Manufacturing based business. We have jobs with material allocations. I have jobs with the same material required but not enough stock on hand to fulfil all those requirements.
I have 10 on hand. How is SQL can I apply in this example the qty the first 10 jobs based on the job delivery date where the AllocCompleted is N. I want to call the field SoftAlloc. I want to see both the completed and non complete allocations.
Job
Material
QtyReq
QtyIss
SoftAlloc
JobDate
AlloCompleted
100
3205
1
0
1
2022-02-28
N
110
3205
1
1
0
2022-02-28
Y
120
3205
1
1
0
2022-02-28
Y
200
3205
1
0
1
2022-02-28
N
300
3205
1
0
1
2022-02-28
N
310
3205
1
1
0
2022-02-28
Y
320
3205
1
1
0
2022-02-28
Y
400
3205
1
0
1
2022-02-28
N
500
3205
1
0
1
2022-03-15
N
540
3205
1
1
0
2022-03-15
Y
550
3205
1
1
0
2022-03-15
Y
600
3205
1
0
1
2022-03-20
N
700
3205
1
0
1
2022-03-20
N
800
3205
1
0
1
2022-03-22
N
900
3205
1
0
1
2022-04-28
N
920
3205
1
1
0
2022-04-28
Y
930
3205
1
1
0
2022-04-28
Y
940
3205
1
1
0
2022-04-28
Y
1000
3205
1
0
1
2022-05-28
N
1100
3205
1
0
0
2022-06-28
N
declare #QtyOnHand int = 10;
select *,
SoftAlloc = case when AllocCompleted <> 'Y' AND sum(QtyReq) over (order by JobDate) <= #QtyOnHand
then QtyReq
when AllocCompleted <> 'Y' sum(QtyReq) over (order by JobDate) - QtyReq <= #QtyOnHand
then #QtyOnHand - sum(QtyReq) over (order by JobDate) + QtyReq
else 0
end
from jobs
use sum(QtyReq) over (order by JobDate) to create a running total of QtyReq and compare with the QtyOnHand. The allocation decision is handle by case expression
declare #QtyOnHand int = 10;
select *,
SoftAlloc = case when sum(QtyReq) over (order by JobDate) <= #QtyOnHand
then QtyReq
when sum(QtyReq) over (order by JobDate) - QtyReq <= #QtyOnHand
then #QtyOnHand - sum(QtyReq) over (order by JobDate) + QtyReq
else 0
end
from jobs
Note : in the fiddle, it is using an identity column to simulate the JobDate sequence
db<>fiddle demo
Related
I'm sure I saw it somewhere, but I cannot find it.
Given this table Historic:
ID1
ID2
Event_Date
Label
1
1
2020-01-01
1
1
1
2020-01-02
1
1
1
2020-01-04
1
1
1
2020-01-08
1
1
1
2020-01-20
1
1
1
2020-12-30
1
1
1
2020-01-01
0
1
1
2020-01-02
1
1
1
2020-01-04
0
1
1
2020-01-08
1
1
1
2020-01-20
0
1
1
2020-12-30
1
1
2
2020-01-01
1
1
2
2020-01-02
1
1
2
2020-01-04
1
2
1
2020-01-08
1
2
1
2020-01-20
1
2
1
2020-12-30
1
And the table startingpoint
ID1
ID2
Event_Date
1
1
2020-01-01
1
1
2020-01-02
1
1
2020-01-05
1
1
2020-01-08
1
1
2020-01-21
1
1
2021-01-01
1
1
2020-01-01
1
1
2020-01-03
1
1
2020-01-06
1
1
2020-01-11
1
1
2020-01-20
1
1
2020-12-31
1
2
2020-01-03
1
2
2020-01-05
1
2
2020-01-08
2
1
2020-01-08
2
1
2020-01-21
2
1
2021-01-01
For each row in startingpoint, compute the number of rows in historic with the same ID1 and ID2, where Event_Date in historic is between StartingPoint.Event_date - n days (I make it n so that I can change for different values) and StartingPoint.Event_date - 2 days. Then use the same rules to compute the fraction of rows with label = 1.
