are not set. ## Documentation: - Adds detailed documentation explaining how to configure and set the `ExecutionMode.AIRFLOW_ASYNC`. ## Scope & Limitations of the feature being introduced: 1. This feature is meant to be released as Experimental and is also marked so in the documentation. 2. Currently, it has been scoped for only dbt models to be executed asynchronously (being worked upon in PR #1230), while other resource types would be run synchronously. 3. `BigQuery` will be the only supported target database for this execution mode ((being worked upon in PR #1230). Thus, this PR enhances Cosmos by providing the ground work for more efficient execution of long-running dbt resources ## Additional Notes: - This feature is planned to be introduced in Cosmos v1.7.0. related: #1134

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.github/workflows/test.yml

tatiana · 2024-10-02T11:47:51Z

On the issue:

There are two issues we have to solve before merging this PR

CI is getting stuck when trying to run
tests/test_example_dags.py::test_example_dag[simple_dag_async]

We identified that Cosmos was using its own dag.test that was buggy when used with Airflow deferrable operators. We changed to use Airflow's one if users are using AF >= 2.5 and it seems to have resolved the issue:
16a87ea (CI jobs were no longer stuck)

tatiana

Incredible work, @pankajastro @pankajkoti ! 🎉

To run dbt transformations without dbt while leveraging Airflow asynchronous processing is far from trivial - and this PR is a significant step in the right direction.

codecov · 2024-10-02T14:09:50Z

Codecov Report

Attention: Patch coverage is 89.74359% with 12 lines in your changes missing coverage. Please review.

Project coverage is 95.73%. Comparing base (225d6e9) to head (a0cb147).
Report is 2 commits behind head on main.

Files with missing lines	Patch %	Lines
cosmos/config.py	36.36%	7 Missing ⚠️
cosmos/operators/airflow_async.py	94.04%	5 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1230      +/-   ##
==========================================
- Coverage   95.93%   95.73%   -0.20%     
==========================================
  Files          67       67              
  Lines        3885     3965      +80     
==========================================
+ Hits         3727     3796      +69     
- Misses        158      169      +11

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jlaneve · 2024-10-02T14:10:38Z

I haven't read through the code but this feature looks so awesome - it's something we've been talking about since day 1 so it's incredible to see it come to life!

pankajastro · 2024-10-03T13:05:45Z

Thank you so much, @pankajkoti and @tatiana, for taking this to completion. I truly appreciate your support and hard work 🙏

Following up on the documentation added in PRs #1224 and #1230, this PR refactors the documentation for Async Execution mode, particularly the limitations section. It also addresses a couple of un-rendered items in the scheduling.rst file, caused by missing blank lines after the code-block directive.

