Reputation: 1144
I want to get the first elements of groups, but the groups must be calculated for each window. I would like to do something like this:
SCHEMA
TABLE |
---|
id |
target |
groups |
capture_date |
event_date |
SELECT
AVG(
FIRST(target) GROUP BY id ORDER BY capture_date DESC WHERE capture_date <= MAX(event_date)
) OVER (
PARTITION BY groups
ORDER BY event_date
RANGE BETWEEN INTERVAL 7 DAYS PRECEDING AND CURRENT ROW
)
FROM table
I want to do this in sql or pyspark, whatever in simpler. Any ideas? Thank you!
Upvotes: 0
Views: 57
Reputation: 5125
Here's a all SQL version but can be re-written in spark/pyspark if needed. I used groupby but you could also run a second window with row_number & where
with raw_averages as ( -- short cut for subquery
SELECT
AVG(
target
) OVER (
PARTITION BY groups
ORDER BY event_date
RANGE BETWEEN INTERVAL 7 DAYS PRECEDING AND CURRENT ROW
) as average,
ID,
capture_date,
event_date
FROM table ),
grouped_result as -- more shortcut for subquery
(SELECT
id,
avg(average) as average, -- the average of the entire group is the same -->math trick
reverse( -- sort descending
array_sort( --sort ascending by first item ( event_date )
arrays_zip( -- create one array of below arrays
collect_list( event_date ), -- collect the grouped items *has to be first to get the ordering you want*
collect_list( capture_date ) -- collect the grouped items
)
)
)[0] as values --getting first will return max (reference first item in array)
from raw_averages
GROUP BY groups, id
-- HAVING values.`0` = values.`1` -- having might work here but I didn't explore it
)
select
groups,
id,
average,
values.`0` as event_date -- awkward syntax because of arrays_zip
values.`1` as capture_date
from
grouped_result
where values.`0` = values.`1`
Upvotes: 1