I have two tables, one is called 'users' the other is 'user_activity'.
The 'users' table simply contains the users in the system there is
about 30,000 rows. The 'user_activity' table stores the activities
the user has taken. This table has about 430,000 rows and also
(notably) has a column which tracks the type of activity. 90% of the
table is type 7 which indicates the user logged into the system.
I am trying to write a simple query that returns the last time each
user logged into the system. This is how the query looks at the
moment:
SELECT u.user_id, MAX(ua.activity_date)
FROM pp_users u
LEFT OUTER JOIN user_activity ua ON (u.user_id = ua.user_id AND
ua.user_activity_type_id = 7)
WHERE u.userstatus_id <> 4
AND age(u.joined_date) < interval '30 days'
GROUP BY u.user_id
The above query takes about 5 seconds but I'm wondering how it can be
optimized. When the query is formatted as above it does use an index
on the user_id column of the user_activity table... but the cost is
huge (cost=0.00..1396700.80).
I have tried formatting it another way with a sub-query but it takes
about the same amount to completed:
SELECT u.user_id, ua.last
FROM pp_users u
LEFT OUTER JOIN (SELECT max(activity_date) as last, user_id FROM
user_activity WHERE user_activity_type_id = 7 GROUP BY user_id) as ua
ON (u.user_id = ua.user_id)
WHERE u.userstatus_id <> 4
AND age(u.joined_date) < interval '30 days'
Can anybody offer any pointers on this scenario?
Regards,
Collin
