Which Join Returns All Rows in Both Tables?
You have a Fabric tenant that contains a lakehouse. You plan to use a visual query to merge two tables. You need to ensure that the query returns all the rows in both tables. Which type of join should you use?
Community Votes
100% of anonymous learners picked answer B. Votes are pick records left by other test-takers — they are not the verified answer.
Community Insight
The question tests knowledge of SQL join types and the common trap is confusing partial outer joins (left/right) with a full outer join that preserves all rows from both sides.
To return all rows from both tables in a Fabric lakehouse visual query, a full outer join is required. This page explains why full outer join is the correct choice over inner, left, or right joins.
Choosing left outer or right outer, which only return all rows from one table, not both.
Community Discussion (6 comments)
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Expert Analysis
Why the Answer Is Correct
A full outer join combines the results of both left and right outer joins. It returns all rows from both the left and right tables, filling missing data with NULLs where there is no match. This directly satisfies the requirement to return all rows in both tables.Why the Other Options Are Wrong
An inner join (A) only returns rows where there is a match in both tables. Left outer (C) and right outer (E) return all rows from only one table and matched rows from the other. Right anti (D) returns only rows from the right table that have no match in the left table.Community Comment Notes
The community strongly agrees on the full outer join, noting it is a fundamental SQL concept. As stilferx noted, "FULL OUTER JOIN. Because - ALL rows, not from left, right,... table(s)", and vernillen added that other joins "wouldn't return all the rows in both tables but exclude some."Official Reference
Exam Strategy
When a question specifies returning all rows from both tables without exclusions, immediately look for 'full outer join'. Eliminate inner and anti joins first, then distinguish between left/right and full.
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