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Implementing Data Engineering Solutions Using Azure Databricks

Topic 1

Question 78

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A data engineering team of six developers is adopting Azure Databricks Git folders to version-control their notebooks and Python files against a shared GitHub repository. They want to follow Databricks' recommended collaboration best practices so that developers do not interfere with each other's work and so that beginners avoid rewriting shared history. The team lead proposes a workflow and asks you to validate it. Which set of practices aligns with Databricks' documented recommendations for collaborating in Git folders?

  • AAll six developers clone the repository into a single shared Git folder and take turns committing; for combining branches, they always use `git rebase` because it produces a linear history.
  • BEach developer creates their own Git folder mapped to the repository under their user folder, works on their own development branch, and for beginners uses **merge** rather than **rebase** to combine branches because merge does not require force-pushing or rewriting commit history.
  • CDevelopers commit directly to the `main` branch from their Git folders, relying on pull-with-conflict-resolution to reconcile everyone's simultaneous changes at push time.
  • DEach developer uses a personal Git folder, but all developers commit to a single shared feature branch and resolve conflicts by always selecting **Take all incoming changes** to avoid manual review.