How to make accounting balance report? - sql

I'm new to Oracle apex and SQL. I am developing an Oracle app for accounting. My table ga_voucher contains the following columns with values like:
VNO | DBIT CODE | AMOUNT | CREDIT CODE | VDATE | NARRATION
01 121005 40000 331001 09/07/2021 ABCD
02 331002 50000 121005 09/07/2021
I want to generate report with unique account code balance (debit total of a code - credit total) like:
Account CODE | DEBIT TOTAL|CREDIT TOTAL | BALANCE
331002 50000 | 40000 | 10000
What is the SQL query for the report? Please help me.

I'm pretty sure the 331001 in the first row should really be 331002. If so, I think you want to unpivot the data and aggregate:
select x.account_code, sum(x.debit) as debit, sum(x.credit) as credit,
sum(x.debit - x.credit) as balance\
from ga_voucher v cross join lateral
(select v.debit_code as account_code, v.amount as debit, 0 as credit from dual union all
select v.credit_code, 0, v.amount from dual
) x
group by x.account_code;

Related

How to calculate average monthly number of some action in some perdion in Teradata SQL?

I have table in Teradata SQL like below:
ID trans_date
------------------------
123 | 2021-01-01
887 | 2021-01-15
123 | 2021-02-10
45 | 2021-03-11
789 | 2021-10-01
45 | 2021-09-02
And I need to calculate average monthly number of transactions made by customers in a period between 2021-01-01 and 2021-09-01, so client with "ID" = 789 will not be calculated because he made transaction later.
In the first month (01) were 2 transactions
In the second month was 1 transaction
In the third month was 1 transaction
In the nineth month was 1 transactions
So the result should be (2+1+1+1) / 4 = 1.25, isn't is ?
How can I calculate it in Teradata SQL? Of course I showed you sample of my data.
SELECT ID, AVG(txns) FROM
(SELECT ID, TRUNC(trans_date,'MON') as mth, COUNT(*) as txns
FROM mytable
-- WHERE condition matches the question but likely want to
-- use end date 2021-09-30 or use mth instead of trans_date
WHERE trans_date BETWEEN date'2021-01-01' and date'2021-09-01'
GROUP BY id, mth) mth_txn
GROUP BY id;
Your logic translated to SQL:
--(2+1+1+1) / 4
SELECT id, COUNT(*) / COUNT(DISTINCT TRUNC(trans_date,'MON')) AS avg_tx
FROM mytable
WHERE trans_date BETWEEN date'2021-01-01' and date'2021-09-01'
GROUP BY id;
You should compare to Fred's answer to see which is more efficent on your data.

Cumulative Sum Query in SQL table with distinct elements

I have a table like this, with column names as Date of Sale and insurance Salesman Names -
Date of Sale | Salesman Name | Sale Amount
2021-03-01 | Jack | 40
2021-03-02 | Mark | 60
2021-03-03 | Sam | 30
2021-03-03 | Mark | 70
2021-03-02 | Sam | 100
I want to do a group by, using the date of sale. The next column should display the cumulative count of the sellers who have made the sale till that date. But same sellers shouldn't be considered again.
For example,
The following table is incorrect,
Date of Sale | Count(Salesman Name) | Sum(Sale Amount)
2021-03-01 | 1 | 40
2021-03-02 | 3 | 200
2021-03-03 | 5 | 300
The following table is correct,
Date of Sale | Count(Salesman Name) | Sum(Sale Amount)
2021-03-01 | 1 | 40
2021-03-02 | 3 | 200
2021-03-03 | 3 | 300
I am not sure how to frame the SQL query, because there are two conditions involved here, cumulative count while ignoring the duplicates. I think the OVER clause along with the unbounded row preceding may be of some use here? Request your help
Edit - I have added the Sale Amount as a column. I need the cumulative sum for the Sales Amount also. But in this case , all the sale amounts should be considered unlike the salesman name case where only unique names were being considered.
One approach uses a self join and aggregation:
WITH cte AS (
SELECT t1.SaleDate,
COUNT(CASE WHEN t2.Salesman IS NULL THEN 1 END) AS cnt,
SUM(t1.SaleAmount) AS amt
FROM yourTable t1
LEFT JOIN yourTable t2
ON t2.Salesman = t1.Saleman AND
t2.SaleDate < t1.SaleDate
GROUP BY t1.SaleDate
)
SELECT
SaleDate,
SUM(cnt) OVER (ORDER BY SaleDate) AS NumSalesman,
SUM(amt) OVER (ORDER BY SaleDate) AS TotalAmount
FROM cte
ORDER BY SaleDate;
The logic in the CTE is that we try to find, for each salesman, an earlier record for the same salesman. If we can't find such a record, then we assume the record in question is the first appearance. Then we aggregate by date to get the counts per day, and finally take a rolling sum of counts in the outer query.
The best way to do this uses window functions to determine the first time a sales person appears. Then, you just want cumulative sums:
select saledate,
sum(case when seqnum = 1 then 1 else 0 end) over (order by saledate) as num_salespersons,
sum(sum(sales)) over (order by saledate) as running_sales
from (select t.*,
row_number() over (partition by salesperson order by saledate) as seqnum
from t
) t
group by saledate
order by saledate;
Note that this in addition to being more concise, this should have much, much better performance than a solution that uses a self-join.

