|By Hovhannes Avoyan||
|February 15, 2013 09:45 AM EST||
Stripe Unit Size
In part 4 of the storage subsystem, we’ll provide some guidelines for selecting the stripe-size unit for your selected storage solution. Hardware-managed arrays allow stripe unit sizes ranging from 4 KB to more than 1 MB. The ideal stripe unit size maximizes the disk activity without unnecessarily breaking up requests by requiring multiple disks to service a single request. For example, consider the following:
- One long stream of sequential requests on a JBOD configuration uses only one disk at a time. To keep all striped disks in use for such a workload, the stripe unit should be at least 1/n where n is the request size.
- For n streams of small serialized random requests, if n is significantly greater than the number of disks and if there are no hot spots, striping does not increase performance over a JBOD configuration. However, if hot spots exist, the stripe unit size must maximize the possibility that a request will not be split while it minimizes the possibility of a hot spot falling entirely within one or two stripe units. You might choose a low multiple of the typical request size, such as five times or ten times, especially if the requests are aligned on some boundary (for example, 4 KB or 8 KB).
- If requests are large, and the average or peak number of outstanding requests is smaller than the number of disks, you might need to split some requests across disks so that all disks are being used. You can interpolate an appropriate stripe unit size from the previous two examples. For example, if you have 10 disks and 5 streams of requests, split each request in half (that is, use a stripe unit size equal to half the request size). Note that this assumes some consistency in alignment between the request boundaries and the stripe unit boundaries.
- Optimal stripe unit size increases with concurrency and typical request sizes.
- Optimal stripe unit size decreases with sequentiality and with good alignment between data boundaries and stripe unit boundaries.
Using separate volumes for individual workloads can have some advantges. You can use one volume for the operating system or paging space and one or more volumes for shared user data, applications, and log files. The benefits include fault isolation, easier capacity planning, and easier performance analysis.
You can place different types of workloads into separate volumes on different physical disks. Using separate disks is especially important for any workload that creates heavy sequential loads (such as log files), where a single set of physical disks can be dedicated to handling the updates to the log files. Placing the page file on a separate virtual disk might provide some improvements in performance during periods of high paging.
There is also an advantage to combining workloads on the same physical disks, if the disks do not experience high activity over the same time period. This is basically the partnering of hot data with cold data on the same physical drives.
The “first” partition on a volume that is utilizing hard disks usually uses the outermost tracks of the underlying disks, and therefore it provides better performance. Obviously, this guidance does not apply to solid-state storage.
Choosing and Designing Storage Tiers
With the cost of solid state devices dropping, it is important to consider including multiple tiers of devices into a storage deployment to achieve better balance between performance, cost, and energy consumption. Traditional storage arrays offer the ability to aggregate and tier heterogenous storage, but Storage Spaces provides a more robust implementation.
Our next and final part of the storage subsystem in Windows Server 2012 discusses the Storage Related Performance Counters.
Oct. 25, 2016 06:15 PM EDT Reads: 2,119
Oct. 25, 2016 05:45 PM EDT Reads: 1,423
Oct. 25, 2016 05:15 PM EDT Reads: 1,605
Oct. 25, 2016 04:45 PM EDT Reads: 1,543
Oct. 25, 2016 03:15 PM EDT Reads: 396
Oct. 25, 2016 03:00 PM EDT Reads: 2,015
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Oct. 25, 2016 02:15 PM EDT Reads: 2,669
Oct. 25, 2016 01:30 PM EDT Reads: 2,699
Oct. 25, 2016 01:15 PM EDT Reads: 1,062
Oct. 25, 2016 12:45 PM EDT Reads: 4,950
Oct. 25, 2016 12:30 PM EDT Reads: 8,489
Oct. 25, 2016 11:45 AM EDT Reads: 3,821
Oct. 25, 2016 11:45 AM EDT Reads: 2,145
Oct. 25, 2016 11:42 AM EDT Reads: 254
Oct. 25, 2016 11:30 AM EDT Reads: 2,039
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Oct. 25, 2016 11:30 AM EDT Reads: 3,623
Oct. 25, 2016 11:15 AM EDT Reads: 3,928
Oct. 25, 2016 11:15 AM EDT Reads: 1,550