PR review workflows for dbt changes - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to run dbt tests after a pull request is created.

dbt

steps:
  - name: Run dbt tests
    run: dbt [1]

Drag options to blanks, or click blank then click option'

Atest

Bcompile

Crun

Dbuild

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'run' instead of 'test' will execute models but not run tests.

Using 'build' compiles and runs models but does not run tests.

The dbt test command runs tests on your models to check data quality after changes.

2fill in blank

medium

Complete the code to trigger dbt run only on changed models in the PR.

dbt

steps:
  - name: Run changed models
    run: dbt run --models [1]

Drag options to blanks, or click blank then click option'

Achanged

Bstate:modified

Csource:updated

Dtag:changed

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'state:modified' requires state comparison setup.

Using 'tag:changed' is invalid as 'changed' is not a tag.

The --models changed selector runs only models changed in the current git diff.

3fill in blank

hard

Fix the error in the GitHub Actions step to cache dbt dependencies.

dbt

steps:
  - name: Cache dbt deps
    uses: actions/cache@v3
    with:
      path: ~/.dbt[1]
      key: ${{ runner.os }}-dbt-deps-[2]

Drag options to blanks, or click blank then click option'

A/packages ${{ hashFiles('**/packages.yml') }}

B/deps ${{ hashFiles('**/packages.yml') }}

C/deps ${{ hashFiles('**/dbt_project.yml') }}

D/packages ${{ hashFiles('**/dbt_project.yml') }}

Attempts:

3 left

💡 Hint

Common Mistakes

Using '/packages' instead of '/deps' for the path.

Hashing 'dbt_project.yml' instead of 'packages.yml' for the cache key.

The dbt dependencies are stored in ~/.dbt/deps. The cache key should hash packages.yml to detect changes.

4fill in blank

hard

Fill both blanks to create a job that runs dbt seed and then dbt run.

dbt

jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Install dependencies
        run: pip install dbt
      - name: Seed data
        run: dbt [1]
      - name: Run models
        run: dbt [2]

Drag options to blanks, or click blank then click option'

Aseed

Brun

Ctest

Dcompile

Attempts:

3 left

💡 Hint

Common Mistakes

Running 'dbt run' before 'dbt seed' may cause missing data errors.

Using 'dbt test' instead of 'dbt seed' to load data.

dbt seed loads CSV seed files into the database. dbt run runs the models.

5fill in blank

hard

Fill all three blanks to create a workflow that installs dbt, caches dependencies, and runs tests.

dbt

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Cache dbt deps
        uses: actions/cache@v3
        with:
          path: ~/.dbt/[1]
          key: ${{ runner.os }}-dbt-deps-[2]
      - name: Install dbt
        run: pip install [3]
      - name: Run tests
        run: dbt test

Drag options to blanks, or click blank then click option'

Adeps

B${{ hashFiles('**/packages.yml') }}

Cdbt

Dpackages

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'packages' instead of 'deps' for the cache path.

Hashing 'dbt_project.yml' instead of 'packages.yml'.

Installing 'dbt-core' instead of 'dbt' (depending on adapter).

The dependencies folder is deps. The cache key hashes packages.yml. The package to install is dbt.

Practice

1. What is the main purpose of using a PR (Pull Request) review workflow in dbt projects?

easy

A. To ensure changes are reviewed and tested before merging

B. To speed up merging without checks

C. To delete old branches automatically

D. To create new dbt models without review

Solution

1. Step 1: Understand PR review workflow purpose

   PR review workflows are designed to check code changes carefully before they become part of the main project.

2. Step 2: Identify the correct purpose in dbt context

   In dbt, this means reviewing and testing data models to avoid errors and keep the project reliable.

3. Final Answer:

   To ensure changes are reviewed and tested before merging -> Option A

4. Quick Check:

   PR review = review and test before merge [OK]

Hint: PR reviews catch errors before merging [OK]

Common Mistakes:

• Thinking PRs speed up merging without checks
• Confusing PR reviews with branch deletion
• Assuming PRs create models automatically

2. Which of the following is the correct syntax to create a new branch for a dbt PR workflow using Git?

easy

A. git branch new-feature

B. git merge new-feature

C. git push new-feature

D. git checkout -b new-feature

Solution

1. Step 1: Understand Git branch creation commands

   To create and switch to a new branch in one step, use git checkout -b branch-name.

2. Step 2: Identify the correct command for new branch creation

   git checkout -b new-feature uses git checkout -b new-feature, which creates and switches to the branch.

3. Final Answer:

   git checkout -b new-feature -> Option D

4. Quick Check:

   New branch creation = git checkout -b [OK]

Hint: Use git checkout -b to create and switch branch [OK]

Common Mistakes:

• Using git branch without switching
• Confusing merge with branch creation
• Trying to push before creating branch

3. Given this simplified dbt test command in a PR workflow:

dbt test --models my_model

What will happen if the model my_model has a failing test?

medium

A. The command deletes the model automatically

B. The command completes successfully with no error

C. The command fails and returns a non-zero exit code

D. The command ignores the test and continues

Solution

1. Step 1: Understand dbt test behavior

   When a dbt test fails, the command returns a non-zero exit code indicating failure.

2. Step 2: Identify the effect of a failing test in PR workflow

   This failure stops the PR from merging until the issue is fixed.

3. Final Answer:

   The command fails and returns a non-zero exit code -> Option C

4. Quick Check:

   Failing test = command fails with error code [OK]

Hint: Failing dbt tests cause command to fail [OK]

Common Mistakes:

• Assuming tests pass silently
• Thinking dbt deletes models on failure
• Believing tests are ignored automatically

4. You wrote a dbt model and created a PR, but the automated tests fail. Which of the following is the best way to debug the issue?

medium

A. Ignore the test failures and merge the PR

B. Check the test logs and fix the model SQL accordingly

C. Delete the model file and close the PR

D. Merge the PR and fix errors later in production

Solution

1. Step 1: Understand the role of test logs in debugging

   Test logs show which tests failed and why, helping identify SQL errors or data issues.

2. Step 2: Choose the correct debugging approach

   Fixing the model SQL based on logs ensures the PR passes tests before merging.

3. Final Answer:

   Check the test logs and fix the model SQL accordingly -> Option B

4. Quick Check:

   Debug by reviewing logs and fixing code [OK]

Hint: Use test logs to find and fix errors [OK]

Common Mistakes:

• Ignoring test failures
• Deleting models unnecessarily
• Merging broken code into main branch

5. In a team using dbt with PR review workflows, which combination of practices best ensures data model quality before merging?

hard

A. Create feature branches, run automated tests, and require team approval

B. Directly commit to main branch and run tests after merging

C. Skip tests and rely on manual checks only

D. Merge PRs without reviews to speed up deployment

Solution

1. Step 1: Identify best practices in PR workflows

   Using feature branches isolates changes, automated tests catch errors early, and team approval ensures quality review.

2. Step 2: Compare options to find the best combination

   Create feature branches, run automated tests, and require team approval includes all these practices, while others skip important steps or risk errors.

3. Final Answer:

   Create feature branches, run automated tests, and require team approval -> Option A

4. Quick Check:

   Branch + tests + review = quality assurance [OK]

Hint: Combine branches, tests, and reviews for quality [OK]

Common Mistakes:

• Committing directly to main branch
• Skipping automated tests
• Merging without team review