Note: I have tried to simplify the below to make it simpler both for me and for anyone else to understand, the tables I reference below are in fact sub-queries joining a lot of different data together from different sources)
I have a table of purchased items:
Items
ItemSaleID CustomerID ItemCode
1 100 A
2 100 B
3 100 C
4 200 A
5 200 C
I also have transaction header and detail tables coming from a till system:
TranDetail
TranDetailID TranHeaderID ItemSaleID Cost
11 51 1 $10
12 51 2 $10
13 51 3 $10
14 52 4 $20
15 52 5 $10
TranHeader
TranHeaderID CustomerID Payment Time
51 100 $100 11:00
52 200 $50 12:00
53 100 $20 13:00
I want to get to a point where I have a table like:
ItemSaleID CustomerID ItemCode Cost Payment Time
1 100 A $10 $120 11:00
2 100 B $10 11:00
3 100 C $10 11:00
4 200 D $20 $50 12:00
5 200 E $10 12:00
I have a query which produces the results but when I add in the ROW_NUMBER() case statement goes from 2 minutes to 30+ minutes.
The query is further confused because I need to supply the earliest date relating to the list of transactions and the total price paid (could be many transactions throughout the day for upgrades etc)
Query below:
SELECT ItemSaleID
, CustomerID
, ItemCode
, Cost
, CASE WHEN ROW_NUMBER() OVER (PARTITION BY TranHeaderID ORDER BY ItemSaleID) = 1
THEN TRN.Payment ELSE NULL END AS Payment
FROM Items I
OUTER APPLY (
SELECT TOP 1 SUB.Payment, Time
FROM TranHeader H
INNER JOIN TranDetail D ON H.TranHeaderID = D.TranHeaderID
OUTER APPLY (SELECT SUM(Payment) AS Payment
FROM TranHeader H2
WHERE H2.CustomerID = Items.CustomerID
) SUB
WHERE D.CustomerID = I.CustomerID
) TRN
WHERE ...
Is there a way that I can only show payments for each occurrence of the customer ID whilst maintaining performance
Related
My table looks like the following:
income
date
productid
invoiceid
customerid
300
2015-01-01
A
1234551
1
300
2016-01-02
A
1234552
1
300
2016-01-03
B
1234553
2
300
2016-01-03
A
1234553
2
300
2016-01-04
C
1234554
3
300
2016-01-04
C
1234554
3
300
2016-01-08
A
1234556
3
300
2016-01-08
B
1234556
3
300
2016-01-11
C
1234557
3
I need to know : Number of invoices per customer, how many customers in total (for example one invoice = several customers, two invoices = two customers, three invoices = three customers, and so..).
What is the syntax for this query?
In my sample data above, customer 1 has two invoices, customer 2 one invoice and customer 3 three invoices. So there is one customer each with a count of 1, 2, and 3 invoices in my example.
Expected result:
invoice_count
customers_with_this_invoice_count
1
1
2
1
3
1
I tried this syntax and I'm still stuck:
select * from
(
select CustomerID,count(distinct InvoiceID) as 'Total Invoices'
from exam
GROUP BY CustomerID
) a
Select Count(customerID),CustomerID From a
Group By customerID
Having Count(customerID) > 1
I have been searching the forum and found a single post that is a little smilair to my problem here: Calculate average for Top n combined with SQL Group By.
My situation is:
I have a table tblWEIGHT that contains: ID, Date, idPONR, Weight
I have a second table tblSALES that contains: ID, Date, Sales, idPONR
I have a third table tblPONR that contains: ID, PONR, idProduct
And a fouth table tblPRODUCT that contais: ID, Product
The linking:
tblWEIGHT.idPONR = tblPONR.ID
tblSALES.idPONR = tblPONR.ID
tblPONR.idProduct = tblPRODUCT.ID
The maintable of my query is tblSALES. I want to all my sales listed, with the moving average of the top5
weights of the PRODUCT where the date of the weight is less than the sales date, and the product is the same as the sold product. Its IMPORTANT that the result isn't grouped by the date. I need all the records of tblSALES.
i have gotten as far as to get the top 1 weight, but im not able to get the moving average instread.
The query that gest the top 1 is the following, and i am guessing that the query i need is going to look a lot like it.
SELECT tblSALES.ID, tblSALES.Dato, tblPONR.idPRODUCT,
(
SELECT top 1 Weight FROM tblWEIGHT INNER JOIN tblPONR ON tblWeight.idPONR = tblPONR.ID
WHERE tblPONR.idPRODUCT = idPRODUCT AND
SALES.Date > tblWEIGHT.Date
ORDER BY tblWEIGHT.Date desc
) AS LatestWeight
FROM tblSALES INNER JOIN VtblPONR ON tblSALES.idPONR = tblPONR.ID
this is not my exact query since im danish and i wouldnt make sense. I know im not supposed to use Date as a fieldname.
i imagine the filan query would be something like:
SELECT tblSALES.ID..... avg(SELECT TOP 5 weight .........)
but doing this i keep getting error at max 1 record can be returned by this subquery
Final Question.
