I need help writing a query to generate a summary file of quantity purchase per item, and per cost from a purchase history file. To run the query the ORDER BY would be ITEM_NO, PO_DATE, AND COST.
SAMPLE DATE - PURCHASE HISTORY
OUTPUT FILE - SUMMARY
We can group by item_no and cost and get all the info we need.
select item_no
,cost
,min(po_date) as start_date
,max(po_date) as end_date
,sum(qty) as qty
from (
select *
,count(chng) over(partition by item_no order by po_date) as grp
from (
select *
,case when lag(cost) over(partition by item_no order by po_date) <> cost then 1 end as chng
from t
) t
) t
group by item_no, cost, grp
order by item_no, start_date
item_no
cost
start_date
end_date
qty
12345
1.25
2021-01-02 00:00:00
2021-01-04 00:00:00
150
12345
2.00
2021-02-01 00:00:00
2021-02-03 00:00:00
60
78945
5.25
2021-06-10 00:00:00
2021-06-12 00:00:00
90
78945
4.50
2021-10-18 00:00:00
2021-10-19 00:00:00
150
Fiddle
Related
I have the next data: TABLE_A
RegisteredDate
Quantity
2022-03-01 13:00
100
2022-03-01 13:10
20
2022-03-01 13:20
-80
2022-03-01 13:30
-40
2022-03-02 09:00
10
2022-03-02 22:00
-5
2022-03-03 02:00
-5
2022-03-03 03:00
25
2022-03-03 03:20
-10
If I add cumulative column
select RegisteredDate, Quantity
, sum(Quantity) over ( order by RegisteredDate ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) as Summary
from TABLE_A
RegisteredDate
Quantity
Summary
2022-03-01 13:00
100
100
2022-03-01 13:10
20
120
2022-03-01 13:20
-80
40
2022-03-01 13:30
-40
0
2022-03-02 09:00
10
10
2022-03-02 22:00
-5
5
2022-03-03 02:00
-5
0
2022-03-03 03:00
25
25
2022-03-03 03:20
-10
15
Is there a way to get the following result with a query?
RegisteredDate
Quantity
Summary
2022-03-03 03:00
25
25
2022-03-03 03:20
-10
15
This result is the last records after the last zero.
EDIT:
Really for the solution to this problem I need the: 2022-03-03 03:00 is the first date of the last records after the last zero.
You can try to use SUM aggregate window function to calculation grp column which part represent to last value accumulated.
Query 1:
WITH cte AS
(
SELECT RegisteredDate,
Quantity,
sum(Quantity) over (order by RegisteredDate ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) as Summary
FROM TABLE_A
), cte2 AS (
SELECT *,
SUM(CASE WHEN Summary = 0 THEN 1 ELSE 0 END) OVER(order by RegisteredDate desc) grp
FROM cte
)
SELECT RegisteredDate,
Quantity
FROM cte2
WHERE grp = 0
ORDER BY RegisteredDate
Results:
| RegisteredDate | Quantity |
|----------------------|----------|
| 2022-03-03T03:00:00Z | 25 |
| 2022-03-03T03:20:00Z | -10 |
Use a CTE that returns the summary column and NOT EXISTS to filter out the rows that you don't need:
WITH cte AS (SELECT *, SUM(Quantity) OVER (ORDER BY RegisteredDate) Summary FROM TABLE_A)
SELECT c1.*
FROM cte c1
WHERE NOT EXISTS (
SELECT 1
FROM cte c2 WHERE c2.RegisteredDate >= c1.RegisteredDate AND c2.Summary = 0
)
ORDER BY c1.RegisteredDate;
There is no need for ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW in the OVER clause of the window function, because this is the default behavior.
See the demo.
Try this:
with u as
(select RegisteredDate,
Quantity,
sum(Quantity) over (order by RegisteredDate ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) as Summary
from TABLE_A)
select * from u
where RegisteredDate >= all(select RegisteredDate from u where Summary = 0)
and Summary <> 0;
Fiddle
Basically what you want is for RegisteredDate to be >= all RegisteredDatess where Summary = 0, and you want Summary <> 0.
When using window functions, it is necessary to take into account that RegisteredDate column is not unique in TABLE_A, so ordering only by RegisteredDate column is not enough to get a stable result on the same dataset.
With A As (
Select ROW_NUMBER() Over (Order by RegisteredDate, Quantity) As ID, RegisteredDate, Quantity
From TABLE_A),
B As (
Select A.*, SUM(Quantity) Over (Order by ID) As Summary
From A)
Select Top 1 *
From B
Where ID > (Select MAX(ID) From B Where Summary=0)
ID
RegisteredDate
Quantity
Summary
8
2022-03-03 03:00
25
25
I have query below as
select month, type, count(*) / sum(count(*)) over() as ratio
from
(
select
ID,
date_trunc('month',to_date(hour,'YYYYMMDDHH24')) as month,
timestamp,
from tbl
where hour between '2021060100' and '2021073123'
and (type IN('A','B') or type is null))
where type IN('A','B')
group by 1,2;
""")
Current output:
month | type | ratio
2021-06-01 A .60
2021-06-01 B .05
2021-07-01 A .30
2021-07-01 B .05
Desired Output:
month | type | ratio
2021-06-01 A .60
2021-06-01 B .40
2021-07-01 A .85
2021-07-01 B .15
Where I want desired output to show % of only that month, am I missing something? Thank you
I think you need to partition by month in your over:
select month, type, count(*) / sum(count(*)) over(partition by month)
Well, I have a seemingly simple set of data but it gives me a lot of trouble.
