I have a table that contains Transactions of Customers.
I should Find Customers That had have at least 2 transaction with amount>20000 in Three consecutive days each month.
For example , Today is 2022/03/12 , I should Gather Data Of Transactions From 2022/02/13 To 2022/03/12, Then check These Data and See If a Customer had at least 2 Transaction With Amount>=20000 in Three consecutive days.
For Example, Consider Below Table:
Id
CustomerId
Transactiondate
Amount
1
1
2022-01-01
50000
2
2
2022_02_01
20000
3
3
2022_03_05
30000
4
3
2022_03_07
40000
5
2
2022_03_07
20000
6
4
2022_03_07
30000
7
4
2022_03_07
30000
The Out Put Should be : CustomerId =3 and CustomerId=4
I write query that Find Customer For Special day , but i don't know how to find these customers in one month with out using loop.
the query for special day is:
With cte (select customerid, amount, TransactionDate,Dateadd(day,-2,TransactionDate) as PrevDate
From Transaction
Where TransactionDate=2022-03-12)
Select CustomerId,Count(*)
From Cte
Where
TransactionDate>=Prevdate and TransactionDate<=TransactionDate
And Amount>=20000
Group By CustomerId
Having count(*)>=2
Hi there are many options how to achieve this.
I think that easies (from perfomance maybe not) is using LAG function:
WITH lagged_days AS (
SELECT
ISNULL(LAG(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id),
LEAD(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id)) lagged_dt
,*
FROM Transaction
), valid_cust_base as (
SELECT
*
FROM lagged_days
WHERE DATEPART(MONTH, lagged) = DATEPART(MONTH, Transactiondate)
AND datediff(day, Transactiondate, lagged_dt) <= 3
AND Amount >= 20000
)
SELECT
CustomerID
FROM valid_cust_base
GROUP BY CustomerID
HAVING COUNT(*) >= 2
First I have created lagged TransactionDate over customer (I assume that id is incremental). Then I have Selected only transactions within one month, with amount >= 20000 and where date difference between transaction is less then 4 days. Then just select customers who had more than 1 transaction.
In LAG First value is always missing per Customer missing, but you still need to be able say: 1st and 2nd transaction are within 3 days. Thats why I am replacing first NULL value with LEAD. It doesn't matter if you use:
ISNULL(LAG(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id),
LEAD(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id)) lagged_dt
OR
ISNULL(LEAD(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id),
LAG(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id)) lagged_dt
The main goal is to have for each transaction closest TransactionDate.
I'm trying to see the difference between the two periods for a column.
For example, we see that sales decreased at the end of the month, and we need to see which products were not sold at the end of the month?
I can create SELECT to see quantity for each product for each period:
SELECT product_id, count(product_id) AS Count
FROM testDB
WHERE
sales_date IS NOT NULL
AND
delivery_date BETWEEN '2021-02-01 00:00:03.0000000' AND '2021-02-14 23:56:00.0000000'
GROUP BY
product_id
and the same SELECT with another period:
delivery_date BETWEEN '2021-02-14 00:00:03.0000000' AND '2021-02-28 23:56:00.0000000'
So, after these queries I see list for first period with 10 products with quantity and in second period I see list with 7 products with quantity. I can't get the difference between the lists of the two SELECTs. I tried to use != and NOT IN but without any results.
I will be very grateful for your help. Thanks
Sorry for the confusion. I meant the difference between the two selects:
The result of the first one (for first period):
Product_ID Count
grapes. 100
lime. 13
lemon. 15
cherry. 222
blueberry. 123
banana. 1
apple. 123
watermelon 56
and second one (for second period):
Product_ID Count
grapes. 10
lime. 1
lemon. 10
cherry. 2
blueberry. 13
banana. 12
and I wand to see difference between these selects:
Product_ID Count
apple. 0
watermelon. 0
So we did not sell any apples and watermelons in second period.
SELECT product_id, count(product_id) AS Count,delivery_date-sales_date as DIFFERENCE
FROM testDB
WHERE
sales_date IS NOT NULL
AND
delivery_date BETWEEN '2021-02-01 00:00:03.0000000' AND '2021-02-14 23:56:00.0000000'
GROUP BY
product_id
This should work for getting the difference between the 2 period columns.
How can I update date column of a table in a database(mssql) by 1 year for 1st 1000 data, 2 year for 2nd 1000 data and so on... I know how to implement it by assigning temporary id but is there a way to update data in a loop manner??
for example:
suppose if I have 6000 datas in table with joined_date column in range from 2012-01-01 to 2017-01-01 ordered in ascending order, I want to update first thousand rows increasing it by 1 year, 2nd thousand rows by 1 year as well and so on...
If my first thousand data contain joined date on year 2012, I want to update it to 2013 and if my 2nd thousand data contain joined date on year 2012 to 2013 then I want to increment it by 1 as well.
We can try assigning a row number to your table, then use it to do the updates:
WITH cte AS (
SELECT joined_date, ROW_NUMBER() OVER (ORDER BY joined_date) - 1 rn
FROM yourTable
)
UPDATE cte
SET joined_date = DATEADD(year, (rn % 1000) + 1, joined_date);
The trick here is that the first 1000 rows, which would receive a row number of 0 up to and including 999, would have an rn % 1000 value of 0, to which we add 1 to get the number of years to add. The next 1000 records would have 2 years added, and so on.
I have a list of accounts and their cost which changes every few days.
In this list I only have the start date every time the cost updates to a new one, but no column for the end date.
Meaning, I need to populate a list of dates when the end date for a specific account and cost, should be deduced as the start date of the same account with a new cost.