How do i make a query that creates a moving average of the top 5 weights of my sold product, where the date of the weight is earlier than the date i sold the product?
EDIT Sampledata:
DATEFORMAT: dd/mm/yyyy
tblWEIGHT
ID Date idPONR Weight
1 01-01-2020 1 100
2 02-01-2020 2 200
3 03-01-2020 3 200
4 04-01-2020 3 400
5 05-01-2020 2 250
6 06-01-2020 1 150
7 07-01-2020 2 200
tblSALES
ID Date Sales(amt) idPONR
1 05-01-2020 30 1
2 06-01-2020 15 2
3 10-01-2020 20 3
tblPONR
ID PONR(production Number) idProduct
1 2521 1
2 1548 1
3 5484 2
tblPRODUCT
ID Product
1 Bricks
2 Tiles
Desired outcome read comments for AvgWeight
tblSALES.ID tblSALES.Date tblSales.Sales(amt) AvgWeigt
1 05-01-2020 30 123 -->avg(top 5 newest weight of both idPONR 1 And 2 because they are the same product, and where tblWeight.Date<05-01-2020)
2 06-01-2020 15 123 -->avg(top 5 newest weight of both idPONR 1 And 2 because they are the same product, and where tblWeight.Date<06-01-2020)
3 10-01-2020 20 123 -->avg(top 5 newest weight of idPONR 3 since thats the only idPONR with that product, and where tblWeight.Date<10-01-2020)
Consider:
Query1
SELECT tblWeight.ID AS WeightID, tblWeight.Date AS WtDate,
tblWeight.idPONR, tblPONR.PONR, tblPONR.idProduct, tblWeight.Weight, tblSales.SalesAmt,
tblSales.ID AS SalesID, tblSales.Date AS SalesDate
FROM (tblPONR INNER JOIN tblWeight ON tblPONR.ID = tblWeight.idPONR)
INNER JOIN tblSales ON tblPONR.ID = tblSales.idPONR;
Query2
SELECT * FROM Query1 WHERE WeightID IN (
SELECT TOP 5 WeightID FROM Query1 AS Dupe WHERE Dupe.idProduct = Query1.idProduct
AND Dupe.WtDate<Query1.SalesDate ORDER BY Dupe.WtDate);
Query3
SELECT Query2.SalesID, Query2.SalesDate, Query2.SalesAmt,
First(DAvg("Weight","Query2","idProduct=" & [idProduct] & " AND WtDate<#" & [SalesDate] & "#")) AS AvgWt
FROM Query2
GROUP BY Query2.SalesID, Query2.SalesDate, Query2.SalesAmt;
I want a select query that returns me all rows for the current day, only if the 'amount' is different that the previous days.
sales
-id
-user_id
-amount
-datetime
The sales table gets a new record for each user_id daily.
An example scenerio would be as follows:
5 123 700 2017/01/05
4 123 500 2017/01/04
3 123 1500 2017/01/03
2 123 1500 2017/01/02
1 123 500 2017/01/01
So if you search for records on the Jan. 5th, you will get 1 row since it is different that the previous days (700 vs 500).
result:
5 123 700 2017/01/05
But if you were run the query on the 3rd, since the amound $1500 is the same as on the 2nd, you will get 0 results back.
I have this basic join but I need to somehow compare the current days row from s1 and compare that with the previous days amount value.
select s1.*
from sales as s1
inner join sales s2 on s1.user_id = s2.user_id and s1.datetime = s2.datetime
You basically have the query. You just need the date arithmetic:
select s.*
from sales s left join
sales sprev
on sprev.user_id = s.user_id and sprev.datetime = dateadd(day, -1, s.datetime)
where s.datetime = '2018-01-05' and
(s.amount <> sprev.amount or sprev.amount is null);
Please consider the following payment data:
customerID paymentID pamentType paymentDate paymentAmount
---------------------------------------------------------------------
1 1 A 2015-11-28 500
1 2 A 2015-11-29 -150
1 3 B 2016-03-07 300
2 4 A 2015-03-03 200
2 5 B 2016-05-25 -100
2 6 C 2016-06-24 700
1 7 B 2015-09-22 110
2 8 B 2016-01-03 400
I need to tally per year, per customer, the sum of the diverse payment types (A = invoice, B = credit note, etc), as follows:
year customerID paymentType paymentSum
-----------------------------------------------
2015 1 A 350 : paymentID 1 + 2
2015 1 B 110 : paymentID 7
2015 1 C 0
2015 2 A 200 : paymentID 4
2015 2 B 0
2015 2 C 0
2016 1 A 0
2016 1 B 300 : paymentID 3
2016 1 C 0
2016 2 A 0
2016 2 B 300 : paymentID 5 + 8
2016 2 C 700 : paymentId 6
It is important that there are values for every category (so for 2015, customer 1 has 0 payment value for type C, but still it is good to see this).