@pankajkoti

New Features * Introduction of experimental support to run dbt BQ models using Airflow deferrable operators by @pankajkoti @pankajastro @tatiana in #1224 #1230. This is a first step in this journey and we would really appreciate feedback from the community. For more information, check the documentation: https://astronomer.github.io/astronomer-cosmos/getting_started/execution-modes.html#airflow-async-experimental This work has been inspired by the talk "Airflow at Monzo: Evolving our data platform as the bank scales" by @jonathanrainer @ed-sparkes given at Airflow Summit 2023: https://airflowsummit.org/sessions/2023/airflow-at-monzo-evolving-our-data-platform-as-the-bank-scales/. * Support using ``DatasetAlias`` and fix orphaning unreferenced dataset by @tatiana in #1217 #1240 Documentation: https://astronomer.github.io/astronomer-cosmos/configuration/scheduling.html#data-aware-scheduling * Add GCP_CLOUD_RUN_JOB execution mode by @ags-de #1153 Learn more about it: https://astronomer.github.io/astronomer-cosmos/getting_started/gcp-cloud-run-job.html Enhancements * Create single virtualenv when ``DbtVirtualenvBaseOperator`` has ``virtualenv_dir=None`` and ``is_virtualenv_dir_temporary=True`` by @kesompochy in #1200 * Consistently handle build and imports in ``cosmos/__init__.py`` by @tatiana in #1215 * Add enum constants to init for direct import by @fabiomx in #1184 Bug fixes * URL encode dataset names to support multibyte characters by @t0momi219 in #1198 * Fix invalid argument (``full_refresh``) passed to DbtTestAwsEksOperator (and others) by @johnhoran in #1175 * Fix ``printer_width`` arg type in ``DbtProfileConfigVars`` by @jessicaschueler in #1191 * Fix task owner fallback by @jmaicher in #1195 Docs * Add scarf to readme and docs for website analytics by @cmarteepants in #1221 * Add ``virtualenv_dir`` param to ``ExecutionConfig`` docs by @pankajkoti in #1173 * Give credits to @LennartKloppenburg in CHANGELOG.rst by @tatiana #1174 * Refactor docs for async mode execution by @pankajkoti in #1241 Others * Remove PR branch added for testing a change in CI in #1224 by @pankajkoti in #1233 * Fix CI wrt broken coverage upload artifact @pankajkoti in #1210 * Fix CI issues - Upgrade actions/upload-artifact & actions/download-artifact to v4 and set min version for packaging by @pankajkoti in #1208 * Resolve CI failures for Apache Airflow 2.7 jobs by @pankajkoti in #1182 * CI: Update GCP manifest file path based on new secret update by @pankajkoti in #1237 * Pre-commit hook updates in #1176 #1186, #1186, #1201, #1219, #1231

@pankajkoti

New Features * Introduction of experimental support to run dbt BQ models using Airflow deferrable operators by @pankajkoti @pankajastro @tatiana in #1224 #1230. This is a first step in this journey and we would really appreciate feedback from the community. For more information, check the documentation: https://astronomer.github.io/astronomer-cosmos/getting_started/execution-modes.html#airflow-async-experimental This work has been inspired by the talk "Airflow at Monzo: Evolving our data platform as the bank scales" by @jonathanrainer @ed-sparkes given at Airflow Summit 2023: https://airflowsummit.org/sessions/2023/airflow-at-monzo-evolving-our-data-platform-as-the-bank-scales/. * Support using ``DatasetAlias`` and fix orphaning unreferenced dataset by @tatiana in #1217 #1240 Documentation: https://astronomer.github.io/astronomer-cosmos/configuration/scheduling.html#data-aware-scheduling * Add GCP_CLOUD_RUN_JOB execution mode by @ags-de #1153 Learn more about it: https://astronomer.github.io/astronomer-cosmos/getting_started/gcp-cloud-run-job.html Enhancements * Create single virtualenv when ``DbtVirtualenvBaseOperator`` has ``virtualenv_dir=None`` and ``is_virtualenv_dir_temporary=True`` by @kesompochy in #1200 * Consistently handle build and imports in ``cosmos/__init__.py`` by @tatiana in #1215 * Add enum constants to init for direct import by @fabiomx in #1184 Bug fixes * URL encode dataset names to support multibyte characters by @t0momi219 in #1198 * Fix invalid argument (``full_refresh``) passed to DbtTestAwsEksOperator (and others) by @johnhoran in #1175 * Fix ``printer_width`` arg type in ``DbtProfileConfigVars`` by @jessicaschueler in #1191 * Fix task owner fallback by @jmaicher in #1195 Docs * Add scarf to readme and docs for website analytics by @cmarteepants in #1221 * Add ``virtualenv_dir`` param to ``ExecutionConfig`` docs by @pankajkoti in #1173 * Give credits to @LennartKloppenburg in CHANGELOG.rst by @tatiana #1174 * Refactor docs for async mode execution by @pankajkoti in #1241 Others * Remove PR branch added for testing a change in CI in #1224 by @pankajkoti in #1233 * Fix CI wrt broken coverage upload artifact @pankajkoti in #1210 * Fix CI issues - Upgrade actions/upload-artifact & actions/download-artifact to v4 and set min version for packaging by @pankajkoti in #1208 * Resolve CI failures for Apache Airflow 2.7 jobs by @pankajkoti in #1182 * CI: Update GCP manifest file path based on new secret update by @pankajkoti in #1237 * Pre-commit hook updates in #1176 #1186, #1186, #1201, #1219, #1231

