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  • Troubleshooting High-CPU Utilization for SQL Server

    - by Susantha Bathige
    The objective of this FAQ is to outline the basic steps in troubleshooting high CPU utilization on  a server hosting a SQL Server instance. The first and the most common step if you suspect high CPU utilization (or are alerted for it) is to login to the physical server and check the Windows Task Manager. The Performance tab will show the high utilization as shown below: Next, we need to determine which process is responsible for the high CPU consumption. The Processes tab of the Task Manager will show this information: Note that to see all processes you should select Show processes from all user. In this case, SQL Server (sqlserver.exe) is consuming 99% of the CPU (a normal benchmark for max CPU utilization is about 50-60%). Next we examine the scheduler data. Scheduler is a component of SQLOS which evenly distributes load amongst CPUs. The query below returns the important columns for CPU troubleshooting. Note – if your server is under severe stress and you are unable to login to SSMS, you can use another machine’s SSMS to login to the server through DAC – Dedicated Administrator Connection (see http://msdn.microsoft.com/en-us/library/ms189595.aspx for details on using DAC) SELECT scheduler_id ,cpu_id ,status ,runnable_tasks_count ,active_workers_count ,load_factor ,yield_count FROM sys.dm_os_schedulers WHERE scheduler_id See below for the BOL definitions for the above columns. scheduler_id – ID of the scheduler. All schedulers that are used to run regular queries have ID numbers less than 1048576. Those schedulers that have IDs greater than or equal to 1048576 are used internally by SQL Server, such as the dedicated administrator connection scheduler. cpu_id – ID of the CPU with which this scheduler is associated. status – Indicates the status of the scheduler. runnable_tasks_count – Number of workers, with tasks assigned to them that are waiting to be scheduled on the runnable queue. active_workers_count – Number of workers that are active. An active worker is never preemptive, must have an associated task, and is either running, runnable, or suspended. current_tasks_count - Number of current tasks that are associated with this scheduler. load_factor – Internal value that indicates the perceived load on this scheduler. yield_count – Internal value that is used to indicate progress on this scheduler.                                                                 Now to interpret the above data. There are four schedulers and each assigned to a different CPU. All the CPUs are ready to accept user queries as they all are ONLINE. There are 294 active tasks in the output as per the current_tasks_count column. This count indicates how many activities currently associated with the schedulers. When a  task is complete, this number is decremented. The 294 is quite a high figure and indicates all four schedulers are extremely busy. When a task is enqueued, the load_factor  value is incremented. This value is used to determine whether a new task should be put on this scheduler or another scheduler. The new task will be allocated to less loaded scheduler by SQLOS. The very high value of this column indicates all the schedulers have a high load. There are 268 runnable tasks which mean all these tasks are assigned a worker and waiting to be scheduled on the runnable queue.   The next step is  to identify which queries are demanding a lot of CPU time. The below query is useful for this purpose (note, in its current form,  it only shows the top 10 records). SELECT TOP 10 st.text  ,st.dbid  ,st.objectid  ,qs.total_worker_time  ,qs.last_worker_time  ,qp.query_plan FROM sys.dm_exec_query_stats qs CROSS APPLY sys.dm_exec_sql_text(qs.sql_handle) st CROSS APPLY sys.dm_exec_query_plan(qs.plan_handle) qp ORDER BY qs.total_worker_time DESC This query as total_worker_time as the measure of CPU load and is in descending order of the  total_worker_time to show the most expensive queries and their plans at the top:      Note the BOL definitions for the important columns: total_worker_time - Total amount of CPU time, in microseconds, that was consumed by executions of this plan since it was compiled. last_worker_time - CPU time, in microseconds, that was consumed the last time the plan was executed.   I re-ran the same query again after few seconds and was returned the below output. After few seconds the SP dbo.TestProc1 is shown in fourth place and once again the last_worker_time is the highest. This means the procedure TestProc1 consumes a CPU time continuously each time it executes.      In this case, the primary cause for high CPU utilization was a stored procedure. You can view the execution plan by clicking on query_plan column to investigate why this is causing a high CPU load. I have used SQL Server 2008 (SP1) to test all the queries used in this article.

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  • The Hot-Add Memory Hogs

    - by Andrew Clarke
    One of the more difficult tasks, when virtualizing a server, is to determine the amount of memory that Hypervisor should assign to the virtual machine. This requires accurate monitoring and, because of the consequences of setting the value too low, there is a great temptation to err on the side of over-provisioning. This results in fewer guest VMs and, in fact, with more accurate memory provisioning, many virtual environments could support 30% more VMs. In order to achieve a better consolidation (aka VM density) ratio, Windows Server 2008 R2 SP1 has introduced what Microsoft calls ‘Dynamic Memory’. This means that the start-up RAM VM memory assigned to guest virtual machines can be allowed to vary according to demand, changing dynamically while the VM is running, based on the workload of applications running inside. If demand outstrips supply, then memory can be rationed according to the ‘memory weight’ assigned to the guest VM. By this mechanism, memory becomes a shared resource that can be reallocated automatically as demand patterns vary. Unlike VMWare’s Memory Overcommit technology, the sum of all the memory allocations to each virtual machine will not exceed the total memory of the host computer. This is fine for applications that are self-regulating in their demands for memory, releasing memory back into the 'pool' when not under peak load. Other applications however, such as SQL Server Standard and Enterprise, are by nature, memory hogs under high workload; they can grab hot-add memory whilst running under load and then never release it. This requires more careful setting-up and the SQLOS team have provided some guidelines from for configuring SQL Server in virtual environments. Whereas VMWare’s Memory Overcommit is well-proven in a number of different configurations, Hyper-V’s ‘Dynamic Memory’ is new. So far, the indications are that it will improve the business case for virtualizing and it is probably a far more intuitive technology for the average IT professional to grasp. It is certainly worth testing to see whether it works for you.

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