I am trying to perform a window function on a data-set in Redshift using days an an interval for the preceding rows. Example data:
date ID score
3/1/2017 123 1
3/1/2017 555 1
3/2/2017 123 1
3/3/2017 555 3
3/5/2017 555 2
SQL window function for avg score from the last 3 scores:
select
date,
id,
avg(score) over
(partition by id order by date rows
between preceding 3 and
current row) LAST_3_SCORES_AVG,
from DATASET
Result:
date ID LAST_3_SCORES_AVG
3/1/2017 123 1
3/1/2017 555 1
3/2/2017 123 1
3/3/2017 555 2
3/5/2017 555 2
Problem is that I would like the average score from the last 3 DAYS (moving average) and not the last three tests. I have gone over the Redshift and Postgre Documentation and can't seem to find any way of doing it.
Desired Result:
date ID 3_DAY_AVG
3/1/2017 123 1
3/1/2017 555 1
3/2/2017 123 1
3/3/2017 555 2
3/5/2017 555 2.5
Any direction would be appreciated.
You can use lag()
and explicitly calculate the average.
select t.*,
(score +
(case when lag(date, 1) over (partition by id order by date) >=
date - interval '2 day'
then lag(score, 1) over (partition by id order by date)
else 0
end) +
(case when lag(date, 2) over (partition by id order by date) >=
date - interval '2 day'
then lag(score, 2) over (partition by id order by date)
else 0
end)
)
) /
(1 +
(case when lag(date, 1) over (partition by id order by date) >=
date - interval '2 day'
then 1
else 0
end) +
(case when lag(date, 2) over (partition by id order by date) >=
date - interval '2 day'
then 1
else 0
end)
)
from dataset t;