August 29, 2009 at 7:53 am
I am trying to import 650 million records from a table in a database that will eventually be removed from the server to a table in my database. I'm trying to use an OLE DB Source, with a query to get the records, and send it to an OLE DB Destination. I have set the connection property's packet size to 32,000 and set the rows per batch and max commit size if the OLE DB Destination to 100k each. My problem is that my memory of 60 gig is getting full and the process pretty much slows to a crawl. What can I do to correct this? I thought setting the max commit size and rows per batch would prevent this.
August 29, 2009 at 8:22 am
Maybe the initial fetch is causing problems.
Can you loop/batch the whole thing to SELECT and process x thousand rows at a time?
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August 29, 2009 at 8:26 am
unfortunately not. There is no column that I could use that way. I noticed that I didn't remove the index on the destination table, hopefully removing the index will make it run faster.
August 29, 2009 at 5:51 pm
dndaughtery (8/29/2009)
..I have set the connection property's packet size to 32,000 and set the rows per batch and max commit size if the OLE DB Destination to 100k each. My problem is that my memory of 60 gig is getting full and the process pretty much slows to a crawl. What can I do to correct this? I thought setting the max commit size and rows per batch would prevent this.
100,000 rows is a *very* large rows-per-batch and max-commit size. Remember that more than one batch may have to co-exists at the same time, both because clean-up/startup of each batch could overlap and because of the pipeline-processor's desire to try to run parallel streams (5 simultaneaous streams would not be odd, if you do not restrict it). 1000 is a more typical setting and 10k is usually considered the upper limit of workable settings.
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August 30, 2009 at 1:42 pm
Export in native format using BCP and then import it.
--Jeff Moden
Change is inevitable... Change for the better is not.
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