I know I can do this with a join , but if historic and startingpoint are very large, this looks very inefficient (for every row in startingpoint it will create a large join, and in the end it will sumarize the same set of rows many times repetadly). From an abstract point, it looks to me like it would be better to first sumarize historic for every ID1, ID2, Event_date, and the join with the startingpoint and select the best, but I'm open to other solutions.
You can try below solution with subquery:
select * ,(select count(*) from historic h where h.id1=s.id1 and h.id2=s.id2 and h.event_date between dateadd(day,-30,s.event_date) and dateadd(day,-2,s.event_date) )from startingpoint s
You have to have some form of join; either joining directly, or with a scalar subquery, which is probably not going to be as efficient.
The simplest way to do this is probably just a plain join, if you only want to see rows which have historic data:
select sp.id1, sp.id2, sp.event_date,
count(h.event_date) as any_label,
count(case when h.label = 1 then h.label end) as label_1,
count(case when h.label = 1 then h.label end) / count(h.event_date) as fraction_1
from startingpoint sp
join historic h on h.id1 = sp.id1
and h.id2 = sp.id2
and h.event_date >= sp.event_date - 10
and h.event_date < sp.event_date - 2
group by sp.id1, sp.id2, sp.event_date
order by sp.id1, sp.id2, sp.event_date;
where n is 10; which with your data would give you:
ID1 ID2 EVENT_DATE ANY_LABEL LABEL_1 FRACTION_1
--- --- ---------- --------- ------- --------------------
1 1 2020-01-05 4 3 .75
1 1 2020-01-06 4 3 .75
1 1 2020-01-08 6 4 .6666666666666666667
1 1 2020-01-11 8 6 .75
1 2 2020-01-05 2 2 1
1 2 2020-01-08 3 3 1
Or if you want to see zero counts, you can use an outer join; though then the fraction calculation needs some logic to avoid a divide-by-zero error:
select sp.id1, sp.id2, sp.event_date,
count(h.event_date) as any_label,
count(case when h.label = 1 then h.label end) as label_1,
case when count(h.event_date) > 0 then
count(case when h.label = 1 then h.label end) / count(h.event_date)
end as fraction_1
from startingpoint sp
left join historic h on h.id1 = sp.id1
and h.id2 = sp.id2
and h.event_date >= sp.event_date - 10
and h.event_date < sp.event_date - 2
group by sp.id1, sp.id2, sp.event_date
order by sp.id1, sp.id2, sp.event_date;
which gets:
ID1 ID2 EVENT_DATE ANY_LABEL LABEL_1 FRACTION_1
--- --- ---------- --------- ------- --------------------
1 1 2020-01-01 0 0
1 1 2020-01-02 0 0
1 1 2020-01-03 0 0
1 1 2020-01-05 4 3 .75
1 1 2020-01-06 4 3 .75
1 1 2020-01-08 6 4 .6666666666666666667
1 1 2020-01-11 8 6 .75
1 1 2020-01-20 0 0
1 1 2020-01-21 0 0
1 1 2020-12-31 0 0
1 1 2021-01-01 0 0
1 2 2020-01-03 0 0
1 2 2020-01-05 2 2 1
1 2 2020-01-08 3 3 1
2 1 2020-01-08 0 0
2 1 2020-01-21 0 0
2 1 2021-01-01 0 0
db<>fiddle
I know that my question would be duplicated but I really don't know how to created sql which return results of sum with multiple join.
