Reputation: 1846
I have the following data table:
month marketid totalsold totalshipped lefttoship_thismonth
....
01-01-2015 1 100 50 50
01-01-2015 2 10 3 7
01-01-2015 3 0 0 0
01-02-2015 1 0 50 -50
01-02-2015 2 20 0 20
01-02-2015 3 0 0 0
Basically this table shows information about orders and shipments per market per month.
The date 01-01-2015
in month
column actually represents Jan 2015
(the whole month).
I want to SUM
the lefttoship_thismonth
per market for each month with all previous months. This is needed as someone can place order in January which was supplied in February. So I want to know how many items I still need to ship per month.
The output should be:
month marketid totalsold totalshipped totallefttoship TOTALLEFT
01-01-2015 1 100 50 50 50
01-01-2015 2 10 3 7 7
01-01-2015 3 0 0 0 0
01-02-2015 1 0 50 -50 0 /50-50
01-02-2015 2 20 0 20 27 /7+20
01-02-2015 3 0 0 0 0 / 0+0
How can I do that?
I have no idea how to sum this way and the month
column is very hard to work with.
Upvotes: 3
Views: 1200
Reputation: 6328
You can do it with a SubQuery, if your versions of PostgreSQL does not (yet) allow for window functions):
WITH t (month, marketid, totalsold, totalshipped, lefttoship_thismonth) AS
(VALUES
('01-01-2015'::date, 1, 100, 50, 50),
('01-01-2015'::date, 2, 10, 3, 7),
('01-01-2015'::date, 3, 0, 0, 0),
('01-02-2015'::date, 1, 0, 50, -50),
('01-02-2015'::date, 2, 20, 0, 20),
('01-02-2015'::date, 3, 0, 0, 0)
)
SELECT
month,
marketid,
totalsold,
totalshipped,
lefttoship_thismonth,
(SELECT sum(lefttoship_thismonth)
FROM t t2
WHERE t2.marketid = t1.marketid AND
t2.month <= t1.month
) AS total_left
FROM
t t1
ORDER BY
month, marketid ;
would get you the following result:
|------------+----------+-----------+--------------+----------------------+------------|
| month | marketid | totalsold | totalshipped | lefttoship_thismonth | total_left |
|------------+----------+-----------+--------------+----------------------+------------|
| 2015-01-01 | 1 | 100 | 50 | 50 | 50 |
|------------+----------+-----------+--------------+----------------------+------------|
| 2015-01-01 | 2 | 10 | 3 | 7 | 7 |
|------------+----------+-----------+--------------+----------------------+------------|
| 2015-01-01 | 3 | 0 | 0 | 0 | 0 |
|------------+----------+-----------+--------------+----------------------+------------|
| 2015-01-02 | 1 | 0 | 50 | -50 | 0 |
|------------+----------+-----------+--------------+----------------------+------------|
| 2015-01-02 | 2 | 20 | 0 | 20 | 27 |
|------------+----------+-----------+--------------+----------------------+------------|
| 2015-01-02 | 3 | 0 | 0 | 0 | 0 |
|------------+----------+-----------+--------------+----------------------+------------|
If you can use Window functions (which are more efficient), you can do the following:
SELECT
month,
marketid,
totalsold,
totalshipped,
lefttoship_thismonth,
( sum(lefttoship_thismonth)
OVER (PARTITION BY marketid ORDER BY month ROWS UNBOUNDED PRECEDING)
) AS total_left
FROM
t t1
ORDER BY
month, marketid ;
If your month
column is a varchar (not a good idea), you can cast it to date, or use the to_date
function.
Upvotes: 3
Reputation: 39457
Too long for a comment.
If the column is varchar type then you'll have to convert it into date to use it in the order by clause like this.
select t.*,
sum(totallefttoship) over
(partition by marketid order by to_date(month,'dd-mm-yyyy')) as TOTALLEFT
From yourtable t
Upvotes: 2