Databricks Certified Machine Learning Associate Practice Mode

Community Discussion

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• Chose D0

  - Correct answer : D — The DataFrame is missing one of the feature table's primary key columns, and `write_table` requires every primary key column to be present so it can determine which rows to update or insert. A . This claim about merge mode is invented: merge mode works the same way regardless of whether the primary key is a single column or a composite key, so restricting composite-key tables to overwrite mode is not an actual constraint of the API. B . Column order in the incoming DataFrame does not matter to `write_table`; it matches columns by name against the feature table's schema, so this is not the reason the call fails. C . Publishing to an online store does not place a lock on offline writes to the feature table, so a prior online sync would not block this `write_table` call. D . Because the feature table's primary key is `(loan_id, as_of_date)`, every write must supply both columns so the client can identify which existing rows to update and which new rows to insert; omitting `as_of_date` leaves the operation unable to resolve the primary key, which is why validation fails.