I want to update a table with the sum of a second table
This is the table 'x' that I want to update. Has a starting value and a closing value:
id
op_date
initial_value
end_value
1
2020-02-01
0
0
1
2020-02-02
0
0
2
2020-02-01
0
0
2
2020-02-02
0
0
The table 'y' save the values of the day:
id
op_date
value_day
1
2020-01-29
500
1
2020-02-01
100
1
2020-02-02
200
2
2020-01-29
750
2
2020-02-01
100
2
2020-02-02
250
I want the result to look like this:
id
op_date
initial_value
end_value
1
2020-02-01
500
600
1
2020-02-02
600
800
2
2020-02-01
750
850
2
2020-02-02
850
1100
I tried this script, but the process just runs it and doesn't finish it:
UPDATE x
SET
initial_value= (select sum(y.value_day)
from public.y where
y.op_date > '2020-11-01' and y.op_date < x.op_date
and y.id = x.id),
end_value= (select sum(y.value_day)
from public.y where
y.op_date between '2020-11-01' and x.op_date
and y.id = x.id);
You can use window function. To understand window function more you can look this link.
At first i am writing query to select the value.
select id,op_date,
sum(value_day) over (
partition by y.id
rows between unbounded preceding and current row
)-value_day as initial_value,
sum(value_day) over (
partition by y.id
rows between unbounded preceding and current row
) as end_value
from y
;
This is your update query.
UPDATE x
set initial_value=s_statement.initial_value,
end_value=s_statement.end_value
from
(select id,op_date,
sum(value_day) over (
partition by y.id
rows between unbounded preceding and current row
)-value_day as initial_value,
sum(value_day) over (
partition by y.id
rows between unbounded preceding and current row
) as end_value
from y) s_statement
where x.id=s_statement.id
and x.op_date=s_statement.op_date
;
Let me know if its ok with you.
Related
I have a table table1 which contains the details of any depositor like
Depositor
Deposit_Amount
Deposit_Date
Maturity_Date
Tenure
Rate
A
25000
2021-08-10
2022-08-10
12
10%
I have another table table2 which contains the interest due date as:
Interest_Due_Date
2021-09-30
2021-12-31
2022-03-31
2022-06-30
2022-08-10
My Code is:
with recursive recur (n, start_bal, days,principle,interest, end_bal) as
(
select sno,deposit_amount,rate,days,deposit_amount * (((rate::decimal(18,2))/100)/365)*days as interest, deposit_amount+(deposit_amount * (((rate::decimal(18,2))/100)/365)*days) as end_bal from (
SELECT
sno, COALESCE(DATE_PART('day', deposit_date::TIMESTAMP - lag(deposit_date::TIMESTAMP) over
(ORDER BY sno ASC rows BETWEEN UNBOUNDED PRECEDING AND CURRENT row)),0) AS
days, deposit_date, deposit_amount, rate
FROM
( SELECT
ROW_NUMBER () OVER (ORDER BY deposit_date) AS sno,
deposit_date,
deposit_amount,
rate
FROM
( SELECT
t1.deposit_date, t1.deposit_amount, t1.rate from table1 t1
UNION ALL
SELECT
t2.Interest_Due_Date AS idate, 0 as depo_amount, 0 as rate
FROM
table2 t2
ORDER BY
deposit_date) dep) calc) b where sno = 1 union all select b.sno, b.end_bal,b.days,b.prin_bal,(coalesce(a.end_bal,0)) * (((b.rate)/100)/365)*b.days as interest_NEW,
coalesce(a.end_bal,0)+ ((a.end_bal) * (((calc.rate)/100)/365)*calc.days) as end_bal_NEW
from b, recur as a
where calc.sno = a.n+1 ) select * from recur
"Every time when i try to execute the query its showing an error 'relation 'b' does not exist"
...
The result table should be
Deposit Amount
Date
Days
Interest
Total Amount
25000
2021-08-10
0
0
25000
0
2021-09-30
51
349.32
25349.32
0
2021-12-31
92
638.94
25988.26
0
2022-03-31
90
640.81
26629.06
0
2022-06-30
91
663.90
27292.97
0
2022-08-10
41
306.58
27599.54
I have a table with a shipment_id, no_of_boxes, and no_of_pallets as shown below.
shipment_id
no_of_boxes
no_of_pallets
1
23
0
1
45
0
1
0
1
2
3
0
2
165
0
2
0
10
I want to sum the no_of_boxes, and no_of_pallets columns against their respective shipment_id. The columns no_of_boxes, and no_of_pallets are COUNT derived columns (calculated from a different table with JOINS).
I tried writing a subquery for this but didn't help. Below subquery is for no_of_boxes, a similar query was written for no_of_pallets.
