[CT-3049] [Bug] Unable to override default materialization for python models (dbt >1.4)/Hierarchical Configuration Not Applied

[devmessias]

Is this a new bug in dbt-core?

• I believe this is a new bug in dbt-core
• I have searched the existing issues, and I could not find an existing issue for this bug

Current Behavior

When working within my company's workflow, we outline all configurations, metadata, etc. in the schema.yml file, with broader configurations being described in the dbt_projects.yml. However, the materialization of Python models cannot be controlled through these files. This requires us to set the configuration within the model itself, as demonstrated below:

def model(dbt, session):
    dbt.config(materialization='incremental')
    ...

If this isn't done, the materialization always defaults to 'table' in the generated manifest.json.

commit that introduces this behavior: https://github.com/dbt-labs/dbt-core/blame/48d04e81417195393af5af1f78ef695f3398f193/core/dbt/parser/base.py#L217

Expected Behavior

I would expect that the materialization of Python models could be controlled through these configuration files, just as it is observed with SQL models. Ideally, without having to specify the materialization within the model itself. When defining configurations in these files, they should be respected, and the materialization shouldn't default to 'table' in the generated manifest.json unless explicitly set to do so. The current behavior introduces an inconsistency in the way dbt models are configured and managed.

Steps To Reproduce

1. Ensure you are using dbt version 1.4 or newer.

2. Create a Python model with a materialization setting other than 'table' specified either in dbt_projects.yml or schema.yml.

3. Execute dbt run. Observe in the terminal that the materialization is displayed as 'table'.

4. Upon inspecting the manifest.json, you'll find that all other configurations are respected, except for the materialization which defaults to 'table'.

Relevant log output

No response

Environment

- OS: Ubuntu 20.04.6 LTS
- Python: 3.10.9
- dbt: (tested with multiple versions: 1.4, 1.5, and 1.6.1)

Which database adapter are you using with dbt?

spark, other (mention it in "Additional Context")

Additional Context

database adatpter: dbt-databricks

commit that introduces this behavior: https://github.com/dbt-labs/dbt-core/blame/48d04e81417195393af5af1f78ef695f3398f193/core/dbt/parser/base.py#L217

I've some workarounds to fix this. If this issue is accepted I can send a PR.

[dbeatty10]

Thanks for reporting this @devmessias !

Using the dbt project here as a starting point, I was able to reproduce what you described.

Namely, the manifest showed "materialized": "incremental" when using dbt 1.3.x, but showed table for dbt 1.4.x through 1.6.x.

Here's the customized YAML file that I used:

models/_models.yml

version: 2

models:
  - name: transactions
    config:
      materialized: incremental

Although I didn't try it out for dbt 1.4 though 1.6, I'm assuming we'd see something similar with the following dbt_project.yml:

version: "1.0.0"
config-version: 2
profile: "sandcastle"

models:
  my_project:
    +materialized: incremental

So I agree that this is a bug, and we'd welcome a PR to fix it.

[devmessias]

Hi @dbeatty10 , thank you for the prompt reply. I'll send PR latter with a proposed solution

[devmessias]

PR here #8538 @dbeatty10 . I've tried to create more tests, but I don't know if there is tests that tests hierarchical override in python models.

[devmessias]

Hi @dbeatty10 I'm reaching out regarding the pull request #8538. I understand everyone's likely quite busy to deal with open-source, but I was wondering if there have been any updates or if there is anything more I can do to assist in the review process.

[alex-hsp]

I have just unearthed this myself during my debugging through DBT's source code. Basically, DBT sets a default for python model materialization config here, but it takes precedence overy anything defined in schema file (as stated here). With all amazing developents towards python incremental models, i am surprised this was not found during testing