I hope someone can tell me what I'm doing wrong in this query. I'm unable to find the cause of the error.
I have 2 tables with 2 columns each, see the CREATE statements here:
CREATE TABLE TableA(datum DECIMAL(8,0), colA INTEGER);
CREATE TABLE TableB(datum DECIMAL(8,0), colB INTEGER);
INSERT INTO TableA values('20160104', '1');
INSERT INTO TableA values('20160101', '2');
INSERT INTO TableA values('20160102', '3');
INSERT INTO TableA values('20160105', '2');
INSERT INTO TableA values('20160102', '6');
INSERT INTO TableA values('20160105', '4');
INSERT INTO TableB values('20160107', '5');
INSERT INTO TableB values('20160103', '8');
INSERT INTO TableB values('20160107', '2');
INSERT INTO TableB values('20160101', '1');
INSERT INTO TableB values('20160101', '4');
INSERT INTO TableB values('20160105', '3');
What I'm trying to achieve is to get a result with all the dates and the sum of the columns for that date.
The query that I use is the following:
select datum, sum(resColA), sum(resColB)
from
select datum, sum(colA) as resColA, 0 as resColB
from TableA
group by datum
union
select datum, 0 as resColA, sum(colB) as resColB
from TableB
group by datum
group by datum
order by datum
It keeps telling me:
[SQL0104] Token ( is invalid. Valid tokens: FOR USE SKIP WAIT WITH FETCH ORDER UNION EXCEPT OPTIMIZE.
Both legs of the union work fine as separate SELECT statements, but when I put them together, the whole thing doesn't work any more.
Does anyone have an idea what I'm doing wrong? I can't figure it out.
Best Answer
You want to
group by
again the result of the union. For that you need to enclose the union in parentheses and add an alias ("name" it), i.e. make it a derived table:or make it a CTE (common table expression):
There is practically little difference between the above 2 options and I think no difference in efficiency in DB2. Pick whatever feels more readable to you. Alternatively, you could first
union
the data from the 2 tables and thengroup by
. This will probably result in different execution plans, so test which is more efficient: