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despite the availability of a number of idle schedulers.4 In this case, the total CPU percentage (as reported by Performance Monitor) may be well below 100 percent, even though there is significant contention on some CPU cores. Of course, if a system is completely CPU bound (all CPU cores), then the yielding process, exposed with the SOS_SCHEDULER_YIELD wait type, would be occurring on all schedulers. The important point is that the yielding process may be occurring on only some schedulers, even when overall CPU usage appears low. This makes the SOS_SCHEDULER_YIELD wait type an important consideration in an overall assessment of CPU pressure.
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sys.dm_os_schedulers
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Scheduler details can be inspected with the sys.dm_os_schedulers DMV. Querying this DMV will reveal one scheduler per CPU core that the instance has access to, a number of system schedulers, and one for the dedicated administrator connection (DAC). Included columns reveal a number of scheduler-level details such as the number of tasks and yield count.
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In closing this section on CPU pressure, let s look at some DMV queries that can be used in supplementing information from the waits and queues analysis. DMV QUERIES The two DMV queries in this section identify signal wait percentage and top CPU consumers. Listing 17.7 can be used to detect signal waits and resource waits as a percentage of the total wait time. As discussed previously, a high signal wait time usually indicates CPU pressure.
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Listing 17.7 Signal wait time
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-- Wait Analysis; Signal vs. Resource Waits SELECT SUM(wait_time_ms - signal_wait_time_ms) as [ResourceWaitTotal] , CAST(100.0 * sum(wait_time_ms - signal_wait_time_ms) / SUM(wait_time_ms) as numeric(20, 2)) AS [ResourceWait%] , SUM(signal_wait_time_ms) AS [SignalWaitTotal] , CAST (100.0 * sum(signal_wait_time_ms) / SUM (wait_time_ms) AS numeric(20, 2)) AS [SignalWait%] FROM sys.dm_os_wait_stats WHERE wait_type not in ( 'CLR_SEMAPHORE' , 'LAZYWRITER_SLEEP' , 'RESOURCE_QUEUE' , 'SLEEP_TASK'
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In this case restarting one of the processes would more than likely position it on an idle scheduler.
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Waits and queues: a performance-tuning methodology
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, 'SLEEP_SYSTEMTASK' , 'WAITFOR' )
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Notice that the script excludes a number of wait types not relevant to a performancetuning process. The get/track_waitstats stored procedures we covered earlier perform the same exclusions. Listing 17.8 lists the top 50 queries ordered by CPU time. It includes the execution_count column to indicate how many times this query has been executed. Frequently executed queries with large CPU consumption are targets for optimization.
Listing 17.8 Top 50 queries by CPU consumption
-- Top 50 Queries by CPU Consumption SELECT TOP 50 queryStats.total_worker_time/queryStats.execution_count AS [Avg CPU Time] , queryStats.execution_count , SUBSTRING(queryText.text,queryStats.statement_start_offset/2, (CASE WHEN queryStats.statement_end_offset = -1 THEN len(convert(nvarchar(max), queryText.text)) * 2 ELSE queryStats.statement_end_offset end queryStats.statement_start_offset) / 2) AS query_text , dbname=db_name(queryText.dbid) FROM sys.dm_exec_query_stats queryStats CROSS APPLY sys.dm_exec_sql_text(queryStats.sql_handle) AS queryText ORDER BY [Avg CPU Time] DESC
One of the things that will become obvious as we move throughout this section is that common design problems affect a number of resources. For example, poor index selection and maintenance can have a dramatic impact on both memory and disk I/O.
17.3.3 Index-related memory pressure
As we covered in chapter 13, the correct selection and maintenance of indexes are crucial from a query-performance perspective. Numerous unused indexes have a large maintenance overhead, and missing or poorly maintained indexes have a double impact on resources: additional disk I/O and a reduction in the available buffer cache. From a performance-monitoring perspective, the following performance counters are of interest in assessing the impact of poor index design and maintenance:
SQL Server:Buffer Manager Page Life Expectancy This counter indicates the average time (in seconds) that data pages remain in memory. A common occurrence is for this value to drop suddenly in response to a large query that requires a lot of disk access, flushing data pages from memory to make way for the required data from disk. Missing indexes are a common contributor to this type of event. A system with adequate memory and good indexing should see this value in excess of 500 seconds, without frequent sudden drops during normal activity.
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