svetakvsundhar commented on code in PR #17159:
URL: https://github.com/apache/beam/pull/17159#discussion_r870886625
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sdks/python/apache_beam/io/gcp/bigquery.py:
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@@ -2525,6 +2526,12 @@ def _get_pipeline_details(unused_elm):
**self._kwargs))
| _PassThroughThenCleanupTempDatasets(project_to_cleanup_pcoll))
+ def get_pcoll_from_schema(table_schema):
+ pcoll_val = apache_beam.io.gcp.bigquery_schema_tools.\
+ produce_pcoll_with_schema(table_schema)
+ return beam.Map(lambda values: pcoll_val(**values)).with_output_types(
Review Comment:
@TheNeuralBit just to follow up here, it looks like ```rowcoder``` was
indeed the coder being used. I verified that the asserts passed here
https://github.com/svetakvsundhar/beam/blob/bqio/sdks/python/apache_beam/coders/row_coder_test.py#L263,
and they both proved to be using rowcoder.
Are there any other intermediate methods I can run on our ```usertype``` to
verify during the rowcoder ptransform? One thing I noted was that
```usertype``` doesn't have a ```.schema``` property, and that I wasn't able to
verify if the argument of this ptransform is a schema
(```apache_beam.portability.api.schema_pb2.Schema```). Is there an easy way to
verify that the input is indeed of that type?
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