In reality, there are over 10 payment types and about 30 customers. The total date range is 10 years.
Is this possible to do in only SQL, and if so could somebody show me how? If possible by using relatively easy queries so that I can learn from it, for instance by storing intermediary result into a #temptable.
Any help is greatly appreciated!
a simple GROUP BY with SUM() on the paymentAmount will gives you what you wanted
select year = datepart(year, paymentDate),
customerID,
paymentType,
paymentSum = sum(paymentAmount)
from payment_data
group by datepart(year, paymentDate), customerID, paymentType
This is a simple query that generates the required 0s. Note that it may not be the most efficient way to generate this result set. If you already have lookup tables for customers or payment types, it would be preferable to use those rather than the CTEs1 I use here:
declare #t table (customerID int,paymentID int,paymentType char(1),paymentDate date,
paymentAmount int)
insert into #t(customerID,paymentID,paymentType,paymentDate,paymentAmount) values
(1,1,'A','20151128', 500),
(1,2,'A','20151129',-150),
(1,3,'B','20160307', 300),
(2,4,'A','20150303', 200),
(2,5,'B','20160525',-100),
(2,6,'C','20160624', 700),
(1,7,'B','20150922', 110),
(2,8,'B','20160103', 400)
;With Customers as (
select DISTINCT customerID from #t
), PaymentTypes as (
select DISTINCT paymentType from #t
), Years as (
select DISTINCT DATEPART(year,paymentDate) as Yr from #t
), Matrix as (
select
customerID,
paymentType,
Yr
from
Customers
cross join
PaymentTypes
cross join
Years
)
select
m.customerID,
m.paymentType,
m.Yr,
COALESCE(SUM(paymentAmount),0) as Total
from
Matrix m
left join
#t t
on
m.customerID = t.customerID and
m.paymentType = t.paymentType and
m.Yr = DATEPART(year,t.paymentDate)
group by
m.customerID,
m.paymentType,
m.Yr
Result:
customerID paymentType Yr Total
----------- ----------- ----------- -----------
1 A 2015 350
1 A 2016 0
1 B 2015 110
1 B 2016 300
1 C 2015 0
1 C 2016 0
2 A 2015 200
2 A 2016 0
2 B 2015 0
2 B 2016 300
2 C 2015 0
2 C 2016 700
(We may also want to play games with a numbers table and/or generate actual start and end dates for years if the date processing above needs to be able to use an index)
Note also how similar the top of my script is to the sample data in your question - except it's actual code that generates the sample data. You may wish to consider presenting sample code in such a way in the future since it simplifies the process of actually being able to test scripts in answers.
1CTEs - Common Table Expressions. They may be thought of as conceptually similar to temp tables - except we don't actually (necessarily) materialize the results. They also are incorporated into the single query that follows them and the whole query is optimized as a whole.
Your suggestion to use temp tables means that you'd be breaking this into multiple separate queries that then necessarily force SQL to perform the task in an order that we have selected rather than letting the optimizer choose the best approach for the above single query.
I have the following tables.
Accounts(account_number*,balance)
Transactions(account_number*,transaction_number*,date,amount,type)
Date is the date that the transaction happened. Amount is the amount of the transaction
and it can have a positive or a negative value, dependent of the type(Withdrawal -,Deposit +). I think the type is irrelevant here as the amount is already given in the proper way.
I need to write a query which points out the account_number of the accounts that have at least once had negative balance.
Here's some sample data from the Transactions table, ordered by account_number and date.
account_number transaction_number date amount type
--------------------------------------------------------------------
1 2 02/03/2013 -20000 withdrawal
1 3 03/15/2013 300 deposit
1 1 01/01/2013 100 deposit
2 1 04/15/2013 235236 deposit
3 1 06/15/2013 500 deposit
4 1 03/01/2013 10 deposit
4 2 04/01/2013 80 deposit
5 1 11/11/2013 10000 deposit
5 2 12/11/2013 20000 deposit
5 3 12/13/2013 -10002 withdrawal
6 1 03/15/2013 102300 deposit
7 1 03/15/2013 100 deposit
8 1 08/08/2013 133990 deposit
9 1 05/09/2013 10000 deposit
9 2 06/01/2013 300 deposit
9 3 10/11/2013 23 deposit
Something like this with an analytic to keep a running balance for an account:
SELECT DISTINCT account_number
FROM ( SELECT account_number
,SUM(amount)
OVER (PARTITION BY account_number ORDER BY date) AS running_balance
FROM transactions
) x
WHERE running_balance < 0
Explanation:
It is using an analytic function: the PARTITION BY breaks the table into groups identified by the account number. Within each group, the data is ordered by date. Then there is a walk through each element in the ordered group and the SUM function is applied (by default summing everything from the beginning of the group to the current row). This gives you a running balance. Just run the inner query on its own and take a look at the output, then read a bit about analytic queries. They are pretty cool.