Provider for Apache Airflow. Implements apache-airflow-providers-apache-beam package
Project description
Package apache-airflow-providers-apache-beam
Release: 3.2.1rc1
Provider package
This is a provider package for apache.beam provider. All classes for this provider package are in airflow.providers.apache.beam python package.
You can find package information and changelog for the provider in the documentation.
Installation
You can install this package on top of an existing Airflow 2.1+ installation via pip install apache-airflow-providers-apache-beam
The package supports the following python versions: 3.7,3.8,3.9,3.10
PIP requirements
PIP package |
Version required |
|---|---|
apache-airflow |
>=2.1.0 |
apache-beam |
>=2.33.0 |
Cross provider package dependencies
Those are dependencies that might be needed in order to use all the features of the package. You need to install the specified provider packages in order to use them.
You can install such cross-provider dependencies when installing from PyPI. For example:
pip install apache-airflow-providers-apache-beam[google]Dependent package |
Extra |
|---|---|
Changelog
3.2.1
Misc
Add Trove classifiers in PyPI (Framework :: Apache Airflow :: Provider)
3.2.0
Features
Add support for BeamGoPipelineOperator (#20386)
Misc
Support for Python 3.10
3.1.0
Features
Use google cloud credentials when executing beam command in subprocess (#18992)
3.0.1
Misc
Optimise connection importing for Airflow 2.2.0
3.0.0
Breaking changes
Auto-apply apply_default decorator (#15667)
2.0.0
Breaking changes
Integration with the google provider
In 2.0.0 version of the provider we’ve changed the way of integrating with the google provider. The previous versions of both providers caused conflicts when trying to install them together using PIP > 20.2.4. The conflict is not detected by PIP 20.2.4 and below but it was there and the version of Google BigQuery python client was not matching on both sides. As the result, when both apache.beam and google provider were installed, some features of the BigQuery operators might not work properly. This was cause by apache-beam client not yet supporting the new google python clients when apache-beam[gcp] extra was used. The apache-beam[gcp] extra is used by Dataflow operators and while they might work with the newer version of the Google BigQuery python client, it is not guaranteed.
This version introduces additional extra requirement for the apache.beam extra of the google provider and symmetrically the additional requirement for the google extra of the apache.beam provider. Both google and apache.beam provider do not use those extras by default, but you can specify them when installing the providers. The consequence of that is that some functionality of the Dataflow operators might not be available.
Unfortunately the only complete solution to the problem is for the apache.beam to migrate to the new (>=2.0.0) Google Python clients.
This is the extra for the google provider:
extras_require = (
{
# ...
"apache.beam": ["apache-airflow-providers-apache-beam", "apache-beam[gcp]"],
# ...
},
)And likewise this is the extra for the apache.beam provider:
extras_require = ({"google": ["apache-airflow-providers-google", "apache-beam[gcp]"]},)You can still run this with PIP version <= 20.2.4 and go back to the previous behaviour:
pip install apache-airflow-providers-google[apache.beam]or
pip install apache-airflow-providers-apache-beam[google]But be aware that some BigQuery operators functionality might not be available in this case.
1.0.1
Bug fixes
Improve Apache Beam operators - refactor operator - common Dataflow logic (#14094)
Corrections in docs and tools after releasing provider RCs (#14082)
Remove WARNINGs from BeamHook (#14554)
1.0.0
Initial version of the provider.
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