@tatiana

**New Features** * Support using ``DatasetAlias`` and fix orphaning unreferenced dataset by @tatiana in #1217 #1240 Documentation: https://astronomer.github.io/astronomer-cosmos/configuration/scheduling.html#data-aware-scheduling * Add GCP_CLOUD_RUN_JOB execution mode by @ags-de #1153 Learn more about it: https://astronomer.github.io/astronomer-cosmos/getting_started/gcp-cloud-run-job.html * Introduction of experimental support to run dbt BQ models using Airflow deferrable operators by @pankajkoti @pankajastro @tatiana in #1224 #1230. This is the first step in the journey of running dbt resources with native Airflow, and we would appreciate feedback from the community. For more information, check the documentation: https://astronomer.github.io/astronomer-cosmos/getting_started/execution-modes.html#airflow-async-experimental This work has been inspired by the talk "Airflow at Monzo: Evolving our data platform as the bank scales" by @jonathanrainer @ed-sparkes given at Airflow Summit 2023: https://airflowsummit.org/sessions/2023/airflow-at-monzo-evolving-our-data-platform-as-the-bank-scales/. **Enhancements** * Create single virtualenv when ``DbtVirtualenvBaseOperator`` has ``virtualenv_dir=None`` and ``is_virtualenv_dir_temporary=True`` by @kesompochy in #1200 * Consistently handle build and imports in ``cosmos/__init__.py`` by @tatiana in #1215 * Add enum constants to init for direct import by @fabiomx in #1184 **Bug fixes** * URL encode dataset names to support multibyte characters by @t0momi219 in #1198 * Fix invalid argument (``full_refresh``) passed to DbtTestAwsEksOperator (and others) by @johnhoran in #1175 * Fix ``printer_width`` arg type in ``DbtProfileConfigVars`` by @jessicaschueler in #1191 * Fix task owner fallback by @jmaicher in #1195 **Docs** * Add scarf to readme and docs for website analytics by @cmarteepants in #1221 * Add ``virtualenv_dir`` param to ``ExecutionConfig`` docs by @pankajkoti in #1173 * Give credits to @LennartKloppenburg in CHANGELOG.rst by @tatiana #1174 * Refactor docs for async mode execution by @pankajkoti in #1241 Others * Remove PR branch added for testing a change in CI in #1224 by @pankajkoti in #1233 * Fix CI wrt broken coverage upload artifact @pankajkoti in #1210 * Fix CI issues - Upgrade actions/upload-artifact & actions/download-artifact to v4 and set min version for packaging by @pankajkoti in #1208 * Resolve CI failures for Apache Airflow 2.7 jobs by @pankajkoti in #1182 * CI: Update GCP manifest file path based on new secret update by @pankajkoti in #1237 * Pre-commit hook updates in #1176 #1186, #1186, #1201, #1219, #1231 --------- Co-authored-by: Pankaj Koti <pankajkoti699@gmail.com>

tatiana · 2024-10-21T09:30:11Z

I just created a few follow-up tickets:

