This section explains the differences between random I/O and sequential I/O, and DiskSuite strategies for optimizing your particular configuration.
What is random I/O?
Databases and general-purpose file servers are examples of random I/O environments. In random I/O, the time spent waiting for disk seeks and rotational latency dominates I/O service time.
Why do I need to know about random I/O?
You can optimize the performance of your configuration to take advantage of a random I/O environment.
What is the general strategy for configuring for a random I/O environment?
You want all disk spindles to be busy most of the time servicing I/O requests. Random I/O requests are small (typically 2-8 Kbytes), so it's not efficient to split an individual request of this kind onto multiple disk drives.
The interlace size doesn't matter, because you just want to spread the data across all the disks. Any interlace value greater than the typical I/O request will do.
For example, assume you have 4.2 Gbytes DBMS table space. If you stripe across four 1.05-Gbyte disk spindles, and if the I/O load is truly random and evenly dispersed across the entire range of the table space, then each of the four spindles will tend to be equally busy.
The target for maximum random I/O performance on a disk is 35 percent or lower as reported by DiskSuite Tool's performance monitor, or by iostat(1M). Disk use in excess of 65 percent on a typical basis is a problem. Disk use in excess of 90 percent is a major problem.
If you have a disk running at 100 percent and you stripe the data across four disks, you might expect the result to be four disks each running at 25 percent (100/4 = 25 percent). However, you will probably get all four disks running at greater than 35 percent since there won't be an artificial limitation to the throughput (of 100 percent of one disk).
While most people think of disk I/O in terms of sequential performance figures, only a few servers--DBMS servers dominated by full table scans and NFS servers in very data-intensive environments--will normally experience sequential I/O.
Why do I need to know about sequential I/O?
You can optimize the performance of your configuration to take advantage of a sequential I/O environment.
The goal in this case is to get greater sequential performance than you can get from a single disk. To achieve this, the stripe width should be "small" relative to the typical I/O request size. This will ensure that the typical I/O request is spread across multiple disk spindles, thus increasing the sequential bandwidth.
What is the general strategy for configuring for a sequential I/O environment?
You want to get greater sequential performance from an array than you can get from a single disk by setting the interlace value small relative to the size of the typical I/O request.
max-io-size / #-disks-in-stripe
Example:
Assume a typical I/O request size of 256 Kbyte and striping across 4 spindles. A good choice for stripe unit size in this example would be:
256 Kbyte / 4 = 64 Kbyte, or smaller
Seek and rotation time are practically non-existent in the sequential case. When optimizing sequential I/O, the internal transfer rate of a disk is most important.
The most useful recommendation is: max-io-size / #-disks. Note that for UFS file systems, the maxcontig parameter controls the file system cluster size, which defaults to 56 Kbyte. It may be useful to configure this to larger sizes for some sequential applications. For example, using a maxcontig value of 12 results in 96 Kbyte file system clusters (12 * 8 Kbyte blocks = 96 Kbyte clusters). Using a 4-wide stripe with a 24 Kbyte interlace size results in a 96 Kbyte stripe width (4 * 24 Kbyte = 96 Kbyte) which is a good performance match.
Example: In sequential applications, typical I/O size is usually large (greater than 128 Kbyte, often greater than 1 Mbyte). Assume an application with a typical I/O request size of 256 Kbyte and assume striping across 4 disk spindles. Do the arithmetic: 256 Kbyte / 4 = 64 Kbyte. So, a good choice for the interlace size would be 32 to 64 Kbyte.
Number of stripes: Another way of looking at striping is to first determine the performance requirements. For example, you may need 10.4 Mbyte/sec performance for a selected application, and each disk may deliver approximately 4 Mbyte/sec. Based on this, then determine how many disk spindles you need to stripe across:
10.4 Mbyte/sec / 4 Mbyte/sec = 2.6
Therefore, 3 disks would be needed.