在SQL Server 2005性能問題的疑難解答
作家：蘇尼爾阿加瓦爾，鮑里斯·巴雷什尼科夫，湯姆·戴維森，基思·埃爾莫爾，登齊爾·裏貝羅，于爾根·托馬斯
適用於：SQL Server 2005中
摘要：體驗偶爾慢下來的SQL Server數據庫，這是並不鮮見。 設計拙劣的數據庫或系統，配置不當的工作量，但幾個這種類型的性能問題很多可能的原因。 管理員需要積極主動地防止或減少問題發生時，診斷原因並採取糾正措施來解決這個問題。 本文提供了一步一步地指導診斷和解決常見的性能問題，通過使用公開可用的工具，如SQL Server Profiler中，監控系統，並在SQL Server 2005新的動態管理視圖。
在此頁中
介紹
目標
方法論
資源瓶頸
CPU瓶頸
內存瓶頸
I
/ O瓶頸
tempdb中
運行慢的查詢
結論
附錄A：DBCC
MEMORYSTATUS中描述
附錄B：阻止腳本
介紹
許多客戶都可以體驗他們的SQL Server數據庫偶爾慢下來。 的原因，範圍可以從一個設計不當的數據庫的工作量，不當配置系統。 作爲管理員，你要積極主動地防止或減少問題發生時，診斷病因，並在可能的情況下，採取糾正措施來解決這個問題。 本白皮書限制其範圍通常由微軟®公司的客戶支援服務（CSS或PSS）以來所有可能出現的問題進行詳盡的分析是不可行的問題。 我們的診斷和解決常見的性能問題，通過使用公開可用的工具，如SQL Server Profiler中，系統監視器（Perfmon），在Microsoft SQL Server的新的動態管理視圖™2005提供了一步一步地指導。
目標
本文的主要目的是提供一個共同的客戶案例中的SQL Server性能問題診斷和故障排除利用公開可用的工具的一般方法。
可支持SQL Server 2005中已取得了長足的進步。 內核層（SQL-OS），已重新架構和內部結構和統計數據，通過動態管理視圖（DMV）的關係行集的暴露。 SQL Server 2000中暴露出的一些信息，但如sysprocesses系統表，但有時你需要生成一個SQL Server進程的內存，從內部結構中提取相關信息的物理轉儲。 這主要有兩個問題。 首先，客戶不能總是提供物理轉儲轉儲的大小和所花費的時間來創建它。 其次，它需要更長的時間來診斷問題，因爲這些文件通常必須被傳輸分析微軟公司。
這給我們帶來的這紙，這是爲了展示DMV的第二個目標。 DMV的可以加快診斷過程中，無需生成和分析，在大多數情況下的物理轉儲。 本文提供了，在可能的情況下，解決同樣的問題在SQL Server 2000和SQL Server 2005中並排並排比較。 DMV的提供簡化和熟悉的關係接口，一個越來越重要的系統信息。 此信息可用於監測目的，以提醒管理員任何潛在的問題。 或信息，可以調查和收集定期進行詳細的分析。
方法論
可以在SQL Server放緩的原因很多。 我們使用以下三個主要症狀，開始診斷問題。
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本文涵蓋資源瓶頸 ：處理器，內存，I / O瓶頸。 我們不考慮網絡問題。 對於每個資源的瓶頸，我們描述瞭如何確定的問題，然後遍歷可能的原因。 例如，內存瓶頸可以導致過多的分頁，最終影響性能。
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tempdb的瓶頸 ：由於只有一個tempdb中的每個SQL Server實例，這可以是一個性能和磁盤空間的瓶頸。 一個行爲不端的應用程序可以超載tempdb中過多的DDL / DML操作的條件和空間。 這可能導致無關的服務器上運行的應用程序，以減緩或失敗。
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一個緩慢的運行用戶查詢 ：現有的查詢的性能可能會倒退或將採取比預期更長，可能會出現一個新的查詢。 可以有許多原因。 例如：
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在統計信息的變化可能導致糟糕的查詢計劃爲現有的查詢。
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缺少索引可以強制表掃描和查詢減慢。
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應用程序可以減緩由於阻塞資源利用率，即使是正常的。
過度阻塞，例如，可能是由於惡劣的應用程序或架構設計或選擇不當的隔離級別的事務。
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這些症狀的原因不一定是相互獨立的。 查詢計劃選擇不當稅制資源，導致工作量的整體放緩。 所以，如果一個大表缺少有用的索引，查詢優化，決定不使用它，這不僅會導致查詢放緩，但它也使沉重的壓力，I / O子系統讀取不必要的數據頁內存（緩衝池），這些頁存儲在緩存中。 同樣，過度的經常運行的查詢重新編譯可以把CPU上的壓力。
資源瓶頸
本文接下來的部分討論的CPU，內存，和的I / O子系統的資源，以及如何將這些能成爲瓶頸。 （網絡問題超出了本文的範圍。）對於每個資源的瓶頸，我們描述瞭如何確定的問題，然後遍歷可能的原因。 例如，內存瓶頸可以導致過多的分頁，可以最終影響性能。
如果你有一個資源瓶頸，然後才能決定，你需要知道如何正常情況下使用的資源。 您可以使用本文中概述的方法，收集有關信息資源的利用基線（當你沒有遇到性能問題）。
您可能會發現問題是附近的能力，且SQL Server上運行的一種資源，不能支持其當前配置的工作量。 爲了解決這個問題，你可能需要添加更多的處理能力，內存，或增加您的I / O或網絡通道的帶寬。 但是，你邁出這一步之前，它是有用的資源瓶頸瞭解一些常見的原因。 有不需要增加額外的資源，例如，重新配置的解決方案。
