使用sys.dm_io_virtual_file_stats了解你的数据库IO

因为sys.dm_io_virtual_file_stats返回数据和日志文件的 I/O 统计信息，包括对文件发出的读取/写入次数以及总字节数，所以这个函数既可以看到IOPS也可以看到吞吐量，还可以计算出单个IO的大小。另外也可以看到IO的等待时间。能够帮助我们很好的了解数据库的IO状况。

配合Perfmon一起使用可以很快的找到IO瓶颈。

下面的文章来自微软的以为高级工程师：

http://blogs.msdn.com/b/dpless/archive/2010/12/01/leveraging-sys-dm-io-virtual-file-stats.aspx

One of the DMVs I try to utilize on any engagement where customers are complaining about disk issues is the sys.dm_io_virtual_file_stats DMV where you can look at the IO stalls for both reads and writes. The sys.dm_io_virtual_file_stats DMV will show an IO Stall when any wait occurs to access a physical data file. IO Stalls are recorded at the file level and you can also obtain the IO Stalls at the database level directly out of the DMV.

By getting this information it is very easy to ORDER BY io_stall_read_ms, io_stall_write_ms, or by io_stall which is an accumulation of reads and writes.

One addition step I have made in the script below is mapping to the sys.master_files catalog view and using the substring function to get the physical disk drive letter. You will now be able to see IO Stall activity at the file, database, and the drive letter. You can then use Reporting Services or simply use Excel to get a quick view of which of these is absorbing most of the IO Stall impact.

If you use Excel 2007, one of the interesting strategies is to use the Chart Advisor from Live Labs.
http://www.officelabs.com/projects/chartadvisor/Pages/default.aspx

This analysis can help make decisions around table partitioning and potentially file and index placement. Of course, this will all depend on the customer's SAN and other constraints.

Note: Mount points will make getting the drive letter less effective. If you are using mount points then just ignore the drive letter column.

SELECT a.io_stall, a.io_stall_read_ms, a.io_stall_write_ms, a.num_of_reads,
a.num_of_writes,
--a.sample_ms, a.num_of_bytes_read, a.num_of_bytes_written, a.io_stall_write_ms,
( ( a.size_on_disk_bytes / 1024 ) / 1024.0 ) AS size_on_disk_mb,
db_name(a.database_id) AS dbname,
b.name, a.file_id,
db_file_type = CASE
WHEN a.file_id = 2 THEN'Log'
ELSE 'Data'
END,
UPPER(SUBSTRING(b.physical_name, 1, 2))AS disk_location
FROM sys.dm_io_virtual_file_stats (NULL, NULL) a
JOIN sys.master_files bONa.file_id = b.file_id
AND a.database_id = b.database_id
ORDER BY a.io_stall DESC

For those looking at disk issues, I have pasted the general guidance on the avg. reads/sec and avg. writes/sec values for perfmon. By using the script above and the guidance here on perfmon, you should be able to take the next steps in addressing disk performance issues with your customers.

I/O Bottlenecks

SQL Server performance depends heavily on the I/O subsystem. Unless your database fits into physical memory, SQL Server constantly brings database pages in and out of the buffer pool. This generates substantial I/O traffic. Similarly, the log records need to be flushed to the disk before a transaction can be declared committed. And finally, SQL Server uses TempDB for various purposes such as to store intermediate results, to sort, to keep row versions and so on. So a good I/O subsystem is critical to the performance of SQL Server.

Access to log files is sequential except when a transaction needs to be rolled back while access to data files, including TempDB, is randomly accessed. So as a general rule, you should have log files on a separate physical disk than data files for better performance. The focus of this paper is not how to configure your I/O devices but to describe ways to identify if you have I/O bottleneck. Once an I/O bottleneck is identified, you may need to reconfigure your I/O subsystem.
If you have a slow I/O subsystem, your users may experience performance problems such as slow response times, and tasks that abort due to timeouts.
You can use the following performance counters to identify I/O bottlenecks. Note, these AVG values tend to be skewed (to the low side) if you have an infrequent collection interval. For example, it is hard to tell the nature of an I/O spike with 60-second snapshots. Also, you should not rely on one counter to determine a bottleneck; look for multiple counters to cross check the validity of your findings.

• Physical Disk Object: Avg. Disk Queue Length represents the average number of physical read and write requests that were queued on the selected physical disk during the sampling period. If your I/O system is overloaded, more read/write operations will be waiting. If your disk queue length frequently exceeds a value of 2 during peak usage of SQL Server, then you might have an I/O bottleneck.
• Avg. Disk Sec/Read is the average time, in seconds, of a read of data from the disk. Any number:
  • Less than 10 ms - very good
  • Between 10 - 20 ms - okay
  • Between 20 - 50 ms - slow, needs attention
  • Greater than 50 ms - Serious I/O bottleneck
• Avg. Disk Sec/Write is the average time, in seconds, of a write of data to the disk. Please refer to the guideline in the previous bullet.
• Physical Disk: %Disk Time is the percentage of elapsed time that the selected disk drive was busy servicing read or write requests. A general guideline is that if this value is greater than 50 percent, it represents an I/O bottleneck.
• Avg. Disk Reads/Sec is the rate of read operations on the disk. You need to make sure that this number is less than 85 percent of the disk capacity. The disk access time increases exponentially beyond 85 percent capacity.
• Avg. Disk Writes/Sec is the rate of write operations on the disk. Make sure that this number is less than 85 percent of the disk capacity. The disk access time increases exponentially beyond 85 percent capacity.

