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N020-M1 Tier 2 · Core SQL · medium analytics · Streamhub

Return the user ID and period name for every pro-user-quarter combination

Part of CROSS JOIN in SQL

The problem

Streamhub's growth team wants a quarterly reporting scaffold restricted to pro-tier users — one row per pro user per quarter.

Write a query to return the user ID and period name for every pro-user-quarter combination.

Assumptions:

  • The users table contains every account on the platform; pro-tier users are identified by plan = 'pro'.
  • The periods table contains the calendar windows used for reporting.
  • The user-side condition narrows the result to pro users before they are expanded across periods.

Output:

  • One row per pro-user-quarter combination, with columns user_id and period_name.
Schema · analytics 5 tables
users
id integer
name text
email text
country text
plan text
signed_up_at timestamptz
is_active boolean
conversions
id integer
user_id integer
converted_at timestamptz
plan text
amount numeric
sessions
id integer
user_id integer
started_at timestamptz
ended_at? timestamptz
event_count integer
events
id integer
user_id integer
session_id? integer
event_type text
occurred_at timestamptz
properties? jsonb
periods
id integer
name text
start_month integer
end_month integer
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Solution query
SELECT
  u.id AS user_id,
  p.name AS period_name
FROM
  users u
  CROSS JOIN periods p
WHERE
  u.plan = 'pro'

The shape

WHERE u.plan = 'pro' narrows the users side to pro-tier accounts; CROSS JOIN periods p then expands each surviving user across all four quarters. The result is a pro-cohort × quarter grid — exactly the scaffold the growth team's report builds on.

Clause by clause

  • FROM users u CROSS JOIN periods p produces the full user-by-period cartesian product first. Conceptually, every user is paired with every quarter.
  • WHERE u.plan = 'pro' then keeps only the rows whose user is on the pro plan. Because the filter targets a property of the left side, it effectively trims users down to the pro cohort before that cohort gets paired with periods. PostgreSQL is free to apply the filter early — it doesn't have to materialise the full cross-product and then throw rows away — but the result is the same either way: pro users × every quarter.
  • u.id AS user_id reads the pro user's ID from each paired row.
  • p.name AS period_name reads the quarter label (Q1–Q4) from the periods side.

Why filter on users and not on the joined result

Filtering on u.plan is equivalent to writing the cohort first and then crossing it with periods — both shapes return the same rows. What the WHERE clause cannot do here is filter on a property of the combination (e.g., "only pro users in Q1"), because the cross-product treats every pairing as equally valid by construction. The filter narrows one side of the grid; it doesn't pick specific cells out of it. For "pro users across every quarter," that's the right shape — every surviving pro user gets all four periods.

You practiced restricting one side of a CROSS JOIN with a WHERE condition. The recurring shape any time a cohort × catalogue grid is the foundation of a per-segment report.

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