爲解決資源瓶頸的工具
一個或多個下列工具是用來解決一個特定的資源瓶頸。
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系統監視器（PerfMon）：這個工具是作爲Windows的一部分提供。 有關詳細信息，請參閱系統監視器文檔。
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SQL Server事件探查 ：在SQL Server 2005程序組中的性能工具組，請參閱SQL Server事件探查 。
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DBCC命令 ：請參見SQL Server聯機叢書和附錄詳細介紹了。
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DMV的在線詳情，請參閱SQL Server聯機叢書。
CPU瓶頸
發生突然和意外，沒有額外的負載在服務器上，CPU瓶頸，通常是由非最優查詢計劃，一個貧窮的配置，或設計因素，並沒有足夠的硬件資源。 衝出購買速度更快的和/或更多的處理器之前，你應該首先確定CPU帶寬最大的消費者，看看他們是否可以調整。
系統監視器通常是最好的方法來確定，如果服務器是CPU綁定。 你應該看到的Processor：％Processor Time計數器如果是高值超過80％，每個CPU的處理器時間一般都被視爲是一個瓶頸。 您還可以監視SQL Server調度使用sys.dm_os_schedulers觀點，看看是否可運行的任務數量通常是非零。 非零值表示任務必須等待的時間片運行;這個計數器的高值是CPU瓶頸的症狀。 你可以使用以下查詢來列出所有的調度和運行的任務數量看。
選擇 scheduler_id， current_tasks_count， runnable_tasks_count 從 sys.dm_os_schedulers 哪裏 scheduler_id <255
下面的查詢，爲您提供了一個高層次的觀點，當前緩存的批次或程序，其中使用最多的CPU。 查詢總量的，同樣plan__handle（這意味着它們是同一批次或程序的一部分）的所有陳述消耗的CPU。如果一個給定的plan_handle的有多個語句，你可能要進一步深入，以找到具體的查詢，是整體的CPU使用率的最大貢獻者。
選擇前50名 總和（qs.total_worker_time）爲total_cpu_time， 總和（qs.execution_count）作爲total_execution_count的， COUNT（*）作爲number_of_statements， qs.plan_handle 從 sys.dm_exec_query_stats的QS 組由qs.plan_handle 整理的總和（qs.total_worker_time）遞減
本節的其餘部分將討論一些常見的CPU密集型操作可能出現的SQL Server，以及有效的方法來檢測和解決這些問題。
過多的編譯和重新編譯
當一個批處理或遠程過程調用（RPC）提交到SQL Server，纔開始執行服務器檢查查詢計劃的有效性和正確性。 如果這些檢查之一失敗，一批可能要重新編譯，以產生不同的查詢計劃。 這種被稱爲彙編重新編譯 。 這些重新編譯通常是必要的，以確保正確性和服務器確定，有可能是由於在基礎數據的變化，更優化的查詢計劃時，往往表現。 彙編的性質是CPU密集型的，因此可能會導致過多的重新編譯系統上的CPU密集型的性能問題。
SQL Server 2000中，當SQL Server重新編譯一個存儲過程，整個存儲過程重新編譯，不只是觸發重新編譯的語句。 SQL Server 2005引入語句級重新編譯存儲過程。 當SQL Server 2005重新編譯存儲過程，只有聲明，導致重新編譯是編譯，而不是整個過程。 使用較少的CPU帶寬和在更短的COMPILE鎖，如鎖資源爭奪的結果。 重新編譯可能發生，由於各種原因，如：
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模式改變
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統計改變
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遞延編譯
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SET選項已變更
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臨時表改變
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RECOMPILE查詢提示或存儲過程中創建，使用選項（重新編譯）
發現
您可以使用系統監視器（PerfMon）或SQL跟蹤（SQL Server事件探查器）來檢測過多的編譯和重新編譯。
系統監視器（PerfMon）
SQL統計對象提供計數器來監視編譯和發送到SQL Server實例的請求類型。 你必須監視查詢編譯和重新編譯的數量結合收到找出如果編譯造成高CPU使用的批次數量。 理想的情況下， 批量請求/秒的SQL重新編譯/秒的比率應該是很低的，除非用戶提交即席查詢。
看關鍵數據計數器如下。
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SQL Server的SQL統計：批量請求/秒
