I have a lot of rows (300k+) to upsert into SQL server database in a shortest possible period of time, so the idea was to use parallelization and partition the data and use async to pump the data into SQL, X threads at the time, 100 rows per context, with context being recycled to minimize tracking overhead. However, that means more than one connection is to be used in parallel and thus CommittableTransaction
/TransactionScope
would use distributed transaction which would cause parallelized transaction enlistment operation to return the infamous "This platform does not support distributed transactions."
exception.
I do need the ability to commit/rollback the entire set of upserts. Its part of the batch upload process and any error should rollback the changes to previously working/stable condition, application wise.
What are my options? Short of using one connection and no parallelization?
Note: Problem is not so simple as a batch of insert commands, if that was the case, I would just generate inserts and run them on server as query or indeed use SqlBulkCopy
. About half of them are updates, half are inserts where new keys are generated by SQL Server which need to be obtained and re-keyed on child objects which would be inserted next, rows are spread over about a dozen tables in a 3-level hierarchy.