Redshift SQL Window Function frame_clause with days - sql

Question

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.

Answer 1

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;

Answer 2

The following approach could be used instead of the RANGE window option in a lot of (or all) cases.
You can introduce "expiry" for each of the input records. The expiry record would negate the original one, so when you aggregate all preceding records, only the ones in the desired range will be considered.
AVG is a bit harder as it doesn't have a direct opposite, so we need to think of it as SUM/COUNT and negate both.
SELECT id, date, running_avg_score
FROM
(
SELECT id, date, n,
SUM(score) OVER (PARTITION BY id ORDER BY date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)
/ NULLIF(SUM(n) OVER (PARTITION BY id ORDER BY date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW), 0) as running_avg_score
FROM
(
SELECT date, id, score, 1 as n
FROM DATASET
UNION ALL
-- expiry and negate
SELECT DATEADD(DAY, 3, date), id, -1 * score, -1
FROM DATASET
)
) a
WHERE a.n = 1