Tables I have
result_summary
num_bin id_summary count_bin
3 172 0
4 172 0
5 172 0
6 172 0
7 172 0
8 172 0
1 174 1
2 174 0
3 174 0
4 174 0
5 174 0
6 174 0
7 174 0
8 174 0
1 175 0
summary_assembly
num_lot id_machine sabun date_work date_write id_product shift count_total count_fail count_good id_summary id_operation
adfe 1 21312 2020-11-25 2020-11-25 1 A 10 2 8 170 2000
adfe 1 21312 2020-11-25 2020-11-25 1 A 1000 1 999 171 2000
adfe 1 21312 2020-11-25 2020-11-25 2 A 100 1 99 172 2000
333 1 21312 2020-12-06 2020-12-06 1 A 10 2 8 500 2000
333 1 21312 2020-11-26 2020-11-26 1 A 10000 1 9999 174 2000
333 1 21312 2020-11-26. 2020-11-26 1 A 100 0 100 175 2000
333 1 21312 2020-12-06 2020-12-06 1 A 10 2 8 503 2000
333 1 21312 2020-12-07 2020-12-07 1 A 10 2 8 651 2000
333 1 21312 2020-12-02 2020-12-02 1 A 10 2 8 178 2000
employees
sabun name_emp
3532 Kim
12345 JS
4444 Gilsoo
21312 Wayn Hahn
123 Lee too
333 JD
info_product
id_product name_product
1 typeA
2 typeB
machine
id_machine id_operation name_machine
1 2000 name1
2 2000 name2
3 2000 name3
4 3000 name1
5 3000 name2
6 3000 name3
7 4000 name1
8 4000 name2
query
select S.id_summary, I.name_product, M.name_machine,
E.name_emp, S.sabun, S.date_work,
S.shift, S.num_lot, S.count_total,
S.count_good, S.count_fail,
sum(case num_bin when '1' then count_bin else 0 end) as bin1,
sum(case num_bin when '2' then count_bin else 0 end) as bin2,
sum(case num_bin when '3' then count_bin else 0 end) as bin3,
sum(case num_bin when '4' then count_bin else 0 end) as bin4,
sum(case num_bin when '5' then count_bin else 0 end) as bin5,
sum(case num_bin when '6' then count_bin else 0 end) as bin6,
sum(case num_bin when '7' then count_bin else 0 end) as bin7,
sum(case num_bin when '8' then count_bin else 0 end) as bin8
from result_assembly as R
join summary_assembly as S on R.id_summary = S.id_summary
join employees as E on S.sabun = E.sabun
join info_product as I on S.id_product = I.id_product
join machine as M on S.id_machine = M.id_machine
where I.id_product = '1'
and E.sabun='21312'
and S.shift = 'A'
and S.date_work between '2020-11-10' and '2020-12-20'
group by S.id_summary, E.name_emp, S.num_lot,
I.name_product,M.name_machine
order by S.id_summary;
result
id_summary name_product name_machine name_emp sabun date_work shift num_lot count_total count_good count_fail bin1 bin2 bin3 bin4 bin5 bin6 bin7 bin8
170 TypeA name1 Kim 21312 2020-11-25 A adfe 10 8 2 1 1 0 0 0 0 0 0
171 TypeA name1 Kim 21312 2020-11-25 A adfe 1000 999 1 1 1 0 0 0 0 0 0
174 TypeA name1 Kim 21312 2020-11-26 A 333 10000 9999 1 1 1 0 0 0 0 0 0
175 TypeA name1 Kim 21312 2020-11-26 A 333 100 100 0 0 0 0 0 0 0 0 0
178 TypeA name1 Kim 21312 2020-12-02 A 333 10 8 2 1 1 0 0 0 0 0 0
179 TypeA name1 Kim 21312 2020-12-02 A 333 10 8 2 1 1 0 0 0 0 0 0
180 TypeA name1 Kim 21312 2020-12-02 A 333 10 8 2 1 1 0 0 0 0 0 0
181 TypeA name1 Kim 21312 2020-12-02 A 333 10 8 2 1 1 0 0 0 0 0 0
182 TypeA name2 Kim 21312 2020-12-02 A 333 10 8 2 1 1 0 0 0 0 0 0
186 TypeA name2 Kim 21312 2020-12-06 A 333 10 8 2 1 1 0 0 0 0 0 0