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SQL Server的SQL統計：SQL編譯/秒
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SQL Server的SQL統計：SQL重新編譯/秒
欲瞭解更多信息，請參見SQL Server聯機叢書中的“SQL統計對象”。
SQL跟蹤
如果PerfMon計數器顯示大量的重新編譯，重新編譯，可以由SQL Server的高CPU消耗的貢獻。 然後，我們需要在探查器跟蹤一下，找到重新編譯存儲過程。 SQL Server Profiler跟蹤讓我們一起重新編譯的原因的信息。 得到這個信息，你可以使用下面的事件。
SP：編譯/ SQL：StmtRecompile的 。 的SP：Recompile和SQL：StmtRecompile事件類指示已重新編譯存儲過程和語句。 當您編譯一個存儲過程，一個事件產生的存儲過程，併爲每個被編譯的語句之一。 然而，當一個存儲過程重新編譯，只導致重新編譯的語句重新編譯（而不是整個存儲過程在SQL Server 2000）。 下面列出了一些比較重要的數據列的SP：Recompile事件類。 重要的是在特定的EventSubclass數據列SP決定重新編譯的原因：重新編譯一次重新編譯，並特設有可能被重新編譯的批次，可以發射的過程或觸發器被觸發。 在SQL Server 2005，它是更有益的監視SQL：StmtRecompiles任何類型的批次，特設，存儲過程，或觸發重新編譯時會觸發此事件類。
我們期待在這些事件中的關鍵數據列如下。
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EventClass
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的EventSubclass
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的ObjectID（代表包含此語句的存儲過程）
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的SPID
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開始時間
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SQLHANDLE
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的TextData
有關詳細信息，請參閱“的SQL：StmtRecompile事件類”SQL Server聯機叢書。
如果你有一個跟蹤文件中保存，你可以用下面的查詢看到在跟蹤中捕獲的所有Recompile事件。
選擇 SPID， 開始時間， TextData資料， 的EventSubclass， ObjectID的， DatabaseID， SQLHANDLE 從 fn_trace_gettable將（'E：\ recompiletrace.trc'，1） 哪裏 在EventClass（37,75,166）
EventClass 37 = SP：重新編譯，75 = 166 = SQL CursorRecompile：StmtRecompile
你可以進一步小組由SQLHANDLE的ObjectID列，或由其他各列從這個查詢的結果，才能看到，如果大部分的重新編譯一個存儲過程歸因，或由於一些其他原因（如SET選項已經改變）。
顯示計劃XML查詢編譯 。 顯示計劃XML的查詢編譯事件類發生時，Microsoft SQL Server編譯或重新編譯SQL語句。 此事件正在編譯或重新編譯的語句的信息。 此信息包括查詢計劃和對象ID問題的過程。 捕獲此事件有顯着的性能開銷，因爲它是每個編譯或重新編譯抓獲。 如果你看到一個高價值的SQL編譯/秒 ，在系統監視器計數器，你應該監視此事件。 有了這個信息，你可以看到哪些語句經常重新編譯。 您可以使用此信息來改變這些語句的參數。 這應減少重新編譯的數量。
DMV的 。 當您使用sys.dm_exec_query_optimizer_info DMV的，你可以得到一個SQL Server的時間花在優化的好主意。 如果你把這個DMV快照，你可以得到一個良好的手感優化在給定的時間內，花的時間。
選擇* 從sys.dm_exec_query_optimizer_info 櫃檯發生的價值 -------------------------------------------------- ------- 優化81 1.0 經過時間的81 6.4547820702944486E-2
特別是，在過去的時間，這是經過由於優化。 由於在優化過程中所經過的時間一般接近被用於優化（自優化過程是非常CPU綁定）的CPU時間，你可以得到一個編譯時間，造成高CPU的程度很好的措施使用。
這是用於捕捉這一信息是另一個DMV的sys.dm_exec_query_stats的 。
你想看看數據列如下。 ：
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的sql_handle
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共有工人時間
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計劃生成號碼
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聲明開始偏移
欲瞭解更多信息，請參見SQL Server聯機叢書sys.dm_exec_query_stats的在線主題。
