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enable overriding the dataproc project for python models #1365
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Thank you for your pull request! We could not find a changelog entry for this change. For details on how to document a change, see the dbt-bigquery contributing guide. |
@dbt-labs/adapters Hi Team, looking for philosophical comment on this ahead of doing additional testing. Thank you! |
@matt-winkler no philosophical qualms on this approach |
@colin-rogers-dbt to give an idea of how this works - it will override the GCP project used for .py models only. Can you please comment on what other testing would be sufficient to prove this works? I'm not sure writing an integration test is the right approach for this since it involves a GCP project-level override, but open to suggestions on approach if you want to go that direction. This failing example from my local illustrates: 21:51:55 1 of 2 START sql view model dbt_mwinkler_core_dev.view_1 ....................... [RUN] My
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@matt-winkler we should set up another GCP project for us to use here (it's what we do in similar situations in other adapters) and then run a python model with this configuration setting. I can work with you to get another project set up |
resolves #1364
docs dbt-labs/docs.getdbt.com/#
Problem
Currently, dbt-bigquery does not support overriding the execution_project for python models. Adding this will enable users to better balance their compute allocations at scale.
Solution
Includes logic to enable setting a
dataproc_project
configuration. Otherwise just useexecution_project
Checklist