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tvalentyn merged 2 commits into from
Sep 7, 2023
Merged

Edit for clarity #28360

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Edit for clarity
tvalentyn Sep 7, 2023
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Update python-pipeline-dependencies.md
tvalentyn Sep 7, 2023
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3 changes: 2 additions & 1 deletion website/www/site/content/en/documentation/sdks/python-pipeline-dependencies.md
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Expand Up @@ -224,8 +224,9 @@ Use a constraint file to ensure that Beam dependencies in the launch environment

The launch environment translates the pipeline graph into a [runner-independent representation](https://github.com/apache/beam/blob/master/model/pipeline/src/main/proto/org/apache/beam/model/pipeline/v1/beam_runner_api.proto). This process involves serializing (or pickling) the code of the transforms. The serialized content is deserialized on the workers. If the runtime worker environment significantly differs from the launch environment, runtime errors might occur for the following reasons:

* The Apache Beam version must match in the submission and runtime environments. Python major.minor versions must match as well. Otherwise, the pipeline might fail with errors like `Pipeline construction environment and pipeline runtime environment are not compatible`. On older SDK versions, the error might be reported as `SystemError: unknown opcode`.
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@AnandInguva AnandInguva Sep 7, 2023 •
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IIRC, if python versions are not same, dataflow used to fail with dill errors. Is this the one dill output as error?

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@tvalentyn tvalentyn Sep 7, 2023

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we now have a better error,

beam/sdks/python/apache_beam/runners/worker/bundle_processor.py

Line 851 in 5bf6fbf

raise RuntimeError(


* Versions of `protobuf` in the submission and runtime environment need to match or be compatible.
The Apache Beam version and the Python major.minor versions must match in the submission and runtime environments. Otherwise, the pipeline might fail with errors like `Pipeline construction environment and pipeline runtime environment are not compatible`. On older SDK versions, the error might be reported as `SystemError: unknown opcode`.

* Libraries used in the pipeline code might need to match. If serialized pipeline code has references to functions or modules that aren’t available on the workers, the pipeline might fail with `ModuleNotFound` or `AttributeError` exceptions on the remote runner. If you encounter such errors, make sure that the affected libraries are available on the remote worker, and check whether you need to [save the main session]( https://beam.apache.org/documentation/sdks/python-pipeline-dependencies/#pickling-and-managing-the-main-session).

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