I like @erwin-brandstetter 's solution, but wanted to show a solution with the USING
keyword:
DELETE FROM table_with_dups T1
USING table_with_dups T2
WHERE T1.ctid < T2.ctid -- delete the "older" ones
AND T1.name = T2.name -- list columns that define duplicates
AND T1.address = T2.address
AND T1.zipcode = T2.zipcode;
If you want to review the records before deleting them, then simply replace DELETE
with SELECT *
and USING
with a comma ,
, i.e.
SELECT * FROM table_with_dups T1
, table_with_dups T2
WHERE T1.ctid < T2.ctid -- select the "older" ones
AND T1.name = T2.name -- list columns that define duplicates
AND T1.address = T2.address
AND T1.zipcode = T2.zipcode;
Update: I tested some of the different solutions here for speed. If you don't expect many duplicates, then this solution performs much better than the ones that have a NOT IN (...)
clause as those generate a lot of rows in the subquery.
If you rewrite the query to use IN (...)
then it performs similarly to the solution presented here, but the SQL code becomes much less concise.
Update 2: If you have NULL
values in one of the key columns (which you really shouldn't IMO), then you can use COALESCE()
in the condition for that column, e.g.
AND COALESCE(T1.col_with_nulls, '[NULL]') = COALESCE(T2.col_with_nulls, '[NULL]')
(name, address, zipcode)
? Are there other columns? Are those irrelevant? Different? Is any combination of columns unique? If some columns differ between duplicates, which row out of each set do you want to keep? – Erwin Brandstetter