I have the following table
| id | date | team |
|----|------------|------|
| 1 | 2019-01-05 | A |
| 2 | 2019-01-05 | A |
| 3 | 2019-01-01 | A |
| 4 | 2019-01-04 | B |
| 5 | 2019-01-01 | B |
How can I query the table to receive the most recent values for the teams?
For example, the result for the above table would be ids 1,2,4.
In this case, you can use window functions:
select t.*
from (select t.*, rank() over (partition by team order by date desc) as seqnum
from t
) t
where seqnum = 1;
In some databases a correlated subquery is faster with the right indexes (I haven't tested this with Postgres):
select t.*
from t
where t.date = (select max(t2.date) from t t2 where t2.team = t.team);
And if you wanted only one row per team, then the canonical answer is:
select distinct on (t.team) t.*
from t
order by t.team, t.date desc;
However, that doesn't work in this case because you want all rows from the most recent date.
If your dataset is large, consider the max analytic function in a subquery:
with cte as (
select
id, date, team,
max (date) over (partition by team) as max_date
from t
)
select id
from cte
where date = max_date
Notionally, max is O(n), so it should be pretty efficient. I don't pretend to know the actual implementation on PostgreSQL, but my guess is it's O(n).
One more possibility, generic:
select * from t join (select max(date) date,team from t
group by team) tt
using(date,team)
Window function is the best solution for you.
select id
from (
select team, id, rank() over (partition by team order by date desc) as row_num
from table
) t
where row_num = 1
That query will return this table:
| id |
|----|
| 1 |
| 2 |
| 4 |
If you to get it one row per team, you need to use array_agg function.
select team, array_agg(id) ids
from (
select team, id, rank() over (partition by team order by date desc) as row_num
from table
) t
where row_num = 1
group by team
That query will return this table:
| team | ids |
|------|--------|
| A | [1, 2] |
| B | [4] |
