If one join works per rep id, don't join next - sql

Question

I am matching two datasets that I imported into a Redshift DB: both are at rep id level.
This is my initial query to match the two datasets:
select *
from #t t
join #t2 t2
on lower(trim(t.unique_id))=lower(trim(t2.unique_id))
or lower(trim(t.email))=lower(trim(t2.email))
or lower(trim(split_part(t.first_name,',',1))||trim(split_part(t.last_name,',',1)))=lower(trim(split_part(t2.first_name,',',1))||trim(split_part(t2.last_name,',',1)))
#t is the source of truth I am matching to, and unique_id is supposedly the universal identifier (though only matches about 60%) for rep id (internal identifier), however, in some cases #t2 table has (incorrectly) multiple unique_ids per rep, and incorrectly multiple emails.
How can I change it so that it is more restrictive, ie. when getting a match by unique_id- dont match next record for that rep, when matching by email- dont match next record for that rep, and lastly join by firstname/lastname.
Thank you!

Answer 1

I think there are a few ways to skin this cat. As one option you could add a rank for each join as a CASE statement, and then pick out the one that has the min rank:
SELECT *
FROM
(
SELECT *,
min(ranktest) OVER (PARTITION BY t1.unique_id) as minrank
FROM
(
select *,
CASE WHEN lower(trim(t.unique_id))=lower(trim(t2.unique_id)) THEN 1
WHEN lower(trim(t.email))=lower(trim(t2.email)) THEN 2
WHEN ower(trim(split_part(t.first_name,',',1))||trim(split_part(t.last_name,',',1)))=lower(trim(split_part(t2.first_name,',',1))||trim(split_part(t2.last_name,',',1))) THEN 3
END as ranktest
from #t t
join #t2 t2
on lower(trim(t.unique_id))=lower(trim(t2.unique_id))
or lower(trim(t.email))=lower(trim(t2.email))
or lower(trim(split_part(t.first_name,',',1))||trim(split_part(t.last_name,',',1)))=lower(trim(split_part(t2.first_name,',',1))||trim(split_part(t2.last_name,',',1)))
) sub1
WHERE ranktest = minrank;
You could also do this by querying twice, once to get your data, and once to get the min(ranktest). It will almost definitely be slower, but.. it's a little prettier:
WITH subquery AS
(
select *,
CASE WHEN lower(trim(t.unique_id))=lower(trim(t2.unique_id)) THEN 1
WHEN lower(trim(t.email))=lower(trim(t2.email)) THEN 2
WHEN ower(trim(split_part(t.first_name,',',1))||trim(split_part(t.last_name,',',1)))=lower(trim(split_part(t2.first_name,',',1))||trim(split_part(t2.last_name,',',1))) THEN 3
END as ranktest
from #t t
join #t2 t2
on lower(trim(t.unique_id))=lower(trim(t2.unique_id))
or lower(trim(t.email))=lower(trim(t2.email))
or lower(trim(split_part(t.first_name,',',1))||trim(split_part(t.last_name,',',1)))=lower(trim(split_part(t2.first_name,',',1))||trim(split_part(t2.last_name,',',1)))
)
SELECT *
FROM subquery t1
WHERE t1.ranktest = (SELECT min(ranktest) FROM subquery WHERE subquery.unique_id = t1.ranktest)
Alternatively, you could run this as a UNION ALL, testing for the join differently each time to avoid repeats and only allowing the top most ranked join through:
select *
from #t t
join #t2 t2
on lower(trim(t.unique_id))=lower(trim(t2.unique_id))
UNION ALL
select *
from #t t
join #t2 t2
on lower(trim(t.unique_id))<>lower(trim(t2.unique_id))
AND lower(trim(t.email))=lower(trim(t2.email))
UNION ALL
select *
FROM #t t
join #t2 t2
ON lower(trim(t.unique_id))<>lower(trim(t2.unique_id))
AND lower(trim(t.email))<>lower(trim(t2.email))
AND lower(trim(split_part(t.first_name,',',1))||trim(split_part(t.last_name,',',1)))=lower(trim(split_part(t2.first_name,',',1))||trim(split_part(t2.last_name,',',1)))