If you want to produce a single set of rows by combining two datasets with compatible columns, which operator is used?

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Multiple Choice

If you want to produce a single set of rows by combining two datasets with compatible columns, which operator is used?

Stacking rows from two datasets that share the same columns is done with the union operation. Union takes all the rows from both sources and produces a single dataset with the same column structure, effectively appending one set of rows after the other. By default, it returns distinct rows, so you get a single, deduplicated set of rows; if you need to keep duplicates, you’d use union all. This is different from joins, which combine rows by matching values and typically produce more columns; a cross join creates every possible pair of rows (a Cartesian product); and an outer join brings in unmatched rows with nulls where there’s no match. So for creating one consolidated set of rows from two datasets with compatible columns, union is the appropriate choice.

Stacking rows from two datasets that share the same columns is done with the union operation. Union takes all the rows from both sources and produces a single dataset with the same column structure, effectively appending one set of rows after the other. By default, it returns distinct rows, so you get a single, deduplicated set of rows; if you need to keep duplicates, you’d use union all.

This is different from joins, which combine rows by matching values and typically produce more columns; a cross join creates every possible pair of rows (a Cartesian product); and an outer join brings in unmatched rows with nulls where there’s no match. So for creating one consolidated set of rows from two datasets with compatible columns, union is the appropriate choice.

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