A team maintains a cleaning notebook that takes a table name as a parameter. They want one Lakeflow Job to run this notebook once for each of six bronze tables — sales, orders, returns, customers, products, and suppliers — with at most two iterations running at the same time. Which approach should they use?

1. A. A For each task with a JSON array of the table names as Inputs, a nested notebook using {{input.table}}, and Concurrency 2 ✓ A
2. B. A For each task containing six nested For each tasks, one per table, all sharing a single concurrency setting that the team tunes per run 💬 B
3. C. Six If/else condition tasks, one per table, each branching to the cleaning notebook 💬 C
4. D. One notebook task that loops over the six table names in Python and applies the cleaning logic sequentially 💬 D

Reveal answer

Correct answer: A For each task with a JSON array of the table names as Inputs, a nested notebook using {{input.table}}, and Concurrency 2

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