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#ask-ai
Title
# ask-ai
p

Paul Herzog

03/04/2024, 2:41 PM
@Scout Im using dbt cloud and dagster managed serverless. i want to load one dbt model with load_assets_from_dbt_project. how to?
s

Scout

03/04/2024, 2:41 PM
To load a dbt model as a Dagster asset when using dbt Cloud and Dagster managed serverless, you would typically follow these steps: 1. Connect to dbt Cloud: You need to set up a connection to your dbt Cloud account. This involves configuring a
DbtCloudClientResource
with your dbt Cloud account details, including the account ID and an API access token. 2. Load dbt Models as Assets: Use the
load_assets_from_dbt_cloud_job
function to load your dbt models as Dagster assets. This function will take the dbt Cloud client resource and the job ID of the dbt Cloud job that you want to load assets from. Here's a general example of how you might set this up:
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python from dagster import Definitions from dagster_dbt import DbtCloudClientResource, load_assets_from_dbt_cloud_job  # Configure the dbt Cloud client resource with your account details dbt_cloud_instance = DbtCloudClientResource(     auth_token="your_dbt_cloud_auth_token",     account_id="your_dbt_cloud_account_id" )  # Load dbt models as Dagster assets from a specific dbt Cloud job dbt_cloud_assets = load_assets_from_dbt_cloud_job(     dbt_cloud=dbt_cloud_instance,     job_id=your_dbt_cloud_job_id, )  # Define your Dagster assets defs = Definitions(     assets=[dbt_cloud_assets] )
Please replace
"your_dbt_cloud_auth_token"
,
"your_dbt_cloud_account_id"
, and
your_dbt_cloud_job_id
with your actual dbt Cloud API token, account ID, and the job ID that contains the dbt model you want to load. 3. Materialize Assets: Once you have defined your assets, you can materialize them using Dagster's UI or CLI commands. This will trigger the execution of the dbt Cloud job and materialize the dbt models as assets in Dagster. Please note that the above code is a general guide. You may need to adjust it based on your specific setup and requirements. If you encounter any issues or need further customization, you should refer to the [Dagster documentation](https://docs.dagster.io/integrations/dbt) for more detailed instructions and examples.
p

Paul Herzog

03/04/2024, 2:53 PM
@Scout ive done everything for cloud CLI but when i dbt compile locally it says: 145234 Running with dbt=1.7.9 145234 Encountered an error: Runtime Error Could not find profile named 'default' why?
s

Scout

03/04/2024, 2:53 PM
The error message you're encountering indicates that
dbt
is unable to find a profile named 'default' in your
profiles.yml
file. This file is where
dbt
looks for connection configurations for your target databases. Here are a few steps you can take to troubleshoot this issue: 1. Check
profiles.yml
Location
: By default,
dbt
expects the
profiles.yml
file to be located in the
~/.dbt/
directory on your local machine. Ensure that your
profiles.yml
file is in the correct location. 2. Verify Profile Name: Open your
profiles.yml
file and check that there is a profile named 'default'. If not, either add a profile with that name or use the name of an existing profile in your
dbt
commands. 3. Use the
--profile
Flag
: If you want to use a profile with a different name, you can specify it when running
dbt
commands using the
--profile
flag. For example:
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bash    dbt compile --profile your_profile_name
4. Set
DBT_PROFILES_DIR
Environment Variable
: If your
profiles.yml
file is not in the default location, you can set the
DBT_PROFILES_DIR
environment variable to tell
dbt
where to find it. For example:
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bash    export DBT_PROFILES_DIR=/path/to/your/dbt/profiles
5. Check for Syntax Errors: Ensure that your
profiles.yml
file is correctly formatted and free of syntax errors.
dbt
uses YAML syntax, so even small mistakes like indentation can cause issues. 6. Environment Variables: If your
profiles.yml
file uses environment variables, make sure they are set in your local environment. If you've gone through these steps and are still encountering issues, you may want to refer to the
dbt
documentation or seek support from the
dbt
community for further assistance. It's also worth noting that if you're using
dbt
with Dagster, you'll need to ensure that Dagster's resources are configured to use the correct
dbt
profile when executing
dbt
commands.
p

Paul Herzog

03/04/2024, 2:54 PM
but when using dbt cloud i dont need profiles.yml @Scout
s

Scout

03/04/2024, 2:54 PM
You are correct; when using dbt Cloud, you typically do not need a
profiles.yml
file because dbt Cloud handles the connection configurations for you. If you are using dbt Cloud and still seeing an error related to the
profiles.yml
file when running
dbt compile
locally, it might be due to one of the following reasons: 1. Local Development: If you are running
dbt
commands locally for development purposes,
dbt
still expects a
profiles.yml
file unless you are using the
dbt Cloud IDE
. If you need to run
dbt
commands locally, you will have to create a
profiles.yml
file with the necessary connection details for your local development environment. 2. CI/CD Pipelines: If you are setting up CI/CD pipelines that use
dbt
commands, you might need to provide a
profiles.yml
file or configure environment variables so that
dbt
knows how to connect to your data warehouse. 3. Misconfiguration: There might be a misconfiguration in your local setup or environment that is causing
dbt
to look for a
profiles.yml
file. Ensure that your local environment is set up correctly for integration with dbt Cloud. If you are only using dbt Cloud and not running any
dbt
commands locally, you should not need a
profiles.yml
file. In this case, you can use the dbt Cloud API or the dbt Cloud UI to run your dbt jobs without needing to compile locally. If you are trying to integrate dbt Cloud with Dagster and you are encountering issues, please ensure that you are following the correct procedures for integration as per the documentation. If the issue persists, you may need to reach out to dbt Cloud support or the Dagster community for further assistance.
p

Paul Herzog

03/04/2024, 2:55 PM
If you need to run
dbt
commands locally, you will have to create a
profiles.yml
file with the necessary connection details for your local development environment. give me example on how to do so @Scout
s

Scout

03/04/2024, 2:55 PM
To run
dbt
commands locally, you need to create a
profiles.yml
file that contains the connection details for your target database. This file is typically located in the
~/.dbt/
directory on your machine. Here's an example of how to create and format a
profiles.yml
file for a PostgreSQL database: 1. Create the
profiles.yml
File
: If it doesn't already exist, create a new file named
profiles.yml
in the
~/.dbt/
directory. 2. Add Connection Details: Open the
profiles.yml
file in a text editor and add the connection details for your database. Here's an example configuration for a PostgreSQL database:
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yaml my_profile: # This is the profile name that dbt will use   target: dev # This is the target environment name   outputs:     dev: # The name of the target, can be anything you choose       type: postgres # The type of database       host: localhost # The host of your database       user: my_user # The username for the database       pass: my_password # The password for the database       port: 5432 # The port where the database is accessible       dbname: my_db # The name of the database to connect to       schema: my_schema # The default schema dbt will use       threads: 1 # The number of threads dbt will use
3. Save the File: Save the
profiles.yml
file with the correct connection details. 4. Use the Profile in dbt Commands: When running
dbt
commands, you can now specify the profile to use. If you named your profile
my_profile
, you would run commands like this:
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bash dbt run --profile my_profile
If you do not specify the
--profile
flag, dbt will look for a profile named
default
. Please replace
my_user
,
my_password
,
my_db
, and
my_schema
with your actual PostgreSQL database credentials. The
threads
parameter is optional and specifies how many threads dbt will use to run models in parallel. Remember to keep your
profiles.yml
file secure, especially if it contains sensitive information like database passwords. Do not commit this file to version control if your repository is public or shared with others who should not have access to these credentials.
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