SQL Server – Handling Large Schema Updates and Transaction Log Issues

You could initial load it in simple model. (as long as the load by itself isn't a multi step process where you want to be able to do a point in time restore).

Now after the load, it could be that your logfile has grown quite a bit if you had a long running transaction regardless of being in simple model. You can then shrink the log file.

Then you need to size the log file. A good starting point would be to check your largest table. If your in full recovery model, you'll need at least as much transaction log file space as your largest table. Since when you do regular index mantainance and you do a rebuild, the transaction log generated by the rebuild is about as much as your table. So sizing for your bigest table is a good start.

However, you'll see over time if your transaction record rate compared to your log backup frequency is making hte log file grow or not. You can either ajust the size of your log file or the frequency of your log backups.

Sizing up front is important. Having the file auto grow is a huge performance penalty, since the log file needs to be zero initialised. Remember, it always autogrows at the moment you are doing transactions, the transaction log writing is synchronous, so waiting for the autogrowth to finish is a direct wait on all pending transactions.

Then the auto grow option is also bad for the internal layout of your log file. see:

http://www.sqlskills.com/BLOGS/KIMBERLY/post/8-Steps-to-better-Transaction-Log-throughput.aspx

and:

http://www.sqlskills.com/BLOGS/KIMBERLY/post/Transaction-Log-VLFs-too-many-or-too-few.aspx

so properly sizing it up front will be best.

My first comment is that you are doing an ELT (Extract, Load, Transform) rather than an ETL (Extract, Transform, Load). While ELTs leverage set based relational advantages and can be very fast, they are sometimes very write intensive (hard on storage). Specifically, the t-log. This is because the transform is done on disk (typically an update or insert). I prefer ETL when possible, as the transform is done in the buffer and, when done correctly, requires minimal t-log writes. Buffer is cheap. Fast storage is not. For some bulk operations, the t-log is a non-value adding bottleneck.

Here are a few things that you're doing but I wouldn't recommend.

1. Bulk loading to tempdb. I'd recommend doing the bulk load on a real table in the destination database. Then you can size you're files accordingly and not worry about impacting tempdb.
2. Bundling independent procedures together. Split these two procedures up. The bulk load and the merge are independent of each other. Splitting them into individual procedures makes them more modular / unit testable.

It looks like you have the minimal logging rules covered pretty well. You're loading to an empty B-Tree with no non-clustereds, using tf 610, the ordering key specified, in bulk-logged mode. Outside of the temp table, everything looks ok here. As long as the file is actually ordered by the key, you should be good. Are you popping the log on tempdb or the user database?

On the merge statement:

UPDATES will always be fully logged. Are you changing a pretty significant portion of your table? If so, you might consider doing the merge in memory (SSIS data flow task or .Net) then bulk loading into a new table. This is more work, but most of the work is done in the buffer and minimal t-log is used. A minimally logged insert can be faster than a fully logged update if the portion of change is significant.

Since you're using tf 610, the insert can minimally log when using a tablock hint. See here for more info on merge with tablock: http://blogs.msdn.com/b/sqlserverstorageengine/archive/2010/06/03/minimal-logging-and-merge-statement.aspx Note, the update will still be fully logged if you go this route.