dbt source not being found in dbt run

2 min read 05-10-2024

Dbt "Source Not Found" Error: A Troubleshooting Guide

Ever encountered the dreaded "Source not found" error while running your dbt models? This frustrating issue can stem from various factors, leaving you scratching your head and wondering where your data went. This article delves into the common causes of this error, provides troubleshooting steps, and equips you with the knowledge to resolve this issue efficiently.

The Scenario:

Imagine this - you're diligently working on your dbt project, confident in your data pipeline, only to be met with the dreaded "Source not found" error message when you run dbt run. This error usually arises when dbt cannot locate the source defined in your dbt_project.yml file.

# dbt_project.yml
sources:
  - name: my_source
    database: my_database
    schema: my_schema
    tables:
      - name: my_table
        columns:
          - name: id
            data_type: INT
          - name: name
            data_type: VARCHAR

Unraveling the Mystery:

Here are the most common culprits behind the "Source not found" error:

Incorrect Source Name: The first suspect is a simple typo in your source name within the dbt_project.yml file. Double-check that the name matches the source definition in your dbt_project.yml.
Missing Source Configuration: Ensure that the source configuration is complete. The dbt_project.yml file requires the source name, database, schema, and tables to be accurately defined. This information guides dbt to the correct location of your source data.
Case Sensitivity: Database systems are often case-sensitive. Verify that the source name, database name, and schema name are consistently cased in your dbt_project.yml and your database.
Database Connection Issues: A broken connection to your database can also trigger this error. Ensure your database credentials are correct and the database server is accessible.
Missing Dependencies: Certain dbt packages may have dependencies on specific sources. Make sure the necessary packages are installed and configured correctly.

Troubleshooting Tactics:

Double-check Your Configuration: Start by carefully reviewing the dbt_project.yml file. Ensure the source name, database, schema, and tables are spelled correctly and consistently cased.
Verify Database Connection: Test your database connection using a database client to confirm it's working correctly. Ensure that your database credentials are valid and the server is accessible.
Review Your Dependencies: If you are using dbt packages, verify that the required sources are defined in your dbt_project.yml. Ensure you've installed any necessary dependencies.
Run dbt debug: The dbt debug command is your best friend for troubleshooting. It provides detailed information about your dbt project, including the source definition, database connection, and any relevant errors.
Consult the dbt Docs: The official dbt documentation is an invaluable resource. You can find detailed guides on source configuration, troubleshooting tips, and best practices.

Additional Tips:

Clear Cache: Try clearing your dbt cache using dbt clean to remove any stale configurations.
Test with Simple Models: Create a simple model that references the source in question to isolate the issue.
Use dbt Cloud: dbt Cloud simplifies source configuration and offers a more streamlined experience for managing your dbt projects.

In Conclusion:

While encountering the "Source not found" error can be frustrating, approaching it systematically and understanding the potential causes will equip you to resolve it effectively. By following the troubleshooting steps outlined above, you can confidently navigate this common obstacle and get back to building your dbt models seamlessly. Remember, persistence, documentation, and the power of dbt debug are your allies in conquering any dbt challenge.