Preparing Rules Based List for Promotions - sql
I am trying to put together a promotions list based on a set of rules
In table #productdetail I need to pick up items that have available =1 or available =2 and expected <=08052019 and not_sellable =0
From #product table I need to join id with pid in #productdetail and coalesce (vendor_id to get the vendor_id
Using the vendor_id that I have got from the step above i need to get the vendorname from #vendor table..
From the #Asin table I need to select the latest lastconfirmedasin from the list of items selected in step 1 and also ensure that I should not pick up data from rows where disable =1
From the #pageviews table I need to get the number of pageviews perday for every item based on the lastconfirmedasin for the list of items selected in step 1
Here for every item if I have datetype =day and also datetype =month then I need to select data from datetype =day and select sum(pageviews)/count of days to get the sum of pageviews per day
Also if I have only datetype =month then I need to select (sum(pageviews)(count of rows that have month)/30
Then in the promo table I need to select the average promo% got for the items selected in step 1..The average promo% is calculated as avg((pre_promo_price-promo_price)/promo_price*100))...This will be calculated at the vendor level...So if the vendor has 3 items then the average promo% is calculated as avg([avg((pre_promo_price-promo_price)/promo_price*100)
Then the cost is taken based on if in the table #promo has the date in between or included in promo_start and promo_end (for example today's date being 08/16/2019 is included then the pre promo cost is to taken as the cost for that item otherwise the cost from #product_detail table should be taken
Then I am calculating the priority of the items by vendor(meaning within each vendor ) prioritizing the items based on the power(calculated as pageviewsperday*price)-Higher value of an item within a vendor gets the first priority
The tables:
create table #productdetail
(
itemid int,
available int,
expected date,
isnotsellable int,
pid int,
vendor_id varchar(50),
cost float,
price float)
insert into #productdetail values
('123','1',NULL,'1','1','201','180','200'),
('125','2','08/05/2019','0','1','NULL','40','60'),
('127','1',NULL,'0','1','201','60','80'),
('129','2',NULL,'0','2','203','80','100'),
('131','1',NULL,'0','2','203','70','90'),
('133','1',NULL,'1','2','203','90','110'),
('135','1',NULL,'0','7','206','110','130'),
('137','1',NULL,'0','8','207','120','140'),
('139','1',NULL,'0','8','207','30','50'),
('141','1',NULL,'0','8','207','40','60'),
('143','1',NULL,'0','11','210','60','80'),
('145','1',NULL,'0','11','210','70','90'),
('147','1',NULL,'1','11','210','50','70'),
('149','1',NULL,'0','11','210','20','40'),
('151','1',NULL,'0','15','211','30','50'),
('153','1',NULL,'0','16','NULL','40','60'),
('155','2','08/29/2019','1','15','211','60','80'),
('157','2','08/04/2019','1','18','216','30','50'),
('159','2','08/06/2019','0','19','217','20','40'),
('161','2','08/03/2019','0','20','218','60','80'),
('163','2','08/15/2019','0','21','NULL','90','110')
create table #product
(id int,
vendor_id varchar(50)
)
insert into #product values