193 TypeA name2 Kim 21312 2020-12-06 A 333 10 8 2 0 0 0 0 0 0 0 0
194 TypeA name2 Kim 21312 2020-12-06 A 333 10 8 2 0 0 0 0 0 0 0 0
195 TypeA name2 Kim 21312 2020-12-06 A 333 10 8 2 0 0 0 0 0 0 0 0
196 TypeA name2 JS 21312 2020-12-06 A 333 10 8 2 0 0 0 0 0 0 0 0
197 TypeA name2 JS 21312 2020-12-06 A 333 10 8 2 0 0 0 0 0 0 0 0
198 TypeA name2 JS 21312 2020-12-06 A 333 10 8 2 0 0 0 0 0 0 0 0
199 TypeA name2 JS 21312 2020-12-06 A 333 10 8 2 0 0 0 0 0 0 0 0
200 TypeA name2 JS 21312 2020-12-06 A 333 10 8 2 0 0 0 0 0 0 0 0
expected output(when sum by num_lot)
num_lot count_total count_good count_fail bin1 bin2 bin3 bin4 bin5 bin6 bin7 bin8
adfe 323 300 23 22 1 0 0 0 0 0 0
333 4312 4300 12 10 2 0 0 0 0 0 0
All of them were modified from original one because they were non-English, so there would be typo.
Here now I need to sum by num_lot, name_product or sabun.
id_summary is unique.
Thanks
As expected in the comments: It seems like you simple need a subquery which groups your table by the column num_lot
SELECT
num_lot,
SUM(count_total),
SUM(count_good)
-- some more SUM()
FROM (
--<your query>
) s
GROUP BY num_lot
It was asked in the comments what the s stands for: A subquery needs an alias, an identifier. Because I didn't want to think about a better name, I just called the subselect s. It is the shortcut for AS s
It sounds like you want to use crosstab() -- https://www.postgresql.org/docs/current/tablefunc.html
I have this table (I put the name over needed colums)
iddip date idv idc val
47 2018-06-01 00:00:00.000 0 3 3 60 NULL NULL
47 2018-06-01 00:00:00.000 0 1 3 200 NULL NULL
47 2018-06-01 00:00:00.000 0 1 4 280 NULL NULL
43 2018-06-01 00:00:00.000 0 3 2 510 NULL NULL
53 2018-06-01 00:00:00.000 0 1 4 480 NULL NULL
29 2018-06-01 00:00:00.000 0 3 2 510 NULL NULL
2 2018-06-11 00:00:00.000 0 1 2 480 NULL NULL
47 2018-06-02 00:00:00.000 0 1 3 100 NULL NULL
I want to obtain this:
id idc Totidv1 Totidv3 TOT
47 3 300 60 360
47 4 280 0 280
43 2 0 510 510
53 4 480 0 480
29 2 0 510 510
2 2 480 0 480
The closest I can get is:
SELECT DISTINCT(iddip),IDCENTROCOSTO,tot=SUM(VALORE),ord=( SELECT SUM(isnull(VALORE,0)) FROM VALORIVOCICDC WHERE IDVOCE='1' and iddip=v.IDDIP and IDCENTROCOSTO ='3' GROUP BY iddip,IDCENTROCOSTO),
str=( SELECT SUM(isnull(VALORE,0)) FROM VALORIVOCICDC WHERE IDVOCE='3' and iddip=v.IDDIP and IDCENTROCOSTO ='3' GROUP BY iddip,IDCENTROCOSTO)
FROM VALORIVOCICDC v
GROUP BY v.iddip,IDCENTROCOSTO
But it returns wrong sums in totidv1 and totisv3, How can I do this? Thanks for any hint
You just need a GROUP BY here (not distinct) and a couple of CASE statements:
SELECT
id,
idc,
SUM(CASE WHEN idv=3 THEN idv ELSE 0 END) as totidv1,
SUM(CASE WHEN idv=1 THEN idv ELSE 0 END) as totidv3,
SUM(idv) as Tot
FROM yourtable
GROUP BY id, idc
Note that Distinct is not a function that you can call like SELECT DISTINCT(somecolumn) This is functionally equivalent to SELECT DISTINCT somecolumn... in that it works against the entire record set returned by the SELECT statement either way.
