I am trying to write a postgres query which returns max, min, median, first and last values in a group along with the timestamp column for each aggregate value
Table
Id Timestamp_utc Value
1 2020-11-05 15:36:15.768388 10
1 2020-11-05 15:40:15.768388 20
1 2020-11-05 15:44:15.768388 30
1 2020-11-05 15:45:15.768388. 5
1 2020-11-05 15:59:15.768388 25
1 2020-11-05 16:59:15.768388 25
Expected Result
Id Median Median_Timestamp Min Min_Timestamp Max Max_TimeStamp
1 17.5. 15:44:15.768388 5 2020-11-05 15:45:15.768388 30 2020-11-05 15:44:15.768388
I have this query which groups data doesn't include the timestamp
SELECT Id, time_bucket('60', timestamp_utc) AS bucket,
percentile_cont(0.5) within group (order by value) median_value,
min(value) min_value,
max(value) max_value
FROM rs.MyTable
WHERE id IN ( 1111,123)
AND timestamp_utc Between '2020-11-05 10:00:15.748643' and '2020-11-05 16:35:48.750313'
GROUP BY id, bucket
ORDER BY id, bucket
Is there a way I could get timestamp column as well for the aggregated value like timestamp_utc col data when the value is maximum?
One option uses window functions in a subquery to rank the timestamps by increasing and descending value, then conditional aggregation in the outer query to bring the relevant values
select id, bucket,
percentile_cont(0.5) within group (order by value) median_value,
min(value) min_value,
max(timestamp_utc) filter(where rn_asc = 1) min_timestamp,
max(value) max_value,
max(timestamp_utc) filter(where rn_desc = 1) max_timestamp
from (
select t.*,
row_number() over(partition by id, bucket order by value) rn_asc,
row_number() over(partition by id, bucket order by value desc) rn_desc
from (
select t.*, time_bucket('60', timestamp_utc) as bucket
from rs.mytable t
where
id in (1111,123)
and timestamp_utc between '2020-11-05 10:00:15.748643'::timestamp
and '2020-11-05 16:35:48.750313'::timestamp
) t
) t
group by id, bucket
order by id, bucket
Note that we need to compute the bucket first, and put it in the partition of the window function.