< Scout> Im using dbt cloud and dagster managed serverless i dagster #ask-ai

<@U0667DNC02Y> Im using dbt cloud and dagster mana...

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?

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.

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?

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.

Paul Herzog

03/04/2024, 2:54 PM

but when using dbt cloud i dont need profiles.yml @Scout

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.

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

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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