More or less like that:
Account start date cost
one 1/1/2016 100$
two 1/1/2016 150$
one 4/1/2016 200$
two 3/1/2016 200$
And the result I need would be:
Account date cost
one 1/1/2016 100$
one 2/1/2016 100$
one 3/1/2016 100$
one 4/1/2016 200$
two 1/1/2016 150$
two 2/1/2016 150$
two 3/1/2016 200$
For example, if the cost changed in the middle of the month, than the sample data will only hold two records (one per each unique combination of account-start date-cost), while the results will hold 30 records with the cost for each and every day of the month (15 for the first cost and 15 for the second one). The costs are a given, and no need to calculate them (inserted manually).
Note the result contains more records because the sample data shows only a start date and an updated cost for that account, as of that date. While the results show the cost for every day of the month.
Any ideas?
Solution is a bit long.
I added an extra date for test purposes:
DECLARE #t table(account varchar(10), startdate date, cost int)
INSERT #t
values
('one','1/1/2016',100),('two','1/1/2016',150),
('one','1/4/2016',200),('two','1/3/2016',200),
('two','1/6/2016',500) -- extra row
;WITH CTE as
( SELECT
row_number() over (partition by account order by startdate) rn,
*
FROM #t
),N(N)AS
(
SELECT 1 FROM(VALUES(1),(1),(1),(1),(1),(1),(1),(1),(1),(1))M(N)
),
tally(N) AS -- tally is limited to 1000 days
(
SELECT ROW_NUMBER()OVER(ORDER BY N.N) - 1 FROM N,N a,N b
),GROUPED as
(
SELECT
cte.account, cte.startdate, cte.cost, cte2.cost cost2, cte2.startdate enddate
FROM CTE
JOIN CTE CTE2
ON CTE.account = CTE2.account
and CTE.rn = CTE2.rn - 1
)
-- used DISTINCT to avoid overlapping dates
SELECT DISTINCT
CASE WHEN datediff(d, startdate,enddate) = N THEN cost2 ELSE cost END cost,
dateadd(d, N, startdate) startdate,
account
FROM grouped
JOIN tally
ON datediff(d, startdate,enddate) >= N
Result:
cost startdate account
100 2016-01-01 one
100 2016-01-02 one
100 2016-01-03 one
150 2016-01-01 two
150 2016-01-02 two
200 2016-01-03 two
200 2016-01-04 one
200 2016-01-04 two
200 2016-01-05 two
500 2016-01-06 two
Thank you #t-clausen.dk!
It didn't solve the problem completely, but did direct me in the correct way.
Eventually I used the LEAD function to generate an end date for every cost per account, and then I was able to populate a list of dates based on that idea.
Here's how I generate the end dates:
DECLARE #t table(account varchar(10), startdate date, cost int)
INSERT #t
values
('one','1/1/2016',100),('two','1/1/2016',150),
('one','1/4/2016',200),('two','1/3/2016',200),
('two','1/6/2016',500)
select account
,[startdate]
,DATEADD(DAY, -1, LEAD([Startdate], 1,'2100-01-01') OVER (PARTITION BY account ORDER BY [Startdate] ASC)) AS enddate
,cost
from #t
It returned the expected result:
account startdate enddate cost
one 2016-01-01 2016-01-03 100
one 2016-01-04 2099-12-31 200
two 2016-01-01 2016-01-02 150
two 2016-01-03 2016-01-05 200
two 2016-01-06 2099-12-31 500
Please note that I set the end date of current costs to be some date in the far future which means (for me) that they are currently active.
This is the input table:
Customer_ID Date Amount
1 4/11/2014 20
1 4/13/2014 10
1 4/14/2014 30
1 4/18/2014 25
2 5/15/2014 15
2 6/21/2014 25
2 6/22/2014 35
2 6/23/2014 10
There is information pertaining to multiple customers and I want to get a rolling sum across a 3 day window for each customer.
The solution should be as below:
Customer_ID Date Amount Rolling_3_Day_Sum
1 4/11/2014 20 20
1 4/13/2014 10 30
1 4/14/2014 30 40
1 4/18/2014 25 25
2 5/15/2014 15 15
2 6/21/2014 25 25
2 6/22/2014 35 60
2 6/23/2014 10 70
The biggest issue is that I don't have transactions for each day because of which the partition by row number doesn't work.
The closest example I found on SO was:
SQL Query for 7 Day Rolling Average in SQL Server
but even in that case there were transactions made everyday which accomodated the rownumber() based solutions
The rownumber query is as follows:
select customer_id, Date, Amount,
Rolling_3_day_sum = CASE WHEN ROW_NUMBER() OVER (partition by customer_id ORDER BY Date) > 2
THEN SUM(Amount) OVER (partition by customer_id ORDER BY Date ROWS BETWEEN 2 PRECEDING AND CURRENT ROW)
END
from #tmp_taml9
order by customer_id
I was wondering if there is way to replace "BETWEEN 2 PRECEDING AND CURRENT ROW" by "BETWEEN [DATE - 2] and [DATE]"
One option would be to use a calendar table (or something similar) to get the complete range of dates and left join your table with that and use the row_number based solution.
Another option that might work (not sure about performance) would be to use an apply query like this:
select customer_id, Date, Amount, coalesce(Rolling_3_day_sum, Amount) Rolling_3_day_sum
from #tmp_taml9 t1
cross apply (
select sum(amount) Rolling_3_day_sum
from #tmp_taml9
where Customer_ID = t1.Customer_ID
and datediff(day, date, t1.date) <= 3
and t1.Date >= date
) o
order by customer_id;
I suspect performance might not be great though.