('1','201'),
('1','201'),
('1','201'),
('2','203'),
('2','203'),
('2','203'),
('7','NULL'),
('8','207'),
('8','207'),
('8','207'),
('11','210'),
('11','210'),
('11','210'),
('11','210'),
('15','211'),
('15','211'),
('15','211'),
('16','206'),
('18','216'),
('19','NULL'),
('20','218'),
('21','219')
create table #vendor
(vendor_id varchar(50),
vendorname varchar(50)
)
insert into #vendor values
('201','cola'),
('203','foam'),
('207','fill'),
('210','falon'),
('211','chiran'),
('216','Hummer'),
('218','sulps'),
('219','culp'),
('217','jko'),
('206','JINCO')
create table #asin
(disable int,
item_id int,
lastconfirmed datetime2,
lastconfirmedasin varchar(50)
)
insert into #asin values
('0','123','12/19/18 10:19 PM','iopyu'),
('1','123','12/19/16 10:19 PM','hjyug'),
('1','125','5/19/19 10:19 PM','uirty'),
('0','125','12/19/16 10:19 PM','1yuio'),
('0','127','2/19/19 10:19 PM','klbnm'),
('1','127','12/19/18 10:19 PM','lopgh'),
('0','127','12/19/16 10:19 PM','nmbh'),
('0','129','11/19/16 10:19 PM','jklh'),
('0','131','11/19/19 10:19 PM','werat'),
('1','133','6/19/19 10:19 PM','vbnwe'),
('0','133','1/19/19 10:19 PM','mnwer'),
('0','133','11/19/17 10:19 PM','sdert'),
('0','135','6/19/19 10:19 PM','vbsdx'),
('0','137','6/19/17 10:19 PM','bnxct')
create table #pageviews
(startdate date,
lastconfirmedasin varchar(50),
noofpageviews int,
datetype varchar(20))
insert into #pageviews values
('05/08/2017','hjyug','102','day'),
('09/05/2017','hjyug','201','day'),
('10/05/2019','hjyug','1002','day'),
('09/05/2018','iopyu','345','month'),
('10/06/2018','iopyu','545','month'),
('06/05/2019','1yuio','300','day'),
('06/06/2019','1yuio','200','day'),
('09/04/2019','uirty','150','day'),
('11/4/2019','uirty','200','day'),
('12/4/2019','nmbh','300','day'),
('04/15/2019','lopgh','400','day'),
('04/15/2019','klbnm','500','day'),
('04/16/2019','klbnm','1000','day'),
('04/15/2019','jklh','600','day'),
('04/15/2019','werat','700','day'),
('04/15/2019','sdert','800','day'),
('04/15/2019','mnwer','900','day'),
('04/15/2019','vbnwe','1000','day'),
('04/15/2019','vbsdx','1100','day'),
('04/25/2019','vbsdx','3000','day'),
('04/15/2019','bnxct','1200','month'),
('05/31/2019','bnxct','2200','month'),
('04/16/2019','bnxct','90','day'),
('04/17/2019','bnxct','100','day'),
('04/18/2019','bnxct','120','day')
create table #promo
(itemid int,
promo_cost float,
pre_promo_cost float,
promo_start varchar(50),
promo_end varchar(50))
insert into #promo values
('123','214.7','220','10/08/2019','22/08/2019'),
('123','225','230','01/02/2018','15/02/2018'),
('125','400','430','12/08/2019','19/08/2019'),
('125','380','390','15/02/2019','30/02/2019'),
('127','120','140','15/03/2019','30/03/2019'),
('129','80','100','15/04/2019','30/04/2019'),
('129','110','120','01/04/2019','10/04/2019'),
('131','80','100','01/02/2019','15/02/2019'),
('131','110','120','10/01/2019','15/01/2019'),
('133','230','420','10/01/2019','15/01/2019'),
('135','250','440','10/01/2019','15/01/2019'),
('137','270','460','10/01/2019','15/01/2019'),
('139','290','480','10/01/2019','15/01/2019'),
('141','310','500','10/01/2019','15/01/2019'),
('143','330','520','10/01/2019','15/01/2019'),
('145','350','540','10/08/2019','22/08/2019')
create table #output
(itemid int,
available int,
expected date,
isnotsellable int,
pid int,
vendor_id varchar(50),
vendorname varchar(50),
lastconfirmedasin varchar(50),
pageviewsperday int,
promoavg float,
cost float,
price float,
[power] int,
[priority] int)
insert into #output values
('151','1',NULL,'0','15','211','chiran','','0','0','30','50','0','1'),
('127','1',NULL,'0','1','201','cola','klbnm','750','6.3','60','80','60000','1'),
('125','2','08/05/2019','0','1','201','cola','','0','0','430','60','0','2'),
('143','1',NULL,'0','11','210','falon','','0','0','60','80','0','1'),
('145','1',NULL,'0','11','210','falon','','0','0','540','90','0','2'),
('149','1',NULL,'0','11','210','falon','','0','0','20','40','0','3'),
('137','1',NULL,'0','8','207','fill','bnxct','103','65.73','120','140','14420','1'),
('139','1',NULL,'0','8','207','fill','','0','0','30','50','0','2'),
('141','1',NULL,'0','8','207','fill','','0','0','40','60','0','3'),
('131','1',NULL,'0','2','203','foam','werat','700','30.16','70','90','63000','1'),
('135','1',NULL,'0','7','206','JINCO','vbsdx','2050','76','110','130','266500','1'),
('153','1',NULL,'0','16','206','JINCO','','0','0','40','60','0','2'),
('161','2','08/03/2019','0','20','218','sulps','','0','0','60','80','0','1')
Code tried:
; WITH firstsel AS (
SELECT itemid, available, expected, isnotsellable, pid, vendor_id
FROM #productdetail
WHERE available = 1
AND isnotsellable = 0
UNION ALL
SELECT itemid, available, expected, isnotsellable, pid, vendor_id
FROM #productdetail
WHERE available = 2
AND isnotsellable = 0
AND expected <= '20190805'
), addvendorid AS (
SELECT fs.itemid, fs.available, fs.expected, fs.pid, fs.isnotsellable,
coalesce(fs.vendor_id, p.vendor_id) AS vendor_id
FROM firstsel fs
JOIN #product p ON fs.pid = p.id
), asinnumbered AS (
SELECT item_id, lastconfirmedasin, row_number() OVER (PARTITION BY item_id ORDER BY lastconfirmedasin DESC) AS rowno
FROM #asin
)
SELECT av.itemid, av.available, av.expected, av.isnotsellable, av.pid,
av.vendor_id, v.vendorname, an.lastconfirmedasin,
isnull(pv.pageviews, 0) AS pageviews, isnull(p.promoavg, 0) AS promoavg
FROM addvendorid av
JOIN #vendor v ON av.vendor_id = v.vendor_id
LEFT JOIN (asinnumbered an
JOIN (SELECT lastconfirmedasin, SUM(pageviews) AS pageviews
FROM #pageviews
GROUP BY lastconfirmedasin) AS pv ON an.lastconfirmedasin = pv.lastconfirmedasin)
ON an.item_id = av.itemid
AND an.rowno = 1
LEFT JOIN (SELECT itemid, avg((pre_promo_price-promo_price)/promo_price*100) AS promoavg
FROM #promo
GROUP BY itemid) AS p ON p.itemid = av.itemid
ORDER BY av.itemid
Related
Insert into 2 different data to 2 table at the same time using first data's id
I have 2 tables: Order and product_order. Every order has some product in it and that's because I store products another table. Table Order: Id name Table PRODUCT_ORDER: id product_id order_id Before I start to insert, I don't know what the Order Id is. I want to insert the data into both tables at once and I need the order id to do that. Both id's are auto incremented. I'm using SQL Server. I can insert first order and then find the id of the order and than execute the second insert, but I want to do these both to execute at once.
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Dale is correct. You cannot insert into multiple tables at once, but if you use a stored procedure to handle your inserts, you can capture the ID and use it in the next insert. -- table definitions create table [order]([id] int identity, [name] nvarchar(100)) go create table [product_order]([id] int identity, [product_id] nvarchar(100), [order_id] int) go -- stored procedure to handle inserts create procedure InsertProductWithOrder( #OrderName nvarchar(100), #ProductID nvarchar(100)) as begin declare #orderID int insert into [order] ([name]) values(#OrderName) select #orderID = ##identity insert into [product_order]([product_id], [order_id]) values(#ProductID, #orderID) end go -- insert records using the stored procedure exec InsertProductWithOrder 'Order ONE', 'AAAAA' exec InsertProductWithOrder 'Order TWO', 'BBBBB' -- verify the results select * from [order] select * from [product_order]
Trying to aggregate quantities across multiple tables SQL
I'm building a stock synch which compares product quantities from three different tables: EWM USOR DSOR The maths behind the stock synch is EWM - (USOR + DSOR) = Misalignment The EWM table divides the product quantities by the different storage types that products are held in which necessitates the need to have the quantities aggregated before being used in the end query but I keep getting the wrong figure after aggregating the quantities so I think I'm doing something wrong but I can't seem to spot it. Here's my code: --Table for EWM Data-- create table EWM( Date_loaded date, Sap_code bigint, Product_description varchar(100), Location nvarchar(50), Storage_type varchar(50), Quantity int, Sap_batch nvarchar(50), Expiry_date date, Stock_type varchar(50) ); --Table for USOR Data-- create table USOR( Date_Loaded date, Sap_Code bigint, Product_description varchar(100), Pack nvarchar(50), Cost_price decimal, Trade_price decimal, Stock int, Location nvarchar(50), ); --Table for DSOR-- create table DSOR( Date_Loaded datetime, Sap_code bigint, Product_description varchar(100), Bin_location nvarchar(50), Location varchar(50), Pack nvarchar(50), Units int, Total int, ); --Table for difference between EWM and USOR+DSOR-- create table Misalignment ( Date_loaded date, Sap_code bigint, Product_description varchar(100), Pack nvarchar(50), Location nvarchar(50), Total_difference int ) --Inserting data in Misalingment using query from USOR, USOR_DSOR, EWM -- WITH x AS ( SELECT SAP_Code, Quantity FROM EWM GROUP BY SAP_Code, Quantity ) insert into Misalignment(Date_Loaded, Sap_code, Product_description, Location, Total_difference) Select USOR.Date_Loaded, USOR.Sap_Code, USOR.Product_description, USOR.Location, sum(x.Quantity - (USOR.stock + DSOR.Total))as Total_difference FROM x INNER JOIN USOR ON x.SAP_Code = USOR.SAP_Code INNER JOIN DSOR ON x.SAP_Code = DSOR.SAP_Code group by USOR.Date_Loaded, USOR.Sap_Code, USOR.Product_description, USOR.Pack, USOR.Location select * from Misalignment where Total_difference > 0 order by Total_difference desc I ran the query below to test my code out: select * from ewm where Date_loaded = '2020-10-05' and Sap_code = 1002945 select * from DSOR where Sap_code = 1002945 and Date_loaded= '2020-10-05' select * from Misalignment where Sap_code = 1002945 and Date_loaded = '2020-10-05' This was the result: The actual result should be 0. Any suggestions?
Is there any way to speed up this query capturing customer information? Is there a better method for this data?
I have a long query but I'll try to break it down into it's parts.
First, there are the variables,
DECLARE #LocalCompanyCode VARCHAR(5)
SET #LocalCompanyCode = '09'
DECLARE #LocalDivisionCode VARCHAR(5)
SET #LocalDivisionCode = '001'
DECLARE #CustomerBaseFromDate DATETIME --CustomerBase
SET #CustomerBaseFromDate = '1/1/2019'
DECLARE #CustomerBaseToDate DATETIME
SET #CustomerBaseToDate = '5/30/2019'
DECLARE #RecurringBaseFromDate DATETIME --Recurring Base
SET #RecurringBaseFromDate = '1/1/2018'
DECLARE #RecurringBaseToDate DATETIME
SET #RecurringBaseToDate = '1/1/2019'
DECLARE #LifetimeBaseFromDate DATETIME --Lifetime Base
SET #LifetimeBaseFromDate = '1/1/2015'
DECLARE #LifetimeBaseToDate DATETIME
SET #LifetimeBaseToDate = '1/1/2018'
Company Code and Division Code select which Company we are running this query for. Customer Base will be the base of customers that we will be looking at. So in our example, it is the past 5 months.
So for all customers in the past 5 months, we will look in our Recurring Base. This is modular so we can control what time before we consider a customer "lost". We will compare against the recurring base and see how many customers are new customers who only ordered once over the customer and recurring base, and how many customers are recurring customers, those who ordered multiple times over those periods.
Then we will also have our Lifetime base. We will check customers who ordered once or more in our lifetime base, did not order in our recurring base, but did order again in our 5 months customer base. This calculates how many customers are "Reactivated" or were considered lost but bought with us again recently.
Then I declare the four tables
DECLARE #FullBase TABLE
(
Date_Created DATE,
Company_Code VARCHAR(2),
Division_Code VARCHAR(3),
Invoice_Number VARCHAR(50),
CUST_PO VARCHAR(50),
Total_Quantity NUMERIC,
TotalPrice MONEY,
City VARCHAR(50),
State VARCHAR(50),
Zip VARCHAR(50),
CountryCode VARCHAR(50),
Month NUMERIC,
CustomerEmail VARCHAR(MAX),
OrderCountBase NUMERIC,
TotalOrdersBase NUMERIC
)
DECLARE #LifetimeBase TABLE
(
Date_Created DATE,
Company_Code VARCHAR(2),
Division_Code VARCHAR(3),
Invoice_Number VARCHAR(50),
CUST_PO VARCHAR(50),
Total_Quantity NUMERIC,
TotalPrice MONEY,
City VARCHAR(50),
State VARCHAR(50),
Zip VARCHAR(50),
CountryCode VARCHAR(50),
Month NUMERIC,
CustomerEmail VARCHAR(MAX),
OrderCountLifetimeBase NUMERIC,
TotalOrdersLifetimeBase NUMERIC
)
DECLARE #RecurringBase TABLE
(
Date_Created DATE,
Company_Code VARCHAR(2),
Division_Code VARCHAR(3),
Invoice_Number VARCHAR(50),
CUST_PO VARCHAR(50),
Total_Quantity NUMERIC,
TotalPrice MONEY,
City VARCHAR(50),
State VARCHAR(50),
Zip VARCHAR(50),
CountryCode VARCHAR(50),
Month NUMERIC,
CustomerEmail VARCHAR(MAX),
OrderCountRecurringBase NUMERIC,
TotalOrdersRecurringBase NUMERIC
)
DECLARE #CustomerBase TABLE
(
Date_Created DATE,
Company_Code VARCHAR(2),
Division_Code VARCHAR(3),
Invoice_Number VARCHAR(50),
CUST_PO VARCHAR(50),
Total_Quantity NUMERIC,
TotalPrice MONEY,
City VARCHAR(50),
State VARCHAR(50),
Zip VARCHAR(50),
CountryCode VARCHAR(50),
Month NUMERIC,
CustomerEmail VARCHAR(MAX),
OrderCountCustomerBase NUMERIC,
TotalOrdersCustomerBase NUMERIC
)
Then I insert all of our customers into the "FullBase", from the beginning of the Lifetime Base, to the end of the Customer Base
INSERT INTO #FullBase
SELECT Orders.Date_Created
,Orders.Company_Code
,Orders.Division_Code
,Orders.Invoice_Number
,Orders.CUST_PO
,Orders.Total_Quantity
,Orders.Total
,Orders.City
,Orders.State
,Orders.Zip
,Orders.CountryCode
,Orders.Month
,Orders.CustomerEmail
,Row_Number() over (partition by CustomerEmail order by Date_Created asc) OrderCountBase
,Count(*) over (partition by CustomerEmail) TotalOrdersBase
FROM(
Select
CONVERT(Date, OrderCreated) Date_Created
,CONCAT ('0', LEFT(OrderName,1)) Company_Code
,CONCAT ('00', RIGHT(LEFT(OrderName,2),1)) Division_Code
,InvoiceNumber Invoice_Number
,OrderName CUST_PO
,1 Total_Quantity
,TotalPrice Total
,ShippingCity City
,CASE WHEN ShippingCountryCode <> 'US' THEN 'INT' ELSE ShippingProvinceCode END State
,ShippingZip Zip
,ShippingCountryCode CountryCode
,Month( OrderCreated) Month
,Email CustomerEmail
From [SHOPIFY].[shopify_moret].[dbo].orderwrappers O
Where CONVERT(Date, O.OrderCreated) >= Convert(datetime, '05/29/2019')
AND CONCAT ('0', LEFT(O.OrderName,1)) = #LocalCompanyCode--'09'
AND CONCAT ('00', RIGHT(LEFT(O.OrderName,2),1)) = #LocalDivisionCode --'001'
UNION
Select
Archive.Date_Created
,Archive.Company_Code
,Archive.Division_Code
,Archive.Invoice_Number
,('91'+Archive.CUST_PO) CUST_PO
,Archive.Total_Quantity
,Archive.Total
,Archive.City
,Archive.State
,Archive.Zip
,Archive.Country
,Archive.Month
,Archive.CustomerEmail
FROM SpraygroundArchivedOrders Archive
Where Archive.Date_Created < Convert(datetime, '05/29/2019')
) Orders
Where Orders.Date_Created BETWEEN #LifetimeBaseFromDate AND #CustomerBaseToDate
Here is an example of how the data looks like:
https://docs.google.com/spreadsheets/d/1wnjVHcPHHnugywa7Qz-aqctaD4cDI5DxehNna0TyaFU/edit?usp=sharing
Then I use this full base to populate the three other tables with orders from their range.
INSERT INTO #LifetimeBase
SELECT
F.Date_Created
,F.Company_Code
,F.Division_Code
,F.Invoice_Number
,F.CUST_PO
,F.Total_Quantity
,F.TotalPrice
,F.City
,F.State
,F.Zip
,F.CountryCode
,F.Month
,F.CustomerEmail
,Row_Number() over (partition by CustomerEmail order by Date_Created asc) OrderCountLifetimeBase
,Count(*) over (partition by CustomerEmail) TotalOrdersLifetimeBase
FROM #FullBase F
Where F.Date_Created BETWEEN #LifetimeBaseFromDate AND #LifetimeBaseToDate
INSERT INTO #RecurringBase
SELECT
F.Date_Created
,F.Company_Code
,F.Division_Code
,F.Invoice_Number
,F.CUST_PO
,F.Total_Quantity
,F.TotalPrice
,F.City
,F.State
,F.Zip
,F.CountryCode
,F.Month
,F.CustomerEmail
,Row_Number() over (partition by CustomerEmail order by Date_Created asc) OrderCountRecurringBase
,Count(*) over (partition by CustomerEmail) TotalOrdersRecurringBase
FROM #FullBase F
Where F.Date_Created BETWEEN #RecurringBaseFromDate AND #RecurringBaseToDate
INSERT INTO #CustomerBase
SELECT
F.Date_Created
,F.Company_Code
,F.Division_Code
,F.Invoice_Number
,F.CUST_PO
,F.Total_Quantity
,F.TotalPrice
,F.City
,F.State
,F.Zip
,F.CountryCode
,F.Month
,F.CustomerEmail
,Row_Number() over (partition by CustomerEmail order by Date_Created asc) OrderCountCustomerBase
,Count(*) over (partition by CustomerEmail) TotalOrdersCustomerBase
FROM #FullBase F
Where F.Date_Created BETWEEN #CustomerBaseFromDate AND #CustomerBaseToDate
If I just select * from an of the bases, including the full base, the query only takes a few seconds to run and returns 140,000 rows (for the #FullBase) of all customer orders.
However, the final part of this query, which is the part that runs, takes 10 minutes to run for my 6 months of customers
SELECT
CC.CustomerEmail
,CC.TotalOrdersCustomerBase
,RC.TotalOrdersRecurringBase
,LC.TotalOrdersLifetimeBase
From
(
SELECT DISTINCT
C.CustomerEmail
,C.TotalOrdersCustomerBase
FROM
#CustomerBase C
) CC
LEFT JOIN
(
SELECT DISTINCT
R.CustomerEmail
,R.TotalOrdersRecurringBase
FROM
#RecurringBase R
) RC ON CC.CustomerEmail = RC.CustomerEmail
LEFT JOIN
(
SELECT DISTINCT
L.CustomerEmail
,L.TotalOrdersLifetimeBase
FROM
#LifetimeBase L
) LC ON CC.CustomerEmail = LC.CustomerEmail
Does anyone have any tips for me at all? Is there any better way to do this?
Fetch single data from table in sql?
I have three tables in my SQL Server 1.) Registration it's columns Reg_Id bigint, primary key and auto increment Name nvarchar(50), Tranx_id nvarchar(30), Email nvarchar(30), Username nvarchar(30), Password nvarchar(30), Edition_Id nvarchar(50), Default_Id nvarchar(50), Reg_Date datetime, usertype nvarchar(50), 2.) AllEditionPages it's columns Page_id bigint, primary key and auto increment edition_date datetime, noofpages int, Page_no int, image_path nvarchar(50), Active int, type_of_page varchar(50), Image_Width int, Image_Height int, 3.) Edition id int, primary key and auto increment edition_date datetime, noofpages int, XMLFile nvarchar(50), PDFFile nvarchar(50), PDFPrefix nvarchar(50), type nvarchar(50), price nvarchar(50), reg_req nvarchar(50) As per above table I try below sql query SELECT edi.*, aep.*, reg.* FROM Edition as edi INNER JOIN Registration as reg ON edi.id = reg.Edition_Id INNER JOIN AllEditionPages as aep ON edi.edition_date = aep.edition_date where reg.Edition_Id= edi.id and reg.Reg_ID = 14 From this query I get this output: id edition_date type price page-id 96 2012-07-18 00:00:00.000 free null 2503 96 2012-07-18 00:00:00.000 free null 2503 I get in output two rows, but want only single row in output
You can use common table expression in this scenario in following way: WITH cteTable AS ( SELECT edi.*, aep.*, reg.* FROM Edition as edi INNER JOIN Registration as reg ON edi.id = reg.Edition_Id INNER JOIN AllEditionPages as aep ON edi.edition_date = aep.edition_date where reg.Edition_Id= edi.id and reg.Reg_ID = 14 ) select top 1 * from cteTable As you two table contains edition_date, you need to spcify the column name instead of using "*" in following way: WITH cteTable AS ( SELECT edi.id,edi.edition_date,edi.noofpagez,edi.XMLFile,edi.PDFFile ,edi.PDFPrefix,edi.type,edi.price,edi.reg_req , aep.Page_id, aep.edition_date,aep.noofpages,aep.Page_no,aep.image_path,aep.Active,aep.type_of_page,aep.Image_Width,aep.Image_Height, reg.Reg_Id,reg.Name,reg.Tranx_id,reg.Email,reg.Username,reg.Password,reg.Edition_Id,reg.Default_Id,reg.Reg_Date,reg.usertype FROM Edition as edi INNER JOIN Registration as reg ON edi.id = reg.Edition_Id INNER JOIN AllEditionPages as aep ON edi.edition_date = aep.edition_date where reg.Edition_Id= edi.id and reg.Reg_ID = 14 ) select top 1 * from cteTable
You have to specify one row.From your putput it looks like you have duplicate data and if that is the issue you should use distinct to get distinct rows..Otherwise specify what exactly you need.
You can use select distinct if the 2 rows have the same value, or you can simple use LIMIT 0,1 behind your query.
group by clause
i have a table called table1 and it has following columns. suppose there are records like localamount is 20,000, 30000,50000, 100000 then as per my condition i have to delete records from this table according to the group by set of site id, till id, transid,shift id where localamount exceeds 10,000... the rest of the records can be available? my aim is to delete rows from this table where local amount is exceeds 10,0000 according to site id, till id, transid,shift id SiteId varchar(10), TillId tinyint, ShiftId int, TransId int, TranDate datetime, SettlementType varchar(5), CreditCardNumber varchar(25), ProductTypeCode varchar(10), NewProductTypeCode varchar(10), TransactionType int, ForeignAmount money, LocalAmount money, ProductCode varchar(10)
Im not sure I understand what you are saying, but couldn't you do this without a group by? delete from table1 where LocalAmount > 10,0000[sic] and SiteId = whatever and TillId = whatever... obviously take the [sic] out...
Assuming you want to delete the whole group where the sum is > 10000 ;with cte as ( select sum(localamount) over (partition by siteid, tillid, transid,shiftid) as l, * from table1 ) delete from cte where l>10000