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PostgreSQL solution
This query returns each qualifying user’s email and total purchase amount for the full three-month window. It assumes each user_id has one row in users.
WITH monthly_counts AS (
SELECT
user_id,
date_trunc('month', purchase_date)::date AS purchase_month,
COUNT(*) AS purchase_count
FROM purchases
WHERE purchase_date >= DATE '2023-04-01'
AND purchase_date < DATE '2023-07-01'
GROUP BY user_id, date_trunc('month', purchase_date)::date
HAVING COUNT(*) >= 3
), power_users AS (
SELECT user_id
FROM monthly_counts
GROUP BY user_id
HAVING COUNT(*) = 3
)
SELECT
u.user_id,
u.email,
CAST(COALESCE(SUM(p.amount), 0) AS DECIMAL(10, 2)) AS total_amount_spent
FROM power_users pu
JOIN users u ON u.user_id = pu.user_id
JOIN purchases p ON p.user_id = pu.user_id
WHERE p.purchase_date >= DATE '2023-04-01'
AND p.purchase_date < DATE '2023-07-01'
GROUP BY u.user_id, u.email
ORDER BY total_amount_spent DESC, u.user_id ASC;How the two GROUP BY levels work
First level: count purchases per user-month
The first WHERE limits the rows before aggregation to April 1 through June 30, 2023. Grouping on user_id and the month creates one group for each user-month that has purchases. HAVING COUNT(*) >= 3 keeps only months with at least three purchase rows.
COUNT(*) is deliberate: it counts rows even when amount is NULL. COUNT(amount) would ignore those rows and could incorrectly disqualify a user. PostgreSQL documents the order and roles of WHERE, GROUP BY, and HAVING, and distinguishes row counts from non-NULL expression counts in its aggregate-function documentation.
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Second level: require all three months
monthly_counts contains only qualifying user-months. The second grouping makes one group per user, and HAVING COUNT(*) = 3 requires exactly three qualifying month rows. Since the date window contains exactly April, May, and June 2023 and the first grouping produces at most one row per user in each month, three rows means the user met the threshold in every target month. A missing month produces no group and therefore cannot pass this test.
Final level: sum the full period
The final query joins qualifying IDs to purchases again and sums every purchase amount in the date window—not only rows retained as qualifying monthly groups. PostgreSQL’s SUM ignores NULL amounts and returns NULL when there are no non-NULL values; COALESCE(..., 0) makes an all-NULL total display as zero. The cast requests two decimal places. Results are ordered by spending from highest to lowest, then by smaller user_id for ties.
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Date boundaries and grouping details
Use a half-open interval for timestamps
The range >= DATE '2023-04-01' AND < DATE '2023-07-01' includes all times on June 30 when purchase_date is a timestamp. An upper bound of June 30 at midnight can exclude later transactions that day. For a DATE column, an inclusive upper bound of June 30 would work, but the exclusive next-day boundary is consistent and explicit.
Keep the year in the month key
Grouping only by month number can combine April from different years if the data window later expands. The example truncates the date to a year-and-month value before grouping, so April 2023 remains distinct from April in another year.
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Common mistakes and adaptations
- Applying the threshold to the whole quarter:
GROUP BY user_id HAVING COUNT(*) >= 9does not prove that a user made three purchases in each month; the purchases could be concentrated in one month. The first grouping preserves the monthly condition. - Using
COUNT(amount): this omits NULL-valued purchase rows, contrary to the stated rule that each purchase row counts. - Summing only the filtered monthly groups: the qualifying CTE is for determining who qualifies. The final sum needs the complete date-window rows for those users.
- Joining duplicate user records: if
usershas multiple rows for oneuser_id, the join can multiply purchase rows and inflate the sum. Enforce uniqueness or aggregate purchases before joining. - Changing the period:
HAVING COUNT(*) = 3is correct for these three target months. For a different number of required months, update the expected count or explicitly test the required months. - Porting to another database: the example uses PostgreSQL’s
date_truncand cast syntax. Month-extraction and date functions differ by SQL dialect; check the target engine’s syntax rather than copying those expressions unchanged. - Rounding or numeric types:
DECIMAL(10, 2)expresses the requested two-decimal output in PostgreSQL. Confirm the target database’s numeric type and rounding behavior when adapting the query.
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