SELECT scheduler_id, cpu_id, parent_node_id, current_tasks_count, runnable_tasks_count, current_workers_count, active_workers_count, work_queue_count FROM sys.dm_os_schedulers; 結果集如下所示。 複製 scheduler_id cpu_id parent_node_id current_tasks_count --- --- --- --- 0 1 0...
SELECT scheduler_id, cpu_id, parent_node_id, current_tasks_count, runnable_tasks_count, current_workers_count, active_workers_count, work_queue_count FROM sys.dm_os_schedulers; 结果集如下。 复制 scheduler_id cpu_id parent_node_id current_tasks_count...
SELECT scheduler_id, cpu_id, parent_node_id, current_tasks_count, runnable_tasks_count, current_workers_count, active_workers_count, work_queue_count FROM sys.dm_os_schedulers; Here's the result set. Copy scheduler_id cpu_id parent_node_id current_tasks_count --- --- --- --- ...
Turning my gaze to SQL Server and checking sys.dm_os_schedulers I wasn't expecting the output I saw. Notice that parent_node_id (numa node) changes from 0 to 1 indicating a different numa node, but the cpu_id changes from 35 to 64! This struck me as very odd, as I expect...
Идентификаторродительскогопланировщика. Этодескрипторсведенийпланировщикадляэтойзадачи. Дополнительныесведениясм. вразделеsys.dm_os_schedulers. ...
Since, again, SQL Server runs on Windows and uses the same APIs to gather information it sees the same exact information. This is why we may not have contiguous cpu_ids in sys.dm_os_schedulers on systems with a large number of cores and numa nodes!
sys.dm_os_memory_clerks sys.dm_os_memory_nodes sys.dm_os_memory_objects sys.dm_os_memory_pools sys.dm_os_nodes sys.dm_os_performance_counters sys.dm_os_process_memory sys.dm_os_schedulers sys.dm_os_server_diagnostics_log_configurations sys.dm_os_stacks sys.dm_os_...
sys.dm_os_memory_pools sys.dm_os_nodes sys.dm_os_performance_counters sys.dm_os_process_memory sys.dm_os_schedulers sys.dm_os_server_diagnostics_log_configurations sys.dm_os_stacks sys.dm_os_sys_info sys.dm_os_sys_memory sys.dm_os_tasks sys.dm_os_threads sys.dm_os_virtual_address...
先贴以下上篇sys.dm_os_waiting_tasks 的结果图: 我们分析一下这个结果的task_address 可以看出去掉重复其实只有9个,也就是说一个并行(4线程,配置不同,情况也不同)会有9个task。 又是线程,又是task ,还有worker,schedulers 这些都是什么? 这个有必要先说一下,因为这篇博客前我也是乱乱的。
若要從 Azure Synapse Analytics 或 Analytics Platform System (PDW) 中的專用 SQL 集區呼叫此專案,請參閱sys.dm_pdw_exec_requests。 針對無伺服器 SQL 集區或 Microsoft Fabric, 請使用sys.dm_exec_requests。 展開資料表 資料行名稱資料類型描述