How to group by similar integer values in Postgres sql? - sql

Question

I have a very simple Database Table where a new entry is inserted everytime a product is scanned (RFID-Scanner).
Scans Table:
ID (PK)
Product_ID (FK)
Created_At
1
1
2023-01-26 10:39:00.0000
2
2
2023-01-26 10:39:02.0000
3
3
2023-01-26 10:39:04.0000
4
4
2023-01-26 10:47:00.0000
My goal is to cluster the product ids by the time they were scanned with a specified tolerance (in seconds), so for example for the entries in my table and a tolerance of 10 seconds, the desired result would be
Product_IDs
{1, 2, 3}
{4}
My first attempt to solve the issue was something like this:
SELECT ARRAY_AGG(DISTINCT Product_ID) FROM scans GROUP BY ROUND(EXTRACT(EPOCH FROM created_at) / 10);
This approach works a little, but in edge cases, when for example one product is scanned at second 19 and another one at seconds 21, it wouldn't be grouped together, although it should.
What is a better, more reliable way to solve this problem?

Answer 1

I will assume that the groups are separated if the time between to rows is more than 10 seconds. For example with test data
create table scans(ID int, Product_ID int, Created_At TimeStamp);
insert into scans values
(1, 1,cast('2023-01-26 10:39:00.000' as TimeStamp))
,(2, 2,cast('2023-01-26 10:39:02.000' as TimeStamp))
,(3, 3,cast('2023-01-26 10:39:11.000' as TimeStamp))
,(4, 4,cast('2023-01-26 10:47:00.000' as TimeStamp))
;
Calculate time difference between current row and preceding. When difference greater than '10 second' - thats new group of scans starts.
with ScansDif as(
select *
,Created_At-lag(Created_At,1,Created_At)over(order by Created_At) dif
from scans
)
,ScansGroup as(
select *
,sum(case when dif>cast('10'||' second' as interval) then 1 else 0 end)
over(order by Created_At rows unbounded preceding) grN
from ScansDif
)
SELECT ARRAY_AGG(DISTINCT Product_ID)
FROM ScansGroup
GROUP BY grn
Group numbers
id
product_id
created_at
dif
grn
1
1
2023-01-26 10:39:00
00:00:00
0
2
2
2023-01-26 10:39:02
00:00:02
0
3
3
2023-01-26 10:39:11
00:00:09
0
4
4
2023-01-26 10:47:00
00:07:56
1
Time difference between first and last row of group 0 is 00:11.
Result
array_agg
{1,2,3}
{4}
Demo