When using above counters, you may need to adjust the values for RAID configurations using the following formulas.

• Raid 0 -- I/Os per disk = (reads + writes) / number of disks
• Raid 1 -- I/Os per disk = [reads + (2 * writes)] / 2
• Raid 5 -- I/Os per disk = [reads + (4 * writes)] / number of disks
• Raid 10 -- I/Os per disk = [reads + (2 * writes)] / number of disks

For example, you have a RAID-1 system with two physical disks with the following values of the counters.

• Disk Reads/sec -  80
• Disk Writes/sec - 70
• Avg. Disk Queue Length - 5

In that case, you are encountering (80 + (2 * 70))/2 = 110 I/Os per disk and your disk queue length = 5/2 = 2.5 which indicates a border line I/O bottleneck."

另外可以利用下面的脚本定期IO信息做比对分析：

SET NOCOUNTON

DECLARE @IOStatsTABLE(
[database_id][smallint]NOTNULL,
[file_id][smallint]NOTNULL,
[num_of_reads][bigint]NOTNULL,
[num_of_bytes_read][bigint]NOTNULL,
[io_stall_read_ms][bigint]NOTNULL,
[num_of_writes][bigint]NOTNULL,
[num_of_bytes_written][bigint]NOTNULL,
[io_stall_write_ms][bigint]NOTNULL)
INSERTINTO @IOStats
SELECT database_id,
                vio.file_id,
                num_of_reads,
                num_of_bytes_read,
                io_stall_read_ms,
                num_of_writes,
                num_of_bytes_written,
                io_stall_write_ms
FROM sys.dm_io_virtual_file_stats(NULL,NULL) vio
DECLARE @StartTime datetime, @DurationInSecsint
SET @StartTime= GETDATE()
WAITFOR DELAY'00:05:00'
SET @DurationInSecs=DATEDIFF(ss, @startTime, GETDATE())
SELECT DB_NAME(vio.database_id)AS[Database],
        mf.nameAS[Logical name],
        mf.type_descAS[Type],
(vio.io_stall_read_ms- old.io_stall_read_ms)/CASE(vio.num_of_reads-old.num_of_reads)WHEN0THEN1ELSE vio.num_of_reads-old.num_of_readsENDAS[Averead speed(ms)],
        vio.num_of_reads- old.num_of_readsAS[Noof readsover period],
CONVERT(DEC(14,2),(vio.num_of_reads- old.num_of_reads)/(@DurationInSecs *1.00))AS[Noof reads/sec],
CONVERT(DEC(14,2),(vio.num_of_bytes_read- old.num_of_bytes_read)/1048576.0)AS[Tot MBreadover period],
CONVERT(DEC(14,2),((vio.num_of_bytes_read- old.num_of_bytes_read)/1048576.0)/ @DurationInSecs)AS[Tot MBread/sec],
(vio.num_of_bytes_read- old.num_of_bytes_read)/CASE(vio.num_of_reads-old.num_of_reads)WHEN0THEN1ELSE vio.num_of_reads-old.num_of_readsENDAS[Averead size(bytes)],
(vio.io_stall_write_ms- old.io_stall_write_ms)/CASE(vio.num_of_writes-old.num_of_writes)WHEN0THEN1ELSE vio.num_of_writes-old.num_of_writesENDAS[Ave write speed(ms)],
        vio.num_of_writes- old.num_of_writesAS[Noof writesover period],
CONVERT(DEC(14,2),(vio.num_of_writes- old.num_of_writes)/(@DurationInSecs *1.00))AS[Noof writes/sec],
CONVERT(DEC(14,2),(vio.num_of_bytes_written- old.num_of_bytes_written)/1048576.0)AS[Tot MB writtenover period],
CONVERT(DEC(14,2),((vio.num_of_bytes_written- old.num_of_bytes_written)/1048576.0)/ @DurationInSecs)AS[Tot MB written/sec],
(vio.num_of_bytes_written-old.num_of_bytes_written)/CASE(vio.num_of_writes-old.num_of_writes)WHEN0THEN1ELSE vio.num_of_writes-old.num_of_writesENDAS[Ave write size(bytes)],
        mf.physical_nameAS[Physicalfile name],
        size_on_disk_bytes/1048576AS[File sizeondisk(MB)]
FROM sys.dm_io_virtual_file_stats(NULL,NULL) vio,
        sys.master_files mf,
        @IOStats old
WHERE mf.database_id= vio.database_idAND
        mf.file_id= vio.file_idAND
        old.database_id= vio.database_idAND
        old.file_id= vio.file_idAND
((vio.num_of_bytes_read- old.num_of_bytes_read)+(vio.num_of_bytes_written- old.num_of_bytes_written))>0
ORDERBY((vio.num_of_bytes_read- old.num_of_bytes_read)+(vio.num_of_bytes_written- old.num_of_bytes_written))DESC
GO