SQL Query to get sums among multiple payments which are greater than or less than 10k

I am trying to write a query to get sums of payments from accounts for a month. I have been able to get it for the most part but I have hit a road block. My challenge is that I need a count of the amount of payments that are either < 10000 or => 10000. The business rules are that a single payment may not exceed 10000 but there can be multiple payments made that can total more than 10000. As a simple mock database it might look like
ID | AccountNo | Payment
1 | 1 | 5000
2 | 1 | 6000
3 | 2 | 5000
4 | 3 | 9000
5 | 3 | 5000
So the results I would expect would be something like
NumberOfPaymentsBelow10K | NumberOfPayments10K+
1 | 2
I would like to avoid doing a function or stored procedure and would prefer a sub query.
Any help with this query would be greatly appreciated!
I suggest avoiding sub-queries as much as possible because it hits the performance, specially if you have a huge amount of data, so, you can use something like Common Table Expression instead. You can do the same by using:
;WITH CTE
AS
(
SELECT AccountNo, SUM(Payment) AS TotalPayment
FROM Payments
GROUP BY AccountNo
)
SELECT
SUM(CASE WHEN TotalPayment < 10000 THEN 1 ELSE 0 END) AS 'NumberOfPaymentsBelow10K',
SUM(CASE WHEN TotalPayment >= 10000 THEN 1 ELSE 0 END) AS 'NumberOfPayments10K+'
FROM CTE
You can get the totals per account using SUM and GROUP BY...
SELECT AccountNo, SUM(Payment) AS TotPay
FROM payments
GROUP BY AccountNo
You can use that result to count the number over 10000
SELECT COUNT(*)
FROM (
SELECT AccountNo, SUM(Payment) AS TotPay
FROM payments
GROUP BY AccountNo
)
WHERE TotPay>10000
You can get the the number over and the number under in a single query if you want but that's a but more complicated:
SELECT
COUNT(CASE WHEN TotPay<=10000 THEN 1 END) AS Below10K,
COUNT(CASE WHEN TotPay> 10000 THEN 1 END) AS Above10K
FROM (
SELECT AccountNo, SUM(Payment) AS TotPay
FROM payments
GROUP BY AccountNo
)

Compare 2 subsets of data from table?

I'm not sure if this is possible - I'm having real trouble getting my head around it.
This is for a product schedule, showing how much we are expecting to deliver on a given date. Data is imported into this schedule weekly which creates a new entry.
For example, if the schedule for the day currently totals 10, and you import 15, a new row is inserted with Qty 5, bringing the sum to 15.
The data I have is like so:
Product | Delivery Required Date | Qty
Prod1 | 1/1/13 | 10
Prod1 | 1/1/13 | -10
Prod1 | 1/1/13 | 10
Prod1 | 1/1/13 | -10
Prod1 | 1/1/13 | 25
I want to design a query which shows the variance between the previous schedule, and the current schedule.
For example, the query will sum all of the rows "Qty", excluding the last entry - and compare it to the last entry. In the data above, the variance is 25 (Existing total was 0, latest entry is 25, 0+25 =25).
Is this possible?
Thanks
I suspect there'a better answer using Common Table Expressions, but a quick & ugly solution might be
select sum(case when EntryNo <> MAX(EntryNo) then Qty else 0 end) as 'sumLessLast'
from MyTable
If MyTable has a million rows in it you'll want a better solution.
SqlServer 2005 and 2008:
;with r1 as (
select DeliveryReqDate, sum(Qty) as TotalQty
from TableName
group by DeliveryReqDate)
, r2 as (
select DeliveryReqDate, Qty
, row_number() over (partition by DeliveryReqDate order by EntryNo desc) rn
from TableName)
select r1.DeliveryReqDate, r1.TotalQty, r2.Qty as LastQty
, r1.TotalQty - r2.Qty as TotalButLastQty
from r1
join r2 on r2.DeliveryReqDate = r1.DeliveryReqDate and r2.rn = 1
SqlServer 2012
;with r1 as (
select DeliveryReqDate, Qty
, sum(Qty) over (partition by DeliveryReqDate) as TotalQty
, row_number() over (partition by DeliveryReqDate order by EntryNo desc) rn
from TableName)
select DeliveryReqDate, TotalQty, Qty as LastQty
, TotalQty - Qty as TotalButLastQty
from r1
where rn = 1
I'm not sure that I completely understand logic regarding the accounting of product and date, but I hope you can adapt above queries to your needs.

Displaying unique attributes of table and the total value in postgresql

I have one table with columns stamp_type and amount as follows
stamp_type | amount
--------------------------------------------------------------+--------
GENERAL STAMP | 11000
GENERAL STAMP | 25000
COURT FEE STAMP | 9800
SPECIAL ADHESIVE | 721000
GENERAL STAMP | 125000
COURT FEE STAMP | 21000
Now I want to display as follows:
stamp_type | amount
GENERAL STAMP 161000
COURT FEE STAMP 30800
SPECIAL ADHESIVE 721000
TOTAL:912800
I am unable to display the unique values. can any one give suggest me the query. I tried to use Distinct but dint work.
select * from
(
select 0 as srt, stamp_type, sum(amount) as SumAmount from t group by stamp_type
union
select 1 as srt, 'Total' as stamp_type, sum(amount) as SumAmount from t
) b order by srt
try this code::
select stamp_type, sum(amount) amount
from tbl
group by stamp_type
union
select 'Total:' stamp_type,sum(amount) amount
from tbl;