c# print barcode zebra Inside Microsoft SQL Server 2008: T-SQL Querying in Visual C#.NET

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Inside Microsoft SQL Server 2008: T-SQL Querying
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a DMV called sys.dm_os_performance_counters containing all the SQL Server instance object-related counters that you can nd in Performance Monitor. Unfortunately, this DMV doesn t give you the more generic operating system counters, such as CPU utilization, I/O queues, and so on. You have to analyze those externally. For example, when I ran the following query on my system, I got the output shown (in abbreviated form) in Table 4-1:
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SELECT object_name, counter_name, instance_name, cntr_value, cntr_type FROM sys.dm_os_performance_counters;
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TABLE 4-1
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Contents of sys.dm_os_performance_counters in Abbreviated Form
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counter_name
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Buffer cache hit ratio Buffer cache hit ratio base Page lookups/sec Free list stalls/sec Free pages Total pages Target pages Database pages Reserved pages Stolen pages
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object_name
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MSSQL$SQL08:Buffer Manager MSSQL$SQL08:Buffer Manager MSSQL$SQL08:Buffer Manager MSSQL$SQL08:Buffer Manager MSSQL$SQL08:Buffer Manager MSSQL$SQL08:Buffer Manager MSSQL$SQL08:Buffer Manager MSSQL$SQL08:Buffer Manager MSSQL$SQL08:Buffer Manager MSSQL$SQL08:Buffer Manager ...
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instance_name
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cntr_value
153 153 36230931 0 164 69472 187769 58627 0 10681
cntr_type
537003264 1073939712 272696576 272696576 65792 65792 65792 65792 65792 65792
You might nd the ability to query these performance counters in SQL Server useful because you can use query manipulation to analyze the data. As with wait information, you can collect performance counters in a table on regular intervals and then use queries and tools such as PivotTables to analyze the data over time.
4
Query Tuning
Determine Course of Action
The next step after you have identi ed the main types of waits and resources involved represents a junction in the tuning process. Based on your discoveries thus far, you will determine a course of action for further investigation. In our case, we need to identify the causes of I/O, parallelism, network-related waits, and transaction log related waits (minor); we will then continue with a route based on our ndings. But if the previous steps had identi ed blocking problems, compilation/recompilation problems, or others, you would need to proceed with a completely different course of action. The I/O-related waits (including I/O latches and write log waits) require us at this point to drill down to the database level. I explain how this is done in the next section. As I mentioned earlier, the parallelism waits (CXPACKET) occur in parallel query plans when threads wait for an exchange packet from other threads before they can continue work. High values in this wait type might indicate that CPU resources are not utilized optimally, especially in OLTP environments where many requests run simultaneously. The problem may be mitigated by lowering the maximum degree of parallelism in the server. Note that even when queries are restricted to use only one CPU, it doesn t mean that SQL Server cannot utilize more than one CPU; rather, a single query will not be processed with a parallel query plan. High values in the CXPACKET wait type can also be caused by using hyperthreading. Note that high values in CXPACKET wait type do not always represent a direct cause of a problem; instead, they can be a symptom, in which case you will typically see high values in other wait types (for example, I/O latches). Also, it is quite natural in parallel query plans for threads to wait for other threads to nish work. So even when you have high values in this wait type, you won t always be able to improve the system s throughput by lowering the maximum degree of parallelism. High values in network waits might indicate network bandwidth problems, but they may also indicate other problems. For example, the client application may have been written inef ciently and can t consume the data fast enough from the moment it made the request. This can happen, for example, when the client uses server-side cursors and in between each fetch of a row it does a lot of processing. Also, some things that seem obvious to most programmers are not necessarily obvious to everyone. This might surprise you, but occasionally we nd applications that do not do any ltering in the database as part of their queries instead, they do the ltering in the application. This, of course, can put an enormous load on the network. I discuss some of the other performance problems later in these books.
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