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Table 3-4. Database I/O Information in Abbreviated Form
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db Performance Performance tempdb Generic master tempdb master Generic msdb
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file_type io_mb data log data data log log data log data
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io_stall_s io_stall_pct rn 74.86 15.76 8.90 0.15 0.09 0.08 0.04 0.03 0.02 0.01 1 2 3 4 5 6 7 8 9 10
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11400.81 11172.55 3732.40 940.08 54.10 7.33 5.24 13.56 1.02 5.07 0.55 2352.55 1327.59 21.78 13.75 11.20 6.20 3.81 2.76 1.71
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AdventureWorks log ...
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The output shows the database name, file type, total I/O (reads and writes) in megabytes, I/O stalls in seconds, I/O stalls in percent of the total for the whole system, and a row number indicating a position in the sorted list based on I/O stalls. Of course, if you want, you can calculate a percentage and row number based on I/O as opposed to I/O stalls, and you can also use running aggregation techniques to calculate a running percentage, as I demonstrated earlier. You might also be interested in a separation between the reads and writes for your analysis. In this output, you can clearly identify the three main elements involving most of the system's I/O stallsthe data portion of Performance, which scores big time; the log portion of Performance; and the data portion of tempdb. Obviously, you should focus on these three elements, with special attention to data activity against the Performance database. Regarding the bulk of our problemI/O against the data portion of the Performance databaseyou now need to drill down to the process level to identify the processes that involve most of the waits. As for the transaction log, you first need to check whether it's configured adequately. That is, whether it is placed on its own disk drive with no interference, and if so, whether the disk drive is fast enough. If the log happens to be placed on a slow disk drive, you might want to consider dedicating a faster disk for it. Once the logging activity exceeds the throughput of the disk drive, you start getting waits and stalls. You might be happy with dedicating a faster disk drive for the log, but then again, you might not have the budget or you might have already assigned the fastest disk you could for it. Keep in mind that the transaction log is written sequentially, so striping it over multiple disk drives won't help, unless you also have activities that read from the log (such as transaction log replication, or triggers in SQL Server 2000). You might also be able to optimize the processes that cause intensive logging by reducing their amount of logging. I'll elaborate on the transaction log and its optimization in 8. As for tempdb, there are many activitiesboth explicit and implicitthat might cause tension in tempdb to the point where it can become a serious bottleneck in the system. In fact, internally tempdb is used more heavily in SQL Server 2005 because of the new row-versioning technology incorporated in the engine. Row versioning is used for the new snapshot-based isolations, the special inserted and deleted tables in triggers, the new online index operations, and the new multiple active result sets (MARS). The new technology maintains an older, consistent version of a row in a linked list in tempdb. Typically, there's a lot of room for optimizing tempdb, and you should definitely give that option adequate attention. I'll elaborate on tempdb and on row versioning in Inside T-SQL Programming in the chapters that cover temporary tables, triggers, and transactions.
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For our demonstration, let's focus on solving the I/O problems related to the data portion of the Performance database.
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Drill Down to the Process Level
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Now that you know which databases (in our case, one) involve most of the performance problem, you want to drill down to the process level; namely, identify the processes (stored procedures, queries, and so on) that need to be tuned. For this task, you will find SQL Server's built-in tracing capabilities extremely powerful. You need to trace a workload representing the typical activities in the system against the databases you need to focus on, analyze the trace data, and isolate the processes that need to be tuned. Before I talk about the specific trace you need to create for such tuning purposes, I'd first like to point out a few important tips regarding working with traces in SQL Server in general. Traces have an impact on the performance of the system, and you should put effort into reducing their impact. My good friend Brian Moran once compared the problematic aspect of measuring performance to the Heisenberg Uncertainty Principle in quantum mechanics. The principle was formulated by Werner Heisenberg in 1927. Very loosely speaking, when you measure something, there's a factor of uncertainty caused by your measurement. The more precise the measure of something's position, the more uncertainty there is regarding its momentum (loosely, velocity and direction). So the more precisely you know one thing, the less precisely you can know some parallel quantity. On the scale of atoms and elementary particles, the effect of the uncertainty principle is very important. There's no proof to support the uncertainty principal (just like there's no scientific proof of God or of evolution), but the theory is mathematically sound and supported by experimentation. Going back to our traces, you don't want your tracing activity to cause a performance problem itself. You can't avoid its effect altogetherthat's impossiblebut you can definitely do much to reduce it by following some important guidelines: Don't trace with the SQL Server Profiler GUI; instead, use the T-SQL code that defines the trace. When you trace with Profiler, you're actually running two tracesone that directs the output to the target file, and one that streams the trace information to the client running Profiler. You can define the trace graphically with Profiler, and then script the trace definition to T-SQL code using the menu item File>Export>Script Trace Definition>For SQL Server 2005... (or 2000...). You can then make slight revisions to the code depending on your needs. I like to encapsulate the code in a stored procedure, which accepts as arguments elements that I want to make variablefor example, the database ID I use as a filter in the trace definition. Do not trace directly to a table, as this will have a significant performance impact. Tracing to a file on a local disk is the fastest option (tracing to a network share is bad as well). You can later load the trace data to a table for analysis using the fn_trace_gettable function with a SELECT INTO statement. SELECT INTO is considered a bulk operation. Bulk operations are minimally logged when the database recovery model is not set to FULL; therefore, they run much faster then when running in a fully logged mode. Tracing can produce enormous amount of data and excessive I/O activity. Make sure the target trace file does not reside on disk drives that contain database files (such as data, log, and tempdb). Ideally, dedicate a separate disk drive for the target trace files, even if it means adding external disk drives. Be selective in your choices of event classes and data columnsonly trace what you need, removing all default and unnecessary ones. Of course, don't be too selective; make sure that all
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relevant event classes and data columns are included. Use the trace filtering capabilities to filter only the relevant events. For example, when tuning a particular database, make sure you filter events only for the relevant database ID. With these important guidelines in mind, let's proceed to the trace that we need for our tuning purposes.
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