I believe I followed procedures properly.
Can you assist?
Need more clarification?
Thanks!
bc@16416e89861c:~/workspace$ aws s3 cp $HOME/workspace/dbt_modeling/models/bi_views s3://de-c4w4a2-211125511887-us-east-1-dbt/dbt_project/dbt_modeling/models/bi_views --recursive
The user-provided path /config/workspace/dbt_modeling/models/bi_views does not exist.
Here is 3.2.6
3.2.6. Go to CloudFormation Outputs tab and copy the value of the key DBTBucket. Replace the placeholders <DBTBucket> with it (in two places). Run the commands in the VSCode terminal to copy the new models and dbt_project.yml into the S3 bucket. The Airflow pipelines will point to this bucket when they run dbt as a final step of their processes.
Note: Before you execute the following commands, make sure that inside the dbt_modeling folder (or any of its subfolders) there is no folder named .ipynb_checkpoints. This folder appears when you modify any file by using the Jupyter’s UI. Make sure to delete those checkpoint folders in your local environment and only then execute the commands. You can do it by running the command find . -name .ipynb_checkpoints -exec rm -rf {} \;
aws s3 cp $HOME/workspace/dbt_modeling/models/bi_views s3://<DBTBucket>/dbt_project/dbt_modeling/models/bi_views --recursive
aws s3 cp $HOME/workspace/dbt_modeling/dbt_project.yml s3://<DBTBucket>/dbt_project/dbt_modeling/dbt_project.yml
Hi @Emilio_Carranza,
Did you add this code as instructed:
bi_views:
+materialized: view
+schema: bi_views
edit: I couldn’t reproduce the issue, could you check in step 3.2.1 ./dbt_modelling/models to create the correct bi_views folder. It looks like it needs the correct path, thanks