Select All Rows From Union of Two Tables with Same Column

Question

I've read at least 10 SO questions on this topic and am not able to figure this out. I'm working in Jupyter, but I don't think it makes a difference.

I have two tables:

   Table A           Table B
+-----+-----+     +-----+-----+
|  x  |  y  |     |  x  |  y  |
+-----+-----+     +-----+-----+
|  1  |  2  |     |  1  |  3  |
|  2  |  3  |     |  4  |  6  |
|  3  |  4  |     |  7  |  9  |
|  4  |  5  |     |  10 |  12 |
|  5  |  6  |     +-----+-----+
+-----+-----+

I'm able to take the union of these tables with the following query:

SELECT * FROM (
    SELECT * FROM A UNION SELECT * FROM B
)

However, I'm not sure how to go about returning the four rows that have duplicate x columns from this union. I've tried GROUP BY x HAVING COUNT(*) > 1 , but this only returns 2 rows. The output should be:

+-----+-----+
|  x  |  y  |
+-----+-----+
|  1  |  2  |
|  1  |  3  |
|  4  |  5  |
|  4  |  6  |
+-----+-----+

Answer 1

You seem to want:

select a.*
from a
where exists (select 1 from b where b.x = a.x)
union all
select b.*
from b
where exists (select 1 from a where a.x = b.x);

union incurs overhead for removing duplicates. This seems unnecessary in your case. So, if you don't need duplicate removal, use union all .