I need one adaptation for the first table because there are negative issues points and I need the net table considerating the negatives points as debit of the first time of issue. E.g:
FechaEmi Cuenta PtosEmi PtosCan
30/06/2015 1 100 0
31/07/2015 1 120 0
31/08/2015 1 130 0
31/08/2015 1 0 55
30/09/2015 1 50 0
31/10/2015 1 30 0
30/11/2015 1 70 0
31/12/2015 1 95 0
31/01/2016 1 50 0
29/02/2016 1 0 74
31/03/2016 1 50 0
30/04/2016 1 15 0
30/06/2015 2 20 0
31/07/2015 2 30 0
31/08/2015 2 40 0
30/09/2015 2 350 0
30/06/2015 3 150 0
31/07/2015 3 120 0
31/08/2015 3 0 56
31/08/2015 3 220 0
30/06/2015 4 70 0
31/07/2015 4 134 0
31/08/2015 4 12 0
30/06/2015 5 97 0
31/07/2015 5 130 0
31/08/2015 5 15 0
30/09/2015 5 135 0
31/10/2015 5 20 0
30/11/2015 5 140 0
31/12/2015 5 25 0
31/01/2016 5 145 0
29/02/2016 5 0 25
where:
FechaEmi= Date;
Cuenta=ID;
PtosEmi=Issues points;
PtosCan=Canceled points
I want this table
FechaEmi Cuenta PtosEmi
30/06/2015 1 0
31/07/2015 1 91
31/08/2015 1 130
30/09/2015 1 50
31/10/2015 1 30
30/11/2015 1 70
31/12/2015 1 95
31/01/2016 1 50
31/03/2016 1 50
30/04/2016 1 15
30/06/2015 2 20
31/07/2015 2 30
31/08/2015 2 40
30/09/2015 2 350
30/06/2015 3 94
31/07/2015 3 120
31/08/2015 3 220
30/06/2015 4 70
31/07/2015 4 134
31/08/2015 4 12
30/06/2015 5 72
31/07/2015 5 130
31/08/2015 5 15
30/09/2015 5 135
31/10/2015 5 20
30/11/2015 5 140
31/12/2015 5 25
31/01/2016 5 145
I have this code. The problem is that doesn't do anything with the points that were debited in a date that there are not issues point. How can you recommend me change that query? Thanks!
