SQL performance of a large number of sum()s - mysql

Question

Within my J2EE web application, I need to generate a bar chart representing the percentage of users in the system with specific alerts. (EDIT - I forgot to mention, the graph only deals with alerts associated with the first situationof each user, thus the min(date) ).
A simplified (but structurally similar) version of my database schema is as follows :
users { id, name }
situations { id, user_id, date }
alerts { id, situation_id, alertA, alertB }
where users to situations are 1-n, and situations to alerts are 1-1.
I've omitted datatypes but the alerts (alertA and B) are booleans. In my actual case, there are many such alerts (30-ish).
So far, this is what I have come up with :
select sum(alerts.alertA), sum(alerts.alertB)
form alerts, (
select id, min(date)
from situations
group by user_id) as situations
where situations.id = alerts.situation_id;
and then divide these sums by
select count(users.id) from users;
This seems far from ideal.
Your recommendations/advice as to how to improve as query would be most appreciated (or maybe I need to re-think my database schema)...
Thanks,
Anthony
PS. I was also thinking of using a trigger to refresh a chart specific table whenever the alerts table is updated but I guess that's a subject for a different query (if it turns out to be problematic).

Answer 1

At first, think about your schema again. You will have a lot of different alerts and you probably don't want to add a single column for every one of those.
Consider changing your alerts table to something like { id, situation_id, type, value } where type would be (A,B,C,....) and value would be your boolean.
Your task to calculate the percentages would then split up into:
(1) Count the total number of users:
SELECT COUNT(id) AS total FROM users
(2) Find the "first" situation for each user:
SELECT situations.id, situations.user_id
-- selects the minimum date for every user_id
FROM (SELECT user_id, MIN(date) AS min_date
FROM situations
GROUP BY user_id) AS first_situation
-- gets the situations.id for user with minimum date
JOIN situations ON
first_situation.user_id = situations.user_id AND
first_situation.min_date = situations.date
-- limits number of situations per user to 1 (possible min_date duplicates)
GROUP BY user_id
(3) Count users for whom an alert is set in at least one of the situations in the subquery:
SELECT
alerts.type,
COUNT(situations.user_id)
FROM ( ... situations.user_id, situations.id ... ) AS situations
JOIN alerts ON
situations.id = alerts.situation_id
WHERE
alerts.value = 1
GROUP BY
alerts.type
Put those three steps together to get something like:
SELECT
alerts.type,
COUNT(situations.user_id)/users.total
FROM (SELECT situations.id, situations.user_id
FROM (SELECT user_id, MIN(date) AS min_date
FROM situations
GROUP BY user_id) AS first_situation
JOIN situations ON
first_situation.user_id = situations.user_id AND
first_situation.min_date = situations.date
GROUP BY user_id
) AS situations
JOIN alerts ON
situations.id = alerts.situation_id
JOIN (SELECT COUNT(id) AS total FROM users) AS users
WHERE
alerts.value = 1
GROUP BY
alerts.type
All queries written from my head without testing. Even if they don't work exactly like that, you should still get the idea!