On 12/5/2018 8:30 PM, John W Higgins wrote:
On Wed, Dec 5, 2018 at 4:34 PM Phil Endecott
<spam_from_pgsql_li...@chezphil.org
<mailto:spam_from_pgsql_li...@chezphil.org>> wrote:
Dear Experts,
I have a couple of tables that I want to reconcile, finding rows
that match and places where rows are missing from one table or the
other:
...
So my question is: how can I modify my query to output only two rows,
like this:?
+------------+--------+------------+--------+
| date | amount | date | amount |
+------------+--------+------------+--------+
| 2018-01-01 | 10.00 | 2018-01-01 | 10.00 |
| 2018-02-01 | 5.00 | | |
| | | 2018-03-01 | 8.00 |
| 2018-04-01 | 5.00 | 2018-04-01 | 5.00 |
| 2018-05-01 | 20.00 | 2018-05-01 | 20.00 | 1
| 2018-05-01 | 20.00 | 2018-05-01 | 20.00 | 2
+------------+--------+------------+--------+
Evening Phil,
Window functions are your friend here. I prefer views for this stuff -
but subqueries would work just fine.
create view a_rows as (select *,
row_number() OVER (PARTITION BY date, amount)
AS pos from a);
create view b_rows as (select *,
row_number() OVER (PARTITION BY date, amount)
AS pos from b);
select
a_rows.date,
a_rows.amount,
a_rows.pos,
b_rows.date,
b_rows.amount,
b_rows.pos
from
a_rows full join b_rows using (date,amount,pos);
Example here - http://sqlfiddle.com/#!17/305d6/3
John
Any suggestions anyone?
The best I have found so far is something involving EXCEPT ALL:
db=> select * from a except all select * from b;
db=> select * from b except all select * from a;
That's not ideal, though, as what I ultimately want is something
that lists everything with its status:
+------------+--------+--------+
| date | amount | status |
+------------+--------+--------+
| 2018-01-01 | 10.00 | OK |
| 2018-02-01 | 5.00 | a_only |
| 2018-03-01 | 8.00 | b_only |
| 2018-04-01 | 5.00 | OK |
| 2018-05-01 | 20.00 | OK |
| 2018-05-01 | 20.00 | OK |
+------------+--------+--------+
That would be easy enough to achieve from the JOIN.
Thanks, Phil.
This question is always asked time to time.
I have found an old article with so far the best solution for big tables.
https://asktom.oracle.com/pls/asktom/f?p=100:11:::::P11_QUESTION_ID:2151582681236#15393095283923
On the same test data
create table a (date date, amount money);
create table b (date date, amount money);
insert into a values ('2018-01-01', 10);
insert into a values ('2018-02-01', 5);
insert into a values ('2018-04-01', 5);
insert into a values ('2018-05-01', 20);
insert into a values ('2018-05-01', 20);
insert into b values ('2018-01-01', 10);
insert into b values ('2018-03-01', 8);
insert into b values ('2018-04-01', 5);
insert into b values ('2018-05-01', 20);
insert into b values ('2018-05-01', 20);
select tt.date,
tt.amount,
count(tt.src1) CNT1,
count(tt.src2) CNT2
from
(
select a.date,
a.amount,
1 src1,
null::integer src2
from a
union all
select b.date,
b.amount,
null::integer src1,
2 src2
from b
) tt
group by tt.date, tt.amount;
date amount cnt1 cnt2
2018-01-01 $10.00 1 1
2018-02-01 $5.00 1 0
2018-03-01 $8.00 0 1
2018-04-01 $5.00 1 1
2018-05-01 $20.00 2 2
It requires a sort, so you may want to increase work_mem before
execution, and then return it back like
SET work_mem = '512MB';
... run your query
RESET work_mem;
Regards,
Sergei Agalakov
