Joins are processed left to right (unless parentheses dictate otherwise). If you LEFT JOIN
(or just JOIN
, similar effect) three groceries to one user you get 3 rows (1 x 3). If you then join 4 fishmarkets for the same user, you get 12 (3 x 4) rows, multiplying the previous count in the result, not adding to it, like you may have hoped for.
Thereby multiplying the visits for groceries and fishmarkets alike.
You can make it work like this:
SELECT u.id
, u.account_balance
, g.grocery_visits
, f.fishmarket_visits
FROM users u
LEFT JOIN (
SELECT user_id, count(*) AS grocery_visits
FROM grocery
GROUP BY user_id
) g ON g.user_id = u.id
LEFT JOIN (
SELECT user_id, count(*) AS fishmarket_visits
FROM fishmarket
GROUP BY user_id
) f ON f.user_id = u.id
ORDER BY u.id;
To get aggregated values for one or few users, correlated subqueries like @Vince provided are just fine. For a whole table or major parts of it, it is (much) more efficient to aggregate the n-tables and join to the result once. This way, we also do not need another GROUP BY
in the outer query.
grocery_visits
and fishmarket_visits
are NULL
for users without any related entries in the respective tables. If you need 0
instead (or any arbitrary number), use COALESCE
in the outer SELECT
:
SELECT u.id
, u.account_balance
, COALESCE(g.grocery_visits , 0) AS grocery_visits
, COALESCE(f.fishmarket_visits, 0) AS fishmarket_visits
FROM ...
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