Match group of variables and values with the nearest datetime - google-bigquery

Question

I have a transaction table that looks like that:
transaction_start store_no item_no amount post_voided
2021-03-01 10:00:00 001 101 45 N
2021-03-01 10:00:00 001 105 25 N
2021-03-01 10:00:00 001 109 40 N
2021-03-01 10:05:00 002 103 35 N
2021-03-01 10:05:00 002 135 20 N
2021-03-01 10:08:00 001 140 2 N
2021-03-01 10:11:00 001 101 -45 Y
2021-03-01 10:11:00 001 105 -25 Y
2021-03-01 10:11:00 001 109 -40 Y
The table does not have an id column; the transaction_start for a given store_no will never be the same.
Whenever a transaction is post voided, the transaction is then repeated with the same store_no, item_no but with a negative/minus amount and an equal or higher transaction_start. Also, the column post_voided is then equal to 'Y'.
In the example above, the rows 1-3 have the same transaction_start and store_no, thus belonging to the same receipt, containing three different items (101, 105, 109). The same logic is applied to the other rows: rows 4-5 belong to a same receipt, and so on. In the example, 4 different receipts can be seen. The last receipt, given by the last three rows, is a post voided of the first receipt (rows 1-3).
What I want to do is to change the transaction_start for the post_voided = 'Y' transactions (in my example, only one receipt - represented by the last three rows - has it) to the next/closest datetime of a similar receipt that has the variables store_no, item_no and (negative) amount (but post_voided = 'N') (in my example, the similar ticket is given by the first three rows - store_no, all item_no and (positive) amount match). The transaction_start for the post voided receipt is always equal or higher than the "original" receipt.
Desired output:
transaction_start store_no item_no amount post_voided
2021-03-01 10:00:00 001 101 45 N
2021-03-01 10:00:00 001 105 25 N
2021-03-01 10:00:00 001 109 40 N
2021-03-01 10:05:00 002 103 35 N
2021-03-01 10:05:00 002 135 20 N
2021-03-01 10:08:00 001 140 2 N
2021-03-01 10:00:00 001 101 -45 Y
2021-03-01 10:00:00 001 105 -25 Y
2021-03-01 10:00:00 001 109 -40 Y
Here a link of the table: https://dbfiddle.uk/?rdbms=sqlserver_2019&fiddle=26142fa24e46acb4213b96c86f4eb94b
Thanks in advance!

Answer 1

Consider below
select a.* replace(ifnull(b.transaction_start, a.transaction_start) as transaction_start)
from `project.dataset.table` a
left join (
select * replace(-amount as amount)
from `project.dataset.table`
where post_voided = 'N'
) b
using (store_no, item_no)
if applied to sample data in your question - output is
Consider below for new / extended example (https://dbfiddle.uk/?rdbms=sqlserver_2019&fiddle=91f9f180fd672e7c357aa48d18ced5fd)
select x.* replace(ifnull(y.original_transaction_start, x.transaction_start) as transaction_start)
from `project.dataset.table` x
left join (
select b.transaction_start, b.store_no, b.item_no, b.amount amount,
max(a.transaction_start) original_transaction_start
from `project.dataset.table` a
join `project.dataset.table` b
on a.store_no = b.store_no
and a.item_no = b.item_no
and a.amount = -b.amount
and a.post_voided = 'N'
and b.post_voided = 'Y'
and a.transaction_start < b.transaction_start
group by b.transaction_start, b.store_no, b.item_no, b.amount
) y
using (store_no, item_no, amount, transaction_start)
with output