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Batching large data sets into smaller data sets, e.g. 100,000 rows or 1,000,000 rows will make the load run better than One Big Insert. But the same is true from SSIS, of course, as it batches inserts. The difference in time that you show in your example is fairly small. That does not give much hope for great speed improvements, but it does encourage you ...


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Can you confirm with a Profiler trace which credentials are attempting to execute sp_start_job? I'm curious if it's the credentials of the client using the browser or the underlying application pool. If the account in question has sysadmin, it should already have the permissions to execute jobs.


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I have a Credential running under a generic (AD) domain account. I changed the password last week. That broke the SSIS jobs. Updating the password fixed it.


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The semaphore timeout period has expired" is a Network error Network issues between the source server and the server running SSIS? A look in the Windows System logs of both machines might provide more information about any network issues. You will probably also find the specific windows error number, which will help in your research. Locking/blocking ...


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Ensure you have the right extension and path to the directory set in your variables within each object including the whereloop and connection file. *.xls versus *.xls*


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The more SSISic way of doing this would be through Expressions. Despite seeing multiple variables here, don't worry about them. I have found that when people try to do too much with an Expression, diagnosing and debugging bad logic will leave you reaching for the nearest blunt object. Variables FlatFileConnection, string. Value = ...


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Have you tried just adding the extension to the variable like this? sFlatFileConnection = sFlatFileConnection + dtRunDate.ToString("yyyy_MM_dd") + '.txt';



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