DATEADD With SYSUTCDATETIME

Aaron Bertrand blogs on an estimation failure with DATEADD and SYSDATETIME/SYSUTCDATETIME:

Essentially, the problem is that a poor estimate can be made not simply when SYSDATETIME() (or SYSUTCDATETIME()) appears, as Erland originally reported, but when any datetime2expression is involved in the predicate (and perhaps only when DATEADD() is also used). And it can go both ways – if we swap >= for <=, the estimate becomes the whole table, so it seems that the optimizer is looking at the SYSDATETIME() value as a constant, and completely ignoring any operations like DATEADD() that are performed against it.

Paul shared that the workaround is simply to use a datetime equivalent when calculating the date, before converting it to the proper data type. In this case, we can swap outSYSUTCDATETIME() and change it to GETUTCDATE()

I suppose switching to GETUTCDATE isn’t too much of a loss, but it looks like (according to Paul White in the second linked Connect item) this appears to have been fixed in SQL Server 2014.

Getting The Last Row Per Group

Daniel Hutmacher wants to get the last element in each group (for example, the current records in a type-two dimension):

The CROSS APPLY and the old-school solutions are by far the best choice for dense indexes, i.e. when the first column has a low degree of uniqueness. The old-school solution is only that fast because the optimizer short-circuits the query plan.

LEAD() and the old school strategy are best for selective indexes, i.e. when the first column is highly unique.

There’s a nice set of options available so if one doesn’t work well with your particular data set, try out some of the others and see if they work for you.

Transaction Log Analysis

Michael Swart shows how to dig into the transaction log to trace down those WRITELOG waits:

WRITELOG waits are a scalability challenge for OLTP workloads under load. Chris Adkin has a lot of experience tuning SQL Server for high-volume OLTP workloads. So I’m going to follow his advice when he writes we should minimize the amount logging generated. And because I can’t improve something if I can’t measure it, I wonder what’s generating the most logging? OLTP workloads are characterized by frequent tiny transactions so I want to measure that activity without filters, but I want to have as little impact to the system as I can. That’s my challenge.

Check out the entire post, as this is a good exercise in investigating busy transactional systems.

Extended Events In Azure SQL Database

Julie Koesmarno walks through Extended Events in Azure SQL Database (currently in preview):

Extended Event (XEvent) feature is available as public preview in Azure SQL Database as announcedhere. XEvent supports 3 types of targets – File Target (writes to Azure Blob Storage), Ring Buffer and Event Counter. Once we’ve created an event session, how do we inspect the event session target properties? This blog post describes how to do this in 2 ways: using the User Interface in SSMS and using T-SQL.

It’s nice to see Extended Events making their way into Azure SQL Database.

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