Swap the seat id of every two consecutive students. If the number of students is odd, the id of the last student is not swapped.
This challenge now meets the current minimum standard for sitemap inclusion and independent indexing.
Swap the seat id of every two consecutive students. If the number of students is odd, the id of the last student is not swapped.
This problem tests conditional row remapping, which comes up in scheduling, seat allocation, and sequence normalization tasks. The real skill is preserving the intended final order while transforming row identities in pairs.
idstudentSELECT
CASE
WHEN id % 2 = 1 AND id <> (SELECT COUNT(*) FROM seat) THEN id + 1
WHEN id % 2 = 1 AND id = (SELECT COUNT(*) FROM seat) THEN id
ELSE id - 1
END AS id,
student
FROM seat
ORDER BY idThis is the standard compact solution. Odd seat IDs normally move forward by one, even IDs move backward by one, and the final odd row stays put when the table has an odd number of seats.
SELECT
CASE
WHEN s1.id % 2 = 1 AND s2.id IS NOT NULL THEN s1.id + 1
WHEN s1.id % 2 = 1 THEN s1.id
ELSE s1.id - 1
END AS id,
s1.student
FROM seat s1
LEFT JOIN seat s2
ON s2.id = s1.id + 1
ORDER BY idThe join version makes the pair relationship more visible by checking whether the next seat exists. It is longer, but it can be easier to explain when you want to reason about the odd-last-row case explicitly.
The easiest bug is forgetting to preserve the last row when the number of seats is odd. If you simply add one to every odd ID and subtract one from every even ID, the final odd seat will point to a seat that does not exist.
Because the question asks for the swapped seat arrangement, not the original physical row order. Ordering by the new id produces the final seating sequence the prompt expects.
Then every odd seat has a matching next seat, so all rows swap cleanly in pairs and no special unchanged row is needed.
Use these guides when you want the fuller explanation behind the SQL pattern this challenge is testing.
Learn how to add conditional logic to your SQL queries using CASE statements. Transform data and categorize results with ease.
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