尤其是plan_generation_num表示已編譯的查詢的次數。 下面的示例查詢給你排名前25位已編譯的存儲程序。
選擇* 從sys.dm_exec_query_optimizer_info 選擇前25名 sql_text.text， sql_handle的， plan_generation_num， execution_count， DBID， 的ObjectID 從 sys.dm_exec_query_stats的1 CROSS APPLY SQL_TEXT sys.dm_exec_sql_text（sql_handle的） 哪裏 plan_generation_num> 1 爲了通過plan_generation_num遞減
如需詳細資訊，請參閱批編譯，重新編譯和計劃緩存在SQL Server 2005問題 （http://www.microsoft.com/technet/prodtechnol/sql/2005/recomp.mspx）的Microsoft TechNet上。
決議
如果檢測到過多的編譯/重編譯，考慮下列選項。
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如果發生重新編譯，因爲SET選項更改，使用SQL Server Profiler來確定SET選項改變。 避免在存儲過程中的SET選項改變。 這是更好地設置他們在連接級別。 確保SET選項在連接的生命週期不改變。
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臨時表的重新編譯閾值低於正常表。 如果在臨時表上重新編譯是由於統計數據的變化，你可以更改臨時表，表變量。 表變量的基數變化不會導致重新編譯。 這種方法的缺點是，查詢優化器不會因爲統計數字沒有建立或維持表變量保持跟蹤表變量的基數。 這可能會導致非最優查詢計劃。 你可以測試不同的選項，並選擇最好的一個。
另一種選擇是使用KEEP PLAN查詢提示。 這設置的臨時表是永久表相同的門檻。 EventSubClass列表示，“統計改爲”在臨時表上的操作。
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爲了避免重新編譯是由於統計數據的變化（例如，當計劃變得不理想，由於改變數據統計），指定的KEEPFIXED的PLAN查詢提示。 與此選項生效，重新編譯只能發生，因爲正確性相關的原因（例如，當底層表結構已經改變，並且計劃不再適用），而不是由於統計。 一個例子可能是當重新編譯時，如果表的架構，是由一份聲明中改變引用，或者如果一個表與存儲過程執行sp_recompile標記。
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關閉自動更新的統計指標和統計定義一個表或索引視圖防止重新編譯是由於該對象的統計變化。 但是請注意，關閉“自動統計”功能，使用此方法通常不是一個好主意。 這是因爲查詢優化器是不再敏感，這些對象和最理想的查詢計劃可能導致的數據變化。 使用這種方法只能作爲最後的手段用盡所有其他替代品後。
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批次應該有限定的對象名稱（例如，dbo.Table1），以避免重新編譯和避免對象之間的模糊性。
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爲了避免重新編譯，由於遞延編譯，不交錯DML和DDL或創造條件結構，如IF語句的DDL。
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運行數據庫引擎優化顧問（DTA），看看是否任何索引的變化，改善編譯時間和查詢的執行時間。
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請檢查RECOMPILE查詢提示WITH RECOMPILE選項，或者如果使用存儲過程創建。 如果RECOMPILE選項，在SQL Server 2005創建的一個過程，我們也許能夠採取的語句級別的RECOMPILE提示需要重新編譯的優勢，如果在該程序的特別聲明。 這將避免重新編譯整個程序每次執行時，而在同一時間允許個別語句進行編譯的必要性。 RECOMPILE提示的更多信息，請參見SQL Server聯機叢書。
低效的查詢計劃
當生成一個查詢執行計劃，SQL Server優化器試圖選擇一個計劃，提供最快的響應時間，該查詢。 請注意，最快的響應時間並不一定意味着減少的I / O的使用量，也不一定意味着使用量最少的CPU，它是一個平衡的各種資源。
某些類型的運營商是比別人更多的CPU密集。 就其性質而言，通過各自的輸入數據的哈希操作和排序操作掃描。 與預讀（預取）在掃描，緩衝區高速緩存中的網頁幾乎都是之前頁是由運營商的需要。因此，等待物理I / O最小化或消除。 當這些類型的操作不再由物理I / O的限制，他們往往表現自己高CPU消耗。 相比之下，嵌套循環聯接有很多索引查找，並能迅速成爲I / O綁定如果索引查找穿越許多不同的部分，使網頁不能放入緩衝區高速緩存表。
優化器在評估各種替代的查詢計劃的成本使用的是最重要的輸入爲每個操作員，您可以看到的Showplan（EstimateRows和EstimateExecutions屬性）的基數估計。 如果沒有準確的基數估計，在優化的主要輸入是有缺陷的，很多次，所以是最後的計劃。