This is an example of what my data look like:
quantity price1 price2 date
100 1 0 2018-01-01 10:00:00
200 1 0 2018-01-02 10:00:00
50 5 0 2018-01-02 11:00:00
100 1 1 2018-01-03 10:00:00
100 1 1 2018-01-03 11:00:00
300 1 0 2018-01-03 12:00:00
I need to sum up "quantity" column grouped by "price1" and "price2" and it would be very easy but I need to take into account time changes of "price1" and "price2". Data is sorted by "date".
What I need is the last row to be not grouped with the first two although it has the same values for "price1" and "price2". Also I need to get minimal and maximal date of each interval.
The end result should looks like this:
quantity price1 price2 dateStart dateEnd
300 1 0 2018-01-01 10:00:00 2018-01-02 10:00:00
50 5 0 2018-01-02 11:00:00 2018-01-02 11:00:00
200 1 1 2018-01-03 10:00:00 2018-01-03 11:00:00
300 1 0 2018-01-03 12:00:00 2018-01-03 12:00:00
Any suggestions for a SQL query?
It is a gap and island problem. Use the following code:
select sum(quantity), price1, price2, min(date) dateStart, max(date) dateend
from
(
select *,
row_number() over (order by date) -
row_number() over (partition by price1, price2 order by date) grp
from data
) t
group by price1, price2, grp
order by dateStart
dbfiddle demo
The solution is based on an identification of consecutive sequences of price1 and price2, which is done by a creation of the grp column. Once you isolate the consecutive sequences then you do a simple group by using grp as well.
I changed a little bit the accepted answer to catch the cases when "date" column of two rows next to each other are exactly the same. I added second parameter so they will be ordered in correct order (my table has "oid" column)
select sum(quantity), price1, price2, min(date) dateStart, max(date) dateend
from
(
select *,
row_number() over (order by date, oid) -
row_number() over (partition by price1, price2 order by date, oid) grp
from data
) t
group by price1, price2, grp
order by dateStart
I need to aggregate Amounts to be displayed by date range per month. To illustrate please take a look at the following table:
Invoice_Payment
Customer_id Invoice_no Invoice_date Amount
---------------------------------------------------
10 10023 2016-07-08 60
10 10018 2016-08-04 90
11 10016 2016-07-01 110
11 10021 2016-07-05 120
12 10028 2016-07-11 10
12 10038 2016-07-31 5
As you'll notice, I want to group them based on Customer_id and display the dates from start to end. Furthermore, this has to be done for each month only.
Following query I have tried so far:
select Customer_id, (mindate + ' to ' + maxdate) Date_Range, Amount
from (
select Customer_id, sum(Amount) Amount, min(Invoice_date) mindate, max(Invoice_date) maxdate
from Invoice_Payment
group by Customer_id
) I ;
From above query I'm getting Output like:
Customer_id Date_Range Amount
10 2016-07-08 to 2016-08-04 150
11 2016-07-01 to 2016-07-05 230
12 2016-07-11 to 2016-07-31 15
Please check this.. SQL Fiddle Working Demo
Let's say Customer_id = 10 who has Invoice_date in July,2016 and August,2016. I need to sum up all payments of that particular Customer for the month of July and August separately within specific date range. But I am getting sum of Amount of all Invoice_date from above endeavor.
Desired output :
Customer_id Date_Range Amount
10 2016-07-08 to 2016-07-08 60
10 2016-08-04 to 2016-08-04 90
11 2016-07-01 to 2016-07-05 230
12 2016-07-11 to 2016-07-31 15
How could I get over this ? Any help would be greatly appreciated.
You are almost done. Just add YEAR and MONTH to GROUP BY.
select Customer_id, (mindate + ' to ' + maxdate) Date_Range, Amount
from (
select Customer_id,
sum(Amount) Amount, min(Invoice_date) mindate, max(Invoice_date) maxdate
from #Invoice_Payment
group by
Customer_id,
YEAR(Invoice_date),
MONTH(Invoice_date)
) I ;
How about grouping by customer_id, month and year
select Customer_id, (mindate + ' to ' + maxdate) Date_Range, Amount
from (
select Customer_id,
sum(Amount) Amount, min(Invoice_date) mindate, max(Invoice_date) maxdate
from #Invoice_Payment
group by Customer_id,month(Invoice_date), year(Invoice_date)
) I
order by customer_id;
I have the following data in my table:
id invoice_id date ammount
1 1 2012-01-01 100.00
20 1 2012-01-31 50.00
470 1 2012-01-15 300.00
Now, I need to calculate running total for an invoice in some period. So, the output for this data sample should look like this:
id invoice_id date ammount running_total
1 1 2012-01-01 100.00 100.00
470 1 2012-01-15 300.00 400.00
20 1 2012-01-31 50.00 450.00
I tried with this samples http://www.sqlusa.com/bestpractices/runningtotal/ and several others, but the problem is that I could have entries like id 20, date 2012-01-31 and id 120, date 2012-01-01, and then I couldn't use NO = ROW_NUMBER(over by date)... in first select and then ID < NO in second select for calculating running total.
DECLARE #DateStart DATE='2012-01-01';
WITH cte
AS (SELECT id = Row_number() OVER(ORDER BY [date]),
DATE,
myid = id,
invoice_id,
orderdate = CONVERT(DATE, DATE),
ammount
FROM [Table_2]
WHERE DATE >= #DateStart)
SELECT myid,
invoice_id,
DATE,
ammount,
runningtotal = (SELECT SUM(ammount)
FROM cte
WHERE id <= a.id)
FROM cte AS a
ORDER BY id