) Pluggable Async Operator Interface ------------------------------------ This PR enhances the initial async operator support in Cosmos, as introduced in [PR #1230](#1230). The changes decouple the DbtRunAirflowAsyncOperator from BigQueryInsertJobOperator, making it more flexible and allowing support for async operators with other data sources in the future Introducing the DbtRunAirflowAsyncFactoryOperator class, which dynamically selects the parent class containing the async operator implementation based on dbt profile. I’ve added a template for implementing the Databricks async operator. ~ATM moved async operator-related code at path `cosmos/operators/_async/`, but open for suggestion~ After discussing this with the team, I have moved async operator-related code at path `cosmos/operators/_asynchronous/` ## Design principle Introduced the `DbtRunAirflowAsyncFactoryOperator` class that uses a Factory Method design pattern combined with dynamic inheritance at runtime. - **Factory Method:** The `create_async_operator()` method generates a specific async operator class based on the profile_config provided. This allows the operator to adapt to different types of async operator at runtime. - **Dynamic Inheritance:** The class dynamically changes its base class (__bases__) to use the async operator class created in the factory method. This ensures the correct async class is used during execution. - **Execution:** The execute() method calls the `super().execute()` to trigger the execution logic, but it dynamically uses the appropriate operator class for async behavior. ### Class hierarchy ``` BigQueryInsertJobOperator | DbtRunLocalOperator DbtRunAirflowAsyncBigqueryOperator DbtRunAirflowAsyncDatabricksOperator (inject these parent class at runtime) \ / DbtRunFactoryAirflowAsyncOperator | DbtRunAirflowAsyncOperator ``` ## How to add a new async db operator - Implement the operator at the path `cosmos/operators/_asynchronous/` - The operator module should be in the format of: `cosmos.operators._asynchronous.{profile_type}.{dbt_class}{_snake_case_to_camelcase(execution_mode)}{profile_type.capitalize()}Operator` - For details example, I have added a dummy implementation for `Databricks` ## Example DAG ```python import os from datetime import datetime from pathlib import Path from cosmos import DbtDag, ExecutionConfig, ExecutionMode, ProfileConfig, ProjectConfig, RenderConfig from cosmos.profiles import GoogleCloudServiceAccountDictProfileMapping DEFAULT_DBT_ROOT_PATH = Path(__file__).parent / "dbt" DBT_ROOT_PATH = Path(os.getenv("DBT_ROOT_PATH", DEFAULT_DBT_ROOT_PATH)) profile_config = ProfileConfig( profile_name="default", target_name="dev", profile_mapping=GoogleCloudServiceAccountDictProfileMapping( conn_id="gcp_gs_conn", profile_args={"dataset": "release_17", "project": "astronomer-dag-authoring"} ), ) # [START airflow_async_execution_mode_example] simple_dag_async = DbtDag( # dbt/cosmos-specific parameters project_config=ProjectConfig( DBT_ROOT_PATH / "original_jaffle_shop", ), profile_config=profile_config, execution_config=ExecutionConfig( execution_mode=ExecutionMode.AIRFLOW_ASYNC, ), render_config=RenderConfig( select=["path:models"], # test_behavior=TestBehavior.NONE ), # normal dag parameters schedule_interval=None, start_date=datetime(2023, 1, 1), catchup=False, dag_id="simple_dag_async", tags=["simple"], operator_args={"full_refresh": True, "location": "northamerica-northeast1"}, ) # [END airflow_async_execution_mode_example] ``` <img width="1687" alt="Screenshot 2025-01-23 at 3 30 48 PM" src="https://github.com/user-attachments/assets/bd7a13cc-7a52-4d55-947e-23a618b47e68" /> **Graph View** <img width="1688" alt="Screenshot 2025-01-27 at 3 41 14 PM" src="https://github.com/user-attachments/assets/d74a1851-39d9-4575-b9cb-11c286094643" /> closes: #1238 closes: #1239

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Introduce ground work for ExecutionMode.AIRFLOW_ASYNC #1224

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Try upgrading dbt-core & dbt adapters versions to see if the dependencies resolve #1235

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Bump dbt adaptor version for sqlite test #1236

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[async] Design ExecutionMode.AIRFLOW_ASYNC interface to incorporate additional database #1238

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[async] Improve test coverage for BigQuery Async task #1239

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Refactor docs for async mode execution #1241

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[bug] Fix ExecutionMode.AIRFLOW_ASYNC query #1260

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[async] Evaluate the possiblity of using dbt itself to create the full SQL command #1266

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Add structure to support multiple db for async operator execution #1483

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Experimental BQ support to run dbt models with `ExecutionMode.AIRFLOW_ASYNC` #1230

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netlify bot commented Sep 30, 2024 •

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netlify bot commented Sep 30, 2024 •

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codecov bot commented Oct 2, 2024 •

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tatiana commented Oct 21, 2024 •

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