A Lakeflow Job starts with a notebook task, `pick_tables`, which scans operational metadata and computes the exact list of bronze tables that need a rebuild — a different list every night: ```python dbutils.jobs.taskValues.set(key = "tables", value = tables) ``` The next step must run the rebuild notebook once for every table in that list. How should the For each task that follows `pick_tables` be configured?

1. A. Point its Inputs field at the task value reference {{tasks.pick_tables.values.tables}}, so the loop follows the list pick_tables produced ✓ A
2. B. Copy the table names from last night's run into the Inputs field as a static JSON array, and edit the job whenever the list changes 💬 B
3. C. Hardcode a master table list in the job definition, because For each inputs cannot reference values from other tasks 💬 C
4. D. Drop the For each task and use a single notebook task that reads the array from pick_tables and loops over the tables with a Python while loop 💬 D

Reveal answer

Correct answer: Point its Inputs field at the task value reference {{tasks.pick_tables.values.tables}}, so the loop follows the list pick_tables produced

Reference: https://docs.databricks.com/aws/en/jobs/tasks/for-each