對於一個優秀的白皮書詳細說明了如何在SQL Server優化器使用統計描述，看到在Microsoft SQL Server查詢優化器採用 S tatistics 200 5（http://www.microsoft.com/technet/prodtechnol/sql/2005/ qrystats.mspx）。 白皮書討論如何優化使用統計，最佳做法保持最新統計，和一些常見的查詢設計問題，可以防止準確的預算基數，從而導致低效的查詢計劃。
發現
通常檢測相對低效的查詢計劃。 低效的查詢計劃可能會導致CPU消耗增加。
對sys.dm_exec_query_stats的查詢是一種有效的方式，以確定哪些查詢使用最累積的CPU。
選擇 highest_cpu_queries.plan_handle， highest_cpu_queries.total_worker_time， q.dbid， q.objectid， q.number， q.encrypted， Q。[文字] 從 （選擇前50名 qs.plan_handle， qs.total_worker_time 從 sys.dm_exec_query_stats的QS 爲了以降序qs.total_worker_time）作爲highest_cpu_queries的 CROSS APPLY sys.dm_exec_sql_text（plan_handle的）爲q 爲了通過highest_cpu_queries.total_worker_time遞減
另外，使用各運營商的過濾器，可能是CPU密集型，如哈希匹配'％％'，'％分類％“，以尋找嫌疑人對sys.dm_exec_cached_plans查詢。
決議
考慮下面的選項，如果你發現低效的查詢計劃。
-
調整查詢數據庫引擎優化顧問，看它是否產生任何索引的建議。
-
檢查不良基數估計的問題。
書面查詢是這樣，他們用最嚴格的WHERE子句適用？ 無限制的查詢是資源密集型通過其本身的性質。
運行更新查詢中所涉及的表的統計和檢查，看看是否問題仍然存在。
查詢中使用的結構優化是無法準確估計的基數嗎？ 考慮是否可以修改，因此可避免這一問題的方式在查詢。
-
如果它是不可能修改的模式或查詢，SQL Server 2005有一個新的計劃指導功能，使您可以指定查詢提示添加到查詢符合特定文字。 即席查詢，以及在存儲過程中可以做到這一點。 如OPTION（OPTIMIZE FOR）的，允許你影響基數估計提示，同時保留其潛在的計劃全陣列優化。 其他如OPTION（FORCE ORDER）或Option（使用USE PLAN）提示讓你不同的查詢計劃的控制程度。
查詢內並行
當生成一個查詢執行計劃，SQL Server優化器試圖選擇的計劃，提供最快的響應時間，該查詢。 如果查詢的成本超過parallelism選項和並行的成本閾值中指定的值並沒有被禁用，那麼優化器嘗試生成一個可以並行運行的計劃。 並行查詢計劃使用多個線程來處理查詢，每個線程分佈在可用的CPU，同時利用從每個處理器的CPU時間。 最大並行度是有限的服務器廣泛使用的最大並行度選項，或對每個查詢使用OPTION（MAXDOP）提示。
並行的實際程度上決定（DOP）用於執行了多少線程會做一個平行執行時間推遲，直到給定的操作措施。 SQL Server 2005中執行查詢之前，決定利用和查詢，充分利用剩餘的調度選擇1 DOP的調度是多少。 DOP是選擇一次，查詢運行並行的選擇，直到完成程度。 並行查詢通常使用的CPU時間相似，但略高的金額相比，相應的串行執行計劃，但它這樣做在較短的時間的流逝時間。 只要有，如等待物理I / O並行計劃，一般應使用跨所有處理器的CPU 100％，沒有其他瓶頸。
一個關鍵因素（系統閒置），導致運行並行計劃可以改變查詢後開始執行。 這可以改變，但是，查詢後開始執行。 例如，如果一個查詢來在空閒時間，服務器可以選擇並行計劃運行和使用DOP四個，併產生了四個不同的處理器上的線程。 一旦這些線程開始執行，現有的連接，還需要大量的CPU，可能提交的其他查詢。 在這一點上，所有不同的線程將共享可用的CPU短的時間片，從而導致更高的查詢時間。
並行計劃運行本身並不壞，應提供查詢的響應時間最快的。 然而，對於一個給定查詢的響應時間必須權衡整體吞吐量和響應其他系統上查詢。 並行查詢一般適合批量處理和決策支持工作負載和事務處理環境中未必可取。
發現
使用以下方法可以檢測內部查詢的並行問題。
系統監視器（PerfMon）
看看在SQL Server：SQL統計-批量請求/秒計數器，並請參閱“SQL統計對象”在SQL Server聯機叢書的更多信息，在線。
因爲查詢必須有一個估計成本超過爲並行配置設置（默認爲5）的成本閾值之前，它被認爲並行計劃，分批服務器每秒處理的可能性就越小，批次正在運行的並行計劃。 服務器正在運行的許多並行查詢通常有小批量的每秒請求（例如，值小於100）。
DMV的
從正在運行的服務器，你可以使用以下查詢確定是否有任何積極的請求是並行運行一個給定的會話。
選擇 r.session_id， r.request_id， 最大（ISNULL（exec_context_id，0））number_of_workers的， r.sql_handle， r.statement_start_offset， r.statement_end_offset， r.plan_handle 從 sys.dm_exec_requestsŕ 加入sys.dm_os_tasks中ţ在r.session_id = t.session_id 加入sys.dm_exec_sessions中小號在r.session_id = s.session_id 哪裏 s.is_user_process =爲0x1 小組 r.session_id，r.request_id， r.sql_handle，r.plan_handle， r.statement_start_offset，r.statement_end_offset 有最大（ISNULL（exec_context_id，0））> 0
