Question at position 57 We can calculate the cumulative sum for each date using the following SQL statement: SELECT t1.date, t1.precip AS 'daily precip', SUM(t2.precip) AS 'cum. precip' FROM rainfall AS t1 INNER JOIN rainfall AS t2 ON t2.date = t1.date GROUP BY t1.date ORDER BY t1.date;TrueFalse

Question

Question at position 57 We can calculate the cumulative sum for each date using the following SQL statement: SELECT t1.date, t1.precip AS 'daily precip', SUM(t2.precip) AS 'cum. precip' FROM rainfall AS t1 INNER JOIN rainfall AS t2 ON t2.date >= t1.date GROUP BY t1.date ORDER BY t1.date;TrueFalse

BlackTom AI · Accepted Answer

The question presents a self-join SQL statement and asks whether it correctly computes a cumulative sum by date.
Option 1 (True): This statement asserts that the given query can calculate the cumulative precipitation. However, the INNER JOIN condition uses t2.date >= t1.date. That comparison pairs each date t1.date with all dates t2.date that are on or after that date, so the SUM(t2.precip) aggregates precipitation from the current date forward to the end, not from the start up to the current date. Consequently, the result labeled as a cumulative sum would actually be a forward-looking total, which is not the standard definition of a cumulative sum up to that date. Moreover, using only t2.date >= t1.date without also constraining t2 to be within the same or earlier period leads to double counting across multiple future rows for each t1.date, depending on how the data is stored. As a result, this option mischaracterizes the query’s effect and its ability to produce a traditional cumulative sum.
Option 2 (False): This statement would be correct if the expectation is a standard cumulative sum up to each date. The provided query uses t2.date >= t1.date, which, as explained, sums precipitation from the current date onward, not up to and including the current date. A correct approach to get a running total up to each date would involve summing precipitation for all dates less than or equal to the current date, for example by joining on t2.date <= t1.date (and grouping by t1.date) or by using a window function like SUM(t1.precip) OVER (ORDER BY t1.date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW). Additionally, depending on the SQL dialect, you might also compute the cumulative sum using a window function directly without a self-join, which would be more efficient and clearer.
Putting these observations together, the statement being evaluated does not compute a proper cumulative sum as typically defined, so the assertion implied by selecting True is incorrect. The reasoning above explains why the True option misleads, and why the False option aligns with the actual behavior of the query.

Question at position 57 We can calculate the cumulative sum for each date using the following SQL statement: SELECT t1.date, t1.precip AS 'daily precip', SUM(t2.precip) AS 'cum. precip' FROM rainfall AS t1 INNER JOIN rainfall AS t2 ON t2.date >= t1.date GROUP BY t1.date ORDER BY t1.date;TrueFalse

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