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apache-airflow-providers-apache-beam¶
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.
Installation¶
You can install this package on top of an existing Airflow 2 installation (see Requirements below)
for the minimum Airflow version supported) via
pip install apache-airflow-providers-apache-beam
Requirements¶
PIP package |
Version required |
|---|---|
|
|
|
|
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 |
|---|---|
|
Downloading official packages¶
You can download officially released packages and verify their checksums and signatures from the Official Apache Download site
The apache-airflow-providers-apache-beam 4.1.0 sdist package (asc, sha512)
The apache-airflow-providers-apache-beam 4.1.0 wheel package (asc, sha512)
Changelog¶
4.1.0¶
This release of provider is only available for Airflow 2.3+ as explained in the Apache Airflow providers support policy.
Misc¶
Move min airflow version to 2.3.0 for all providers (#27196)
Features¶
Add backward compatibility with old versions of Apache Beam (#27263)
4.0.0¶
Breaking changes¶
This release of provider is only available for Airflow 2.2+ as explained in the Apache Airflow providers support policy https://github.com/apache/airflow/blob/main/README.md#support-for-providers
Features¶
Added missing project_id to the wait_for_job (#24020)Support impersonation service account parameter for Dataflow runner (#23961)
Misc¶
chore: Refactoring and Cleaning Apache Providers (#24219)
3.3.0¶
Features¶
Add recipe for BeamRunGoPipelineOperator (#22296)
Bug Fixes¶
Fix mistakenly added install_requires for all providers (#22382)
3.0.0¶
Breaking changes¶
Auto-apply apply_default decorator (#15667)
Warning
Due to apply_default decorator removal, this version of the provider requires Airflow 2.1.0+.
If your Airflow version is < 2.1.0, and you want to install this provider version, first upgrade
Airflow to at least version 2.1.0. Otherwise your Airflow package version will be upgraded
automatically and you will have to manually run airflow upgrade db to complete the migration.
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.