有了這個信息，可以很容易地進行檢索查詢文本sys.dm_exec_sql_text使用，而該計劃可以檢索使用sys.dm_exec_cached_plan。
你也可以搜索計劃，有資格以並行方式運行。 這可以通過搜索緩存的計劃看，如果一個關係運算符有其作爲一個非零值的並行屬性。 這些計劃可能無法並行運行，但他們有資格這樣做，如果系統是不太忙。
- - 查找可能並行運行的查詢計劃 - 選擇 。* Q。* cp.plan_handle 從 sys.dm_exec_cached_plans CP CROSS APPLY sys.dm_exec_query_plan（cp.plan_handle）P CROSS APPLY sys.dm_exec_sql_text（cp.plan_handle）的爲Q 哪裏 cp.cacheobjtype ='編譯計劃“和 p.query_plan.value（“申報命名空間 P =的“http://schemas.microsoft.com/sqlserver/2004/07/showplan”的; 最大（/ / P：RelOp /並行）'，'浮'）> 0
在一般情況下，查詢的時間長於CPU時間量，因爲花了一些時間等待的資源，如鎖或物理I / O。 查詢可以使用更多的CPU時間比經過的時間的唯一情況是當查詢運行並行計劃等多個線程同時使用CPU。 請注意，並非所有的並行查詢將演示這種行爲（CPU時間比時間）。
注：下表中的代碼片段的某些部分，已經在多行顯示，只爲更好的可讀性。 這些應在單行輸入。
選擇 qs.sql_handle， qs.statement_start_offset， qs.statement_end_offset， q.dbid， q.objectid， q.number， q.encrypted， q.text 從 sys.dm_exec_query_stats的QS CROSS APPLY sys.dm_exec_sql_text（qs.plan_handle）的爲Q 哪裏 qs.total_worker_time> qs.total_elapsed_time SQL跟蹤 尋找並行查詢下列跡象， 它可以是語句或批處理有 CPU時間大於持續時間。 選擇 EventClass， 的TextData 從 :: fn_trace_gettable將（'C：\ TEMP \ high_cpu_trace.trc“ 默認情況下） 哪裏 EventClass（10，12） - RPC：已完成， SQL：BatchCompleted 和CPU> Duration/1000 - CPU是 毫秒，微秒時間或可 顯示計劃（UN編碼），有並行運營] 在他們 選擇 EventClass， 的TextData 從 :: fn_trace_gettable將（'C：\ TEMP \ high_cpu_trace.trc“ 默認情況下） 哪裏 的TextData的LIKE'％並行％
決議
並行計劃運行任何查詢，優化器認爲是足夠昂貴，它將超過並行的成本閾值，默認爲五（參考機器上的執行時間大約5秒）。 通過上述方法確定任何疑問作進一步調整的候選人。
-
使用數據庫引擎優化顧問，看看是否任何索引，索引視圖的變化，或分區變化可以減少查詢的成本。
-
檢查顯着性差異，在實際的估計基數相比，由於基數估計中估計的查詢成本的主要因素。 如果發現任何明顯的差別：
如果自動創建統計信息數據庫選項被禁用，確保有沒有丟失統計在Showplan輸出的警告列項。
嘗試運行UPDATE STATISTICS的基數估計是在桌子上。
Verify that the query doesn't use a query construct that the optimizer can't accurately estimate, such as multi-statement table-valued functions or CLR functions, table variables, or comparisons with a Transact-SQL variable (comparisons with a parameter are OK).
-
Evaluate whether the query could be written in a more efficient fashion using different Transact-SQL statements or expressions.
Poor cursor usage
Versions of SQL Server prior to SQL Server 2005 only supported a single active common per connection. A query that was executing or had results pending to send to the client was considered active. In some situations, the client application might need to read through the results and submit other queries to SQL Server based on the row just read from the result set. This could not be done with a default result set, since it could have other pending results. A common solution was to change the connection properties to use a server-side cursor.