SELECT SUM(no_of_boxes)
FROM (SELECT COUNT(si.shipment_item_id) AS no_of_boxes
FROM shipment_item AS si
JOIN shipment_item AS si
ON si.shipment_order_systemid = sho.system_id
JOIN shipping_unit AS su
ON su.system_id = si.shipping_unit_systemid
WHERE su.unit LIKE 'BOX'
GROUP BY si.shipment_item_id,
su.unit) t
My desired result is:
shipment_id
no_of_boxes
no_of_pallets
1
68
1
2
168
10
To get the result you want, use the following query:
SELECT shipment_id, sum(no_of_boxes), sum(no_of_pallets)
FROM shipments
GROUP BY shipment_id;
Suppose I have data formatted in the following way (FYI, total row count is over 30K):
customer_id order_date order_rank
A 2017-02-19 1
A 2017-02-24 2
A 2017-03-31 3
A 2017-07-03 4
A 2017-08-10 5
B 2016-04-24 1
B 2016-04-30 2
C 2016-07-18 1
C 2016-09-01 2
C 2016-09-13 3
I need a 4th column, let's call it days_since_last_order which, in the case where order_rank = 1 then 0 else calculate the number of days since the previous order (with rank n-1).
So, the above would return:
customer_id order_date order_rank days_since_last_order
A 2017-02-19 1 0
A 2017-02-24 2 5
A 2017-03-31 3 35
A 2017-07-03 4 94
A 2017-08-10 5 38
B 2016-04-24 1 0
B 2016-04-30 2 6
C 2016-07-18 1 79
C 2016-09-01 2 45
C 2016-09-13 3 12
Is there an easier way to calculate the above with a window function (or similar) rather than join the entire dataset against itself (eg. on A.order_rank = B.order_rank - 1) and doing the calc?
Thanks!
use the lag window function
SELECT
customer_id
, order_date
, order_rank
, COALESCE(
DATE(order_date)
- DATE(LAG(order_date) OVER (PARTITION BY customer_id ORDER BY order_date))
, 0)
FROM <table_name>
Think of a table like below:
unique_id
a_column
b_column
a_int
b_int
date_created
Let's say data is like:
-unique_id -a_column -b_column -a_int -b_int -date_created
1z23 abc 444 0 1 27.12.2016 18:03:00
2c31 abc 444 0 0 26.12.2016 13:40:00
2e22 qwe 333 0 1 28.12.2016 15:45:00
1b11 qwe 333 1 1 27.12.2016 19:00:00
3a33 rte 333 0 1 15.11.2016 11:00:00
4d44 rte 333 0 1 27.09.2016 18:00:00
6e66 irt 333 0 1 22.12.2016 13:00:00
7q77 aaa 555 1 0 27.12.2016 18:00:00
I want to get the unique_id s where b_int is 1, b_column is 333 and considering a_column, a_int column must always be 0, if there are any records with a_int = 1 even if there are records with a_int = 0 these records must not be shown in the result. Desired result is: " 3a33 , 6e66 " when grouped by a_column and ordered by date_created and got top1 for each unique a_column.
I tried lots of "with ties" and "over(partition by" samples, searched questions, but couldn't manage to do it. This is what I could do:
select unique_id
from the_table
where b_column = '333'
and b_int = 1
and a_column in (select a_column
from the_table
where b_column = '333'
and b_int = 1
group by a_column
having sum(a_int) = 0)
order by date_created desc;
This query returns the result like this " 3a33 ,4d44, 6e66 ". But I don't want "4d44".
You were on the right track with the partitions and window functions. This solution uses ROW_NUMBER to assign a value to the a_column so we can see where there is more than 1. The 1 is the most recent date_created. Then you select from the result set where the row_counter is 1.
;WITH CTE
AS (
SELECT unique_id
, a_column
, ROW_NUMBER() OVER (
PARTITION BY a_column ORDER BY date_created DESC
) AS row_counter --This assigns a 1 to the most recent date_created and partitions by a_column
FROM #test
WHERE a_column IN (
SELECT a_column
FROM #test
WHERE b_column = '333'
AND b_int = 1
GROUP BY a_column
HAVING MAX(a_int) < 1
)
)
SELECT unique_ID
FROM cte
WHERE row_counter = 1
I have the following situation
ID Value
1 50
1 60
2 70
2 80
1 0
2 50
I need to run a query that would return summed value, grouped by ID. The catch is if the value is 0, then the entire sum should be 0.
Query results would be
ID Value
1 0
2 200
I tried
select ID, case
when Value> 0 then sum(Value) * 1
when Value= 0 then sum(value) * 0
end
from table
but that did not work.
select ID,
sum(value)*sign(min(abs(value))) as [sum(value)]
from YourTable
group by ID
With a case if you like:
select ID,
case sign(min(abs(value)))
when 0 then 0
else sum(value)
end as [sum(value)]
from YourTable
group by ID