with cte as(
select Fechaemi, Cuenta,PtosEmi,PtosCan
,row_number() over (partition by Fechaemi,Cuenta order by Fechaemi,Cuenta) as rank
from emision)
select a.Fechaemi, a.Cuenta,a.PtosEmi - coalesce(b.PtosCan, 0) stock
from cte a
left join cte b on
a.FechaEmi= b.FechaEmi and a.Cuenta = b.Cuenta and a.rank = b.rank - 1
where a.PtosEmi - coalesce(b.PtosCan, 0) > 0 order by a.cuenta asc, a.fechaemi asc
SQL FIDDLE DEMO
with totalPay as(
SELECT Cuenta, SUM(PtosCan) TotalPayment
FROM emision
GROUP BY Cuenta
),
totalDebt as (
SELECT FechaEmi, Cuenta, (SELECT SUM(PtosEmi)
FROM emision e2
WHERE e2.FechaEmi <= e.FechaEmi
AND e2.Cuenta = e.Cuenta
) AS TotalDebt
FROM emision e
WHERE e.PtosEmi <> 0
)
select
e.FechaEmi,
e.Cuenta,
e.PtosEmi,
td.TotalDebt,
tp.TotalPayment,
CASE
WHEN td.TotalDebt < tp.TotalPayment THEN 0
WHEN td.TotalDebt - tp.TotalPayment > PtosEmi THEN PtosEmi
ELSE td.TotalDebt - tp.TotalPayment
END Remaining
FROM
totalDebt td inner join
totalPay tp on td.Cuenta = tp.Cuenta inner join
emision e on td.FechaEmi = e.FechaEmi AND td.Cuenta = e.Cuenta
WHERE
e.PtosEmi <> 0
Possibly not the most elegant, but explicit way:
WITH
PtosEmi AS(
SELECT FechaEmi, cuenta, SUM(PtosEmi) as PtosEmi
FROM table1
GROUP BY FechaEmi, cuenta),
PtosCan AS (
SELECT MIN(FechaEmi) as FechaEmi, cuenta, SUM(PtosCan) as PtosCan
FROM table1
GROUP BY cuenta)
SELECT
e.FechaEmi,
e.cuenta,
e.ptosemi,
c.ptoscan,
e.ptosemi - COALESCE(c.ptoscan, 0) total
FROM
PtosEmi e LEFT JOIN
PtosCan c ON e.FechaEmi = c.FechaEmi AND e.cuenta = c.cuenta
ORDER BY e.cuenta, e.FechaEmi
This is based on the assumption that you cannot have cancellations before anything was issued for give cuenta.
Also if you have more cancelled items in total compared to what was issued initially, total value will be negative.
http://sqlfiddle.com/#!6/9ac40/11
Update
as you want to reduce cancellations line by line here is updated query:
WITH
ptosemi AS(
SELECT FechaEmi, cuenta,
PtosEmi as PtosEmi,
SUM(PtosEmi) OVER (PARTITION BY cuenta ORDER BY FechaEmi) runsum
FROM table1),
PtosCan AS (
SELECT cuenta, SUM(PtosCan) as PtosCan
FROM table1
GROUP BY cuenta)
SELECT
e.FechaEmi,
e.cuenta,
e.ptosemi,
e.runsum,
c.ptoscan,
CASE
WHEN e.runsum <= c.ptoscan
THEN 0
WHEN c.ptoscan BETWEEN e.runsum - e.ptosemi AND e.runsum
THEN e.runsum - COALESCE(c.ptoscan, 0)
ELSE e.ptosemi END total
FROM
ptosemi e LEFT JOIN
PtosCan c ON e.cuenta = c.cuenta
ORDER BY e.cuenta, e.FechaEmi
http://sqlfiddle.com/#!6/8036c2/25
Say I have the following data in my table;
tran_date withdraw deposit
25/11/2010 0 500
2/12/2010 100 0
15/12/2010 0 300
18/12/2010 0 200
25/12/2010 200 0
Suppose I want to get the following for date range between 1/12/2010 and 31/12/2010.
tran_date withdraw deposit balance days_since_last_tran
1/12/2010 0 0 500 0
2/12/2010 100 0 400 1
15/12/2010 0 300 700 13
18/12/2010 0 200 900 3
25/12/2010 200 0 700 7
31/12/2010 0 0 700 6
Is this doable in PostgreSQL 8.4?
Use:
SELECT t.tran_date,
t.withdraw,
t.deposit,
(SELECT SUM(y.deposit) - SUM(y.withdrawl)
FROM YOUR_TABLE y
WHERE y.tran_date <= t.tran_date) AS balance,
t.tran_date - COALESCE(LAG(t.tran_date) OVER(ORDER BY t.tran_date),
t.tran_date) AS days_since_last
FROM YOUR_TABLE t
8.4+ is nice, providing access to analytic/windowing functions like LAG.