When using a server-side cursor, the database client software (the OLE DB provider or ODBC driver) transparently encapsulates client requests inside of special extended stored procedures, such as sp_cursoropen , sp_cursorfetch , and so forth. This is referred to as an API cursor (as opposed to a TSQL cursor). When the user executes the query, the query text is sent to the server via sp_cursoropen , requests to read from the result set would result in an sp_cursorfetch instructing the server to only send back a certain number of rows. By controlling the number of rows that are fetched, it is possible for the ODBC driver or OLE DB provider to cache the row(s). This prevents a situation where the server is waiting for the client to read all the rows it has sent. Thus, the server is ready to accept a new request on that connection.
Applications that open cursors and fetch one row (or a small number of rows) at a time can easily become bottlenecked by the network latency, especially on a wide area network (WAN). On a fast network with many different user connections, the overhead required to process many cursor requests may become significant. Because of the overhead associated with repositioning the cursor to the appropriate location in the result set, per-request processing overhead, and similar processing, it is more efficient for the server to process a single request that returns 100 rows than to process 100 separate requests which return the same 100 rows but one row at a time.
發現
You can use the following methods to troubleshoot poor cursor usage.
System Monitor (Perfmon)
By looking at the SQL Server:Cursor Manager By Type – Cursor Requests/Sec counter, you can get a general feel for how many cursors are being used on the system by looking at this performance counter. Systems that have high CPU utilization because of small fetch sizes typically have hundreds of cursor requests per second. There are no specific counters to tell you about the fetch buffer size.
DMVs
The following query can be used to determine the connections with API cursors (as opposed to TSQL cursors) that are using a fetch buffer size of one row. It is much more efficient to use a larger fetch buffer, such as 100 rows.
Note: Some parts of the code snippet presented in the following table have been displayed in multiple lines only for better readability. These should be entered in a single line.
選擇 cur.* 從 sys.dm_exec_connections con cross apply sys.dm_exec_cursors(con.session_id) as cur 哪裏 cur.fetch_buffer_size = 1 and cur.properties LIKE 'API%' -- API cursor (TSQL cursors always have fetch buffer of 1)
SQL Trace
Use a trace that includes the RPC:Completed event class search for sp_cursorfetch statements. The value of the fourth parameter is the number of rows returned by the fetch. The maximum number of rows that are requested to be returned is specified as an input parameter in the corresponding RPC:Starting event class.
決議
-
Determine if cursors are the most appropriate means to accomplish the processing or whether a set-based operation, which is generally more efficient, is possible.
-
Consider enabling multiple active results (MARS) when connecting to SQL Server 2005.
-
Consult the appropriate documentation for your specific API to determine how to specify a larger fetch buffer size for the cursor:
ODBC - SQL_ATTR_ROW_ARRAY_SIZE
OLE DB – IRowset::GetNextRows or IRowsetLocate::GetRowsAt
Memory Bottlenecks
This section specifically addresses low memory conditions and ways to diagnose them as well as different memory errors, possible reasons for them, and ways to troubleshoot.
背景
It is quite common to refer to different memory resources by using the single generic term memory . As there are several types of memory resources, it is important to understand and differentiate which particular memory resource is referred to.
Virtual address space and physical memory
In Microsoft Windows®, each process has its own virtual address space (VAS). The set of all virtual addresses available for process use constitutes the size of the VAS. The size of the VAS depends on the architecture (32- or 64-bit) and the operating system. In the context of troubleshooting, it is important to understand that virtual address space is a consumable memory resource and an application can run out of it even on a 64-bit platform while physical memory may still be available.
For more information about virtual address space, see “Process Address Space” in SQL Server Books Online and the article called Virtual Address Space(http://msdn2.microsoft.com/en-us/library/aa366912.aspx) on MSDN.
Address Windowing Extensions (AWE) and SQL Server
Address Windowing Extensions (AWE) is an API that allows a 32-bit application to manipulate physical memory beyond the inherent 32-bit address limit. AWE mechanism technically is not necessary on 64-bit platform. It is, however, present there. Memory pages that are allocated through the AWE mechanism are referred as locked pageson the 64-bit platform.
On both 32- and 64-bit platforms, memory that is allocated through the AWE mechanism cannot be paged out. This can be beneficial to the application. (This is one of the reasons for using AWE mechanism on 64-bit platform.) This also affects the amount of RAM that is available to the system and to other applications, which may have detrimental effects. For this reason, in order to use AWE, the Lock Pages in Memory privilege must be enabled for the account that runs SQL Server.
