Question

This is going to be my first attempt at fine tuning our SQL Server 2008R2, and I’d like a starting point based on the following.

When I view the resource monitor, I see (in KB):
Commit: 843,948
Working Set: 718,648
Shareable: 26,276
Private: 692,372

Out of 2 gigs available on our virtual server, 1.6 is getting used up, and I suspect it is due SQL Server, and the memory gets chewed up when I initiate a service that does a bunch of TVP inserts and checks. I already added some GC.collect() in my c# service, however I’m not really seeing much of a change, which leads me back to the SQL Server.

Where would be a good starting point for me to learn more about optimizing based on this information, and some quick pointers?

Thanks.

Answer 1

Here is a quick pointer: buy more memory. 2GB is nothing today.

For the long answer: you need to understand how SQL Server allocates and uses memory. 1.6Gb on a 2Gb box is perfectly normal. See Dynamic Memory Management:

When SQL Server starts, it computes the size of virtual address space
for the buffer pool based on a number of parameters such as amount of
physical memory on the system, number of server threads and various
startup parameters. SQL Server reserves the computed amount of its
process virtual address space for the buffer pool, but it acquires
(commits) only the required amount of physical memory for the current
load.

The instance then continues to acquire memory as needed to support the
workload. As more users connect and run queries, SQL Server acquires
the additional physical memory on demand. A SQL Server instance
continues to acquire physical memory until it either reaches its max
server memory allocation target or Windows indicates there is no
longer an excess of free memory; it frees memory when it has more than
the min server memory setting, and Windows indicates that there is a
shortage of free memory.

In other words, SQL Server will not release the 1.6Gb unless there is memory pressure notification from Windows.

And finally, about your question on where to look for info on optimizations: Waits and Queues is an excellent resource. It is a methodology that allows you to identify the bottlenecks and recommends the appropriate action for all common bottleneck cases.