Issue when parsing dbt models
See original GitHub issueHey folks!
I’ve just run ‘dbt2looker’ in my local dbt repo folder, and I receive the following error:
❯ dbt2looker
12:11:54 ERROR Cannot parse model with id: "model.smallpdf.brz_exchange_rates" - is the model file empty?
Failed
The model file itself (pictured below) is not empty, therefore I am not sure what the issue with parsing this model dbt2looker appears to have. It is not materialised as a table or view, it is utilised by dbt as ephemeral - is that of importance when parsing files in the project? I’ve also tried running dbt2looker on a limited subset of dbt models via a tag, the same error appears. Any help is greatly appreciated!
![Screenshot 2022-06-20 at 12 12 22](https://user-images.githubusercontent.com/42939414/174581145-26d0f838-f9e2-495c-9a34-159e62883d4c.png)
Other details:
- on dbt version
dbt 1.0.0
- using dbt-redshift adapter
dbt-redshift@1.0.0
- let me know if anything else is of importance!
Issue Analytics
- State:
- Created a year ago
- Comments:7 (1 by maintainers)
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So yesterday I was modding the code and was able to get past the
- is the model file empty?
error.Since the parser uses the manifest.json file, a node has its materialization in the config object:
If the
DbtNode
changes to:then the
parse_models()
method could be modified to:which should ensure the list of models only contains
DbtModel
instances. This might be overkill as a solution and maybe even not the intended effect but it solve those issues for me. Also make sure todbt build
any models that are resulting in that error before you rundbt docs generate
.@lewisosborne I was running into the same issue, I bypassed it by deleting that ephemeral tag at the top and then re-running
dbt docs generate
and then the subsequentdbt2looker
command. That gets me passed the initial error highlighted here.I am running into a different error afterwards where I am seeing
not supported for conversion from redshift to looker
for all of my data types but maybe we can tackle that one separately.Let me know if my initial suggestion gets you past the issue with the ephemeral model.