SQL to find related rows in Loop in ANSI SQL or Snowflake SQL - sql

Question

I have a requirement where I need to link all related CUSTOMER ID and assign a Unified Cust ID to all the related Cust_id.
Ex: for below data,
INPUT DATA
PK_ID CUST_ID_1 CUST_ID_2 CUST_ID_3
1 123 456 567
2 898 567 780
3 999 780 111
4 111 222 333
Based on CUST_ID_1/CUST_ID_2/CUST_ID_3 need to link all the and assign a Unified ID to all the rows.
OUTPUT DATA
Unified ID CUST_ID_1 CUST_ID_2 CUST_ID_3
1000 123 456 567
1000 898 567 780
1000 999 780 111
1000 111 222 333
Trying to perform Self Join but it cannot be definite. Is there a function or ANSI SQL feature which can help in this?
What i have tried,
CREATE TEMP TBL_TEMP AS(
SELECT A.PK_ID
FROM TBL A
LEFT JOIN TBL B
ON A.CUST_ID_1=B.CUST_ID_1
AND A.PK_ID<>B.PK_ID)
UPDATE TBL
FROM TBL_TEMP
SET UNIFIED_ID=SEQ_UNIF_ID.nextval
WHERE TBL.PK_ID=TBL_TEMP.PK_ID
This update i have to write for each column and multiple times.

Answer 1

If you are ok with gap in sequences then following is what I can come up with as of now.
update cust_temp a
set unified_id = t.unified_id
from
(
select
case
when (select count(*) from cust_temp b
where arrays_overlap(array_construct(a.cust_id_1,a.cust_id_2,a.cust_id_3),
array_construct(b.cust_id_1,b.cust_id_2,b.cust_id_3)))>1 -- match across data-set
then 1000 -- same value for common rows
else
ts.nextval --- using sequence for non-common rows
end unified_id,
a.cust_id_1,a.cust_id_2,a.cust_id_3
from cust_temp a, table(getnextval(SEQ_UNIF_ID)) ts) t
where t.cust_id_1 = a.cust_id_1
and t.cust_id_2 = a.cust_id_2
and t.cust_id_3 = a.cust_id_3;
Updated data-set
select * from cust_temp;
UNIFIED_ID
CUST_ID_1
CUST_ID_2
CUST_ID_3
1000
123
456
567
1000
898
567
780
1000
111
222
333
20000
100
200
300
1000
999
780
111
1000
234
123
901
23000
260
360
460
24000
160
560
760
Original data set -
select * from cust_temp;
UNIFIED_ID
CUST_ID_1
CUST_ID_2
CUST_ID_3
NULL
123
456
567
NULL
898
567
780
NULL
111
222
333
NULL
100
200
300
NULL
999
780
111
NULL
234
123
901
NULL
260
360
460
NULL
160
560
760
Arrays_overlap logic is thanks to #Simeon.
Following procedure can be used -
EXECUTE IMMEDIATE $$
DECLARE
duplicate number;
x number;
BEGIN
duplicate := (select count(cnt) from (select a.unified_id,count(*) cnt from cust_temp a,
cust_temp b
where
arrays_overlap(array_construct(a.cust_id_1,a.cust_id_2,a.cust_id_3),
array_construct(b.cust_id_1,b.cust_id_2,b.cust_id_3))
AND a.cust_id_1 != b.cust_id_1
AND a.cust_id_2 != b.cust_id_2
AND a.cust_id_3 != b.cust_id_3
group by a.unified_id) where cnt>1
);
for x in 1 to duplicate do
update cust_temp a
set a.unified_id = (select min(b.unified_id) uid from cust_temp b
where arrays_overlap(array_construct(a.cust_id_1,a.cust_id_2,a.cust_id_3),
array_construct(b.cust_id_1,b.cust_id_2,b.cust_id_3)));
end for;
END;
$$
;
Which will produce following output dataset -
UNIFIED_ID
CUST_ID_1
CUST_ID_2
CUST_ID_3
1000
100
200
300
2000
123
456
567
2000
898
567
780
2000
111
222
333
2000
999
780
111
2000
234
123
901
7000
260
360
460
8000
160
560
760
8000
186
160
766
For an input data-set as -
UNIFIED_ID
CUST_ID_1
CUST_ID_2
CUST_ID_3
1000
100
200
300
2000
123
456
567
3000
898
567
780
4000
111
222
333
5000
999
780
111
6000
234
123
901
7000
260
360
460
8000
160
560
760
9000
186
160
766