dbt_project.yml configuration

Introduction

The dbt_project.yml file tells dbt how to run your project. It sets up important details like where your data models live and how to build them.

When you start a new dbt project and need to set its name and version.

When you want to tell dbt where your SQL models and tests are located.

When you want to configure how dbt builds models, like materializations (table, view).

When you want to set project-wide configurations like quoting or target schemas.

When you want to organize your project with folders and specify which files to include.

Syntax

dbt

name: your_project_name
version: '1.0'
config-version: 2

profile: your_profile_name

source-paths: ["models"]
analysis-paths: ["analysis"]
test-paths: ["tests"]

target-path: "target"
clean-targets: ["target", "dbt_modules"]

models:
  your_project_name:
    +materialized: view
    staging:
      +schema: staging
      +materialized: table

The name is your project name and must match your folder name.

Indentation matters because YAML uses spaces to organize settings.

Examples

Basic setup with project name, profile, and models materialized as tables.

dbt

name: sales_analytics
version: '1.0'
config-version: 2

profile: prod_profile

source-paths: ["models"]

models:
  sales_analytics:
    +materialized: table

Different folders have different schemas and materializations.

dbt

models:
  sales_analytics:
    staging:
      +schema: staging
      +materialized: incremental
    marts:
      +schema: marts
      +materialized: view

Sample Program

This dbt_project.yml configures a project named my_dbt_project. It sets the default materialization to view. The staging folder models build as tables in the staging schema. The marts folder models build incrementally in the marts schema.

dbt

name: my_dbt_project
version: '1.0'
config-version: 2

profile: default

source-paths: ["models"]
test-paths: ["tests"]

target-path: "target"
clean-targets: ["target", "dbt_modules"]

models:
  my_dbt_project:
    +materialized: view
    staging:
      +schema: staging
      +materialized: table
    marts:
      +schema: marts
      +materialized: incremental

Important Notes

The dbt_project.yml file must be in your project root folder.

Use two spaces for indentation to avoid YAML errors.

You can override settings for specific folders or models under the models: section.

Summary

dbt_project.yml tells dbt how to run your project.

It sets project name, version, file paths, and model build settings.

Indentation and correct YAML format are important for it to work.

Practice

1. What is the primary purpose of the dbt_project.yml file in a dbt project?

easy

A. To configure project settings like name, version, and model paths

B. To write SQL queries for data transformation

C. To store raw data files for analysis

D. To define user access permissions for the project

Solution

1. Step 1: Understand the role of dbt_project.yml

   This file tells dbt how to run the project by setting configurations.

2. Step 2: Identify what configurations it includes

   It sets project name, version, file paths, and model build settings, not SQL or data files.

3. Final Answer:

   To configure project settings like name, version, and model paths -> Option A

4. Quick Check:

   Project configuration = To configure project settings like name, version, and model paths [OK]

Hint: Remember: dbt_project.yml sets project-wide settings [OK]

Common Mistakes:

• Confusing dbt_project.yml with SQL model files
• Thinking it stores data instead of configurations
• Assuming it manages user permissions

2. Which of the following is the correct YAML syntax to set the project name to "my_dbt_project" in dbt_project.yml?

easy

A. project_name: my_dbt_project

B. project: "my_dbt_project"

C. project-name: my_dbt_project

D. name: my_dbt_project

Solution

1. Step 1: Recall the correct key for project name in dbt_project.yml

   The key to set the project name is name, not project_name or others.

2. Step 2: Check YAML syntax

   YAML uses key: value pairs, so name: my_dbt_project is correct syntax.

3. Final Answer:

   name: my_dbt_project -> Option D

4. Quick Check:

   Project name key = name [OK]

Hint: Use name: to set project name in YAML [OK]

Common Mistakes:

• Using underscores or hyphens incorrectly in key names
• Putting project name under wrong key
• Using quotes unnecessarily or missing them when needed

3. Given this snippet in dbt_project.yml:

models:
  my_project:
    materialized: table
    schema: analytics

What will be the materialization type and schema for models in the my_project namespace?

medium

A. Materialized as views, schema is default

B. Materialized as tables, schema is analytics

C. Materialized as incremental, schema is analytics

D. Materialized as tables, schema is default

Solution

1. Step 1: Read the materialized setting under models.my_project

   The setting materialized: table means models will be built as tables.

2. Step 2: Check the schema setting

   The schema is explicitly set to analytics, so models will be created in that schema.

3. Final Answer:

   Materialized as tables, schema is analytics -> Option B

4. Quick Check:

   Materialized = table, schema = analytics [OK]

Hint: Look for materialized and schema keys under models [OK]

Common Mistakes:

• Assuming default schema when schema is set
• Confusing materialized types like view vs table
• Ignoring indentation that defines scope

4. Identify the error in this dbt_project.yml snippet:

name: my_project
version: 1.0
models:
  my_project:
    materialized: table
    schema analytics

medium

A. Version should be a string, not a number

B. Incorrect indentation for 'models' key

C. Missing colon after 'schema' key

D. Project name should be under 'project' key

Solution

1. Step 1: Check YAML syntax for key-value pairs

   Each key must be followed by a colon and a space before the value. Here, schema analytics misses the colon.

2. Step 2: Verify other parts

   Indentation and version format are correct; project name uses correct key name.

3. Final Answer:

   Missing colon after 'schema' key -> Option C

4. Quick Check:

   YAML key-value needs colon [OK]

Hint: Check every key has a colon and space before value [OK]

Common Mistakes:

• Forgetting colon after keys
• Wrong indentation levels
• Using wrong keys for project name

5. You want to configure your dbt project so that all models in the sales folder are materialized as incremental and use the schema sales_data. Which dbt_project.yml snippet correctly achieves this?

hard

A. models:
sales:
+materialized: incremental
+schema: sales_data

B. models:
sales:
materialized: incremental
schema: sales_data

C. models:
sales:
materialized: incremental
+schema: sales_data

D. models:
sales:
+materialized: incremental
schema: sales_data

Solution

1. Step 1: Understand dbt config syntax for folder-level overrides

   To set configs for all models in a folder, use the '+' prefix before keys.

2. Step 2: Check which options use '+' for both keys

   Both materialized and schema need '+' prefix to apply to all models in sales folder.

3. Final Answer:

   models: sales: +materialized: incremental +schema: sales_data -> Option A

4. Quick Check:

   Folder configs use '+' prefix [OK]

Hint: Use '+' before keys to apply configs to all models in a folder [OK]

Common Mistakes:

• Missing '+' prefix for folder-level configs
• Using '+' on only one key instead of both
• Confusing folder name with project name