DP-750 Certification Practice Question #68

Question

You are designing a multi-task Lakeflow Job with the following four tasks:

- `ingest` — a notebook task that loads raw files into a bronze table.
- `transform` — a notebook task that builds the silver table.
- `validate_quality` — a notebook task that runs data-quality checks and may fail when bad data is detected.
- `cleanup` — a notebook task that must always run to release temporary resources, regardless of whether the upstream tasks succeed, fail, or are skipped.

You configure `cleanup` to depend on `validate_quality`. Which **Run if** dependency condition must you set on the `cleanup` task so that it runs even when `validate_quality` fails or is canceled?

Accepted Answer

The `Run if` condition controls whether a downstream task executes based on the outcome of its dependencies. **All done** runs the task after every dependency has finished, ignoring success or failure — the canonical pattern for cleanup/error-correction tasks. The default **All succeeded** would skip `cleanup` (marking it *Upstream failed*) if `validate_quality` fails; **None failed** also requires no failures; **At least one succeeded** requires a success. Only **All done** guarantees the cleanup runs in every outcome, and Databricks documents that for canceled runs the cancellation propagates while failure-handling tasks still run.

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