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When Datahub works with multiple ingestion sources, for example, dbt and bigquery, we found that because bigquery has an option convert_urns_to_lowercase default to False, the result of a table shows in datahub will be duplicated (one lowercased, other preserved).
To Reproduce
Steps to reproduce the behavior:
Go to dbt project and ingest into datahub
Ingest into datahub by bigquery ingestion source
From datahub GUI, click on Datasets, go to the ingested table
See the error (duplicated table name, one lowercased, one preserved)
Expected behavior
dbt ingestion config will have an option like convert_dataset_urns_to_lowercase, allowing users to config the case of dataset urns, seem as #7063.
Desktop (please complete the following information):
OS: (Ubuntu) docker quickstart
Browser: chrome
Datahub Version: 0.10.2
The text was updated successfully, but these errors were encountered:
This issue is stale because it has been open for 30 days with no activity. If you believe this is still an issue on the latest DataHub release please leave a comment with the version that you tested it with. If this is a question/discussion please head to https://slack.datahubproject.io. For feature requests please use https://feature-requests.datahubproject.io
Describe the bug
Follow the issue #7377, dbt ingestion always lowercasing the table identifier for urns:
datahub/metadata-ingestion/src/datahub/ingestion/source/dbt/dbt_common.py
Line 400 in aa388f0
When Datahub works with multiple ingestion sources, for example, dbt and bigquery, we found that because bigquery has an option
convert_urns_to_lowercase
default to False, the result of a table shows in datahub will be duplicated (one lowercased, other preserved).To Reproduce
Steps to reproduce the behavior:
Expected behavior
dbt ingestion config will have an option like
convert_dataset_urns_to_lowercase
, allowing users to config the case of dataset urns, seem as #7063.Desktop (please complete the following information):
The text was updated successfully, but these errors were encountered: