thank you for support

i need to get groups that have only one source as 484456

but groups have multi source i don't need it

so below

MNH32 5601 484456

KLMD33 5022 484456

must not display because it have...

thank you for reply

it not return my expected result above

please run that query

SELECT GivenPartNumber_Non,  vcompanyid int, SourceType

FROM #notmappedsources

WHERE SourceType = 484456

it will give rows extra as

MNH32 ...

ok thank you for support and help

create nonclustered index IDX_ZPLID on ExtractReports.dbo.TPls(ZPLID)

yes yes yes

can you please clarify that below

on diff note - avoid hardcoding dbnames (use synonyms instead) and remove the nolock - if your company is ok with its pitfalls then use...

output as below

CompanyIDYearRev_IDMetarialID1888574MetarialID1888575MetarialID1888576MetarialID1888577supplier1888574supplier1888575supplier1888576supplier1888577
1039109202133982083.1897.0592.8795.7480.1899.0094.8796.74
1039152202033989880.1810098.8793.7479.1899.0096.8790.74

my result will be

company and year and rev then pivot first Colum based on material id ,pivot second Colum based on material id

with another meaning

material...

thanks for  support and help

issue done where Name>1000

instead of

Name >'1000'

i need to make my code accept single quotes

when compare name with any value

DECLARE @ConStr nvarchar(max)=  STUFF((SELECT...

i try as below :

DECLARE @ConStr nvarchar(max)=  STUFF((SELECT CONCAT(' Or (PM.ZfeatureKey= ''', CC.ZfeatureKey , '''', IIF(CC.ZfeatureType='Qualifications',' And AcceptedValuesOption_Value ' , ' And Name ' ) ,...

can i do while loop to divide data

then insert to table

or this solution is bad

after create indexes

are there are any thing remaining can enhance performance

thank you for reply

I solve issue by adding

CREATE NONCLUSTERED INDEX IDX_EStrat ON ExtractReports.dbo.TGen(Zplid) include(EStrat);

thank you very much for support

thank you for reply

i need to generate id for two tables then join by id

so How to do that please ?

if i join hash to hash then for big data...