From a troubleshooting perspective, an important point is that the SQL Server buffer pool uses AWE mapped memory; however, only database (hashed) pages can take full advantage of memory allocated through AWE. Memory allocated through the AWE mechanism is not reported by Task Manager or in the Process: Private Bytesperformance counter. You need to use SQL Server specific counters or Dynamic Management Views to obtain this information.
For more information about AWE mapped memory, see “Managing memory for large databases” and “Memory Architecture” in SQL Server Books Online topics and Large Memory Support (http://msdn2.microsoft.com/library/aa366718.aspx) on MSDN.
The following table summarizes the maximum memory support options for different configurations of SQL Server 2005. (Note that a particular edition of SQL Server or Windows may put more restrictive limits on the amount of supported memory.)
表1
|
組態 |
VAS |
Max physical memory |
AWE/locked pages support |
|---|---|---|---|
|
Native 32-bit on 32-bit OS with /3GB boot parameter 1 |
2 GB的 3 GB的 |
64 GB的 16 GB的 |
是 是 |
|
32-bit on x64 OS (WOW) |
4 GB的 |
64 GB的 |
是 |
|
32-bit on IA64 OS (WOW) |
2 GB的 |
2 GB的 |
沒有 |
|
Native 64-bit on x64 OS |
8 terabyte |
1 terabyte |
是 |
|
Native 64-bit on IA64 OS |
7 terabyte |
1 terabyte |
是 |
Memory pressures
Memory pressure denotes a condition when limited amount of memory is available. Identifying when SQL Server runs under a memory pressure will help you troubleshoot memory-related issues. SQL Server responds differently depending on the type of memory pressure that is present. The following table summarizes the types of memory pressures, and their general underlying causes. In all cases, you are more likely to see timeout or explicit out-of-memory error messages.
表2
|
壓力 |
外部 |
內部 |
|---|---|---|
|
物理 |
Physical memory (RAM) running low. This causes the system to trim working sets of currently running processes, which may result in overall slowdown. SQL Server detects this condition and, depending on the configuration, may reduce the commit target of the buffer pool and start clearing internal caches. |
SQL Server detects high memory consumption internally, causing redistribution of memory between internal components. Internal memory pressure may be a result of:
|
|
虛擬 |
Running low on space in the system page file(s). This may cause the system to fail memory allocations, as it is unable to page out currently allocated memory. This condition may result in the whole system responding very slowly or even bring it to a halt. |
Running low on VAS due to fragmentation (a lot of VAS is available but in small blocks) and/or consumption (direct allocations, DLLs loaded in SQL Server VAS, high number of threads). SQL Server detects this condition and may release reserved regions of VAS, reduce buffer pool commit target, and start shrinking caches. |
Windows has a notification mechanism 2 if physical memory is running high or low. SQL Server uses this mechanism in its memory management decisions.
General troubleshooting steps in each case are explained in Table 3.
表3
|
壓力 |
外部 |
內部 |
|---|---|---|
|
物理 |
|
|
|
虛擬 |
|
|
工具
The following tools and sources of information could be used for troubleshooting.
-
Memory related DMVs
-
DBCC MEMORYSTATUS command
-
Performance counters: performance monitor or DMV for SQL Server specific object
-
任務管理器
-
Event viewer: application log, system log
Detecting memory pressures
Memory pressure by itself does not indicate a problem. Memory pressure is a necessary but not a sufficient condition for the server to encounter memory errors later on. Working under memory pressure could be a normal operating condition of the server. However, signs of memory pressure may indicate that the server runs close to its capacity and the potential for out-of-memory errors exists. In the case of normally operating server, this information could serve as a baseline for determining reasons for out-of-memory conditions later.
External physical memory pressure
Open Task Manager in Performance view and check the Physical Memory section, Available value. If the available memory amount is low, external memory pressure may be present. The exact value depends on many factors, however you can start looking into this when the value drops below 50-100 MB. External memory pressure is clearly present when this amount is less than 10 MB.
The equivalent information can also be obtained using the Memory: Available Bytes counter in System Monitor.
If external memory pressure exists and you are seeing memory-related errors, you will need to identify major consumers of the physical memory on the system. To do this, look at Process: Working Set performance counters or the Mem Usage column on the Processes tab of Task Manager and identify the largest consumers.
The total use of physical memory on the system can be roughly accounted for by summing the following counters.
-
Process object, Working Set counter for each process
-
Memory object
-
Cache Bytes counter for system working set
-
Pool Nonpaged Bytes counter for size of unpaged pool
-
Available Bytes (equivalent of the Available value in Task Manager)
-
If there's no external pressure, the Process: Private Bytes counter or the VM Size in Task Manager should be close to the size of the working set ( Process: Working Set or Task Manager Mem Usage ), which means that we have no memory paged out.
