Traditionally questions about how much memory SQL Server needs were aimed at how to appropriately set the ‘max server memory’ sp_configure option in SQL Server, and in my book the recommendation that I make is to reserve 1 GB of RAM for the OS, 1 GB for each 4 GB of RAM installed from 4–16 GB, and then 1 GB for every 8 GB RAM installed above 16 GB RAM. Then monitor the Memory\Available MBytes performance counter in Windows to determine if you can increase the memory available to SQL Server above the starting value. (Note: This counter should remain above the 150-300MB at a bare minimum, Windows signals the LowMemoryResourceNotification at 96MB so you want a buffer, but I typically like it to be above 1GB on larger servers with 256GB or higher RAM) This has typically worked out well for servers that are dedicated to SQL Server. You can also get much more technical with determining where to set ‘max server memory’ by working out the specific memory requirements for the OS, other applications, the SQL Server thread stack, and other multipage allocators. Typically this would be ((Total system memory) – (memory for thread stack) – (OS memory requirements ~ 2-4GB) – (memory for other applications) – (memory for multipage allocations; SQLCLR, linked servers, etc)), where the memory for thread stack = ((max worker threads) *(stack size)) and the stack size is 512KB for x86 systems, 2MB for x64 systems and 4MB for IA64 systems. The value for ‘max worker threads’ can be found in the max_worker_count column of sys.dm_os_sys_info. However, the assumption with either of these methods is that you want SQL Server to use everything that is available on the machine, unless you’ve made reservations in the calculations for other applications.
As more shops move towards virtualizing SQL Servers in their environment this question is more and more geared towards determining what is the minimum amount of memory that a SQL Server will need to run as a VM. Unfortunately there is no way to calculate out what the ideal amount of RAM for a given instance of SQL Server might actually be since SQL Server is designed to cache data in the buffer pool, and it will typically use as much memory as you can give it. One of the things to keep in mind when you are looking at reducing the RAM allocated to a SQL Server instance is that you will eventually get to a point where the lower memory gets traded off for higher disk I/O access in the environments.
If you need to figure out the ideal configuration for SQL Server memory in an environment that has been over provisioned the best way to try to go about doing this is start off with a baseline of the environment and the current performance metrics. Counters to begin monitoring would include:
- SQL Server:Buffer Manager\Page Life Expectancy
- SQL Server:Buffer Manager\Page reads/sec
- Physical Disk\Disk Reads/sec
Typically if the environment has excess memory for the buffer pool, the Page Life Expectancy value will continue to increase by a value of one every second and it won’t typically drop off under the workload because all of the data pages end up being cached. At the same time, the number of SQL Server:Buffer Manager\Page reads/sec will be low after the cache ramp up occurs which will also correspond to a low value for Physical Disk\Disk Reads/sec.
Once you have your baseline for the environment, make a change to the sp_configure ‘max server memory’ option to reduce the size of the buffer pool by 1GB and then monitor the impact to the performance counters after things stabilize from the initial cache flushing that may typically occur when RECONFIGURE is run in the environment. If the level of Page Life Expectancy remains acceptable for your environment (keeping in mind that a fixed target of >= 300 is ridiculous for servers with large amounts of RAM installed), and the number of SQL Server:Buffer Manager\Page reads/sec is within what the disk I/O subsystem can support without performance degradation, repeat the process of reducing the sp_configure value for ‘max server memory’ by 1GB and continuing to monitor the impact to the environment.