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Databricks Certified Data Analyst Associate · Databricks
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- Correct answer : A — `UNION ALL` keeps every row from both inputs without checking for duplicates, so the matching row count is expected; switching to plain `UNION` removes exact duplicate rows across the combined result. A . This is correct: `UNION ALL` concatenates all rows from both queries with no deduplication step at all, which is exactly why the combined row count equals the sum of the two extracts; switching to `UNION` performs a distinct-style removal of exact duplicate rows. B . This reverses the actual behavior: `UNION ALL` is specifically the variant that skips deduplication, while plain `UNION` is the one that removes duplicate rows, so no bug or workaround is involved here. C . `UNION ALL` performs no internal deduplication logic based on keys or any other columns, so describing the matching row count as coincidental misrepresents how the operator is defined to behave. D . This describes the behavior of plain `UNION`, not `UNION ALL`; the whole reason the combined count matches the sum of the two extracts is that no such column-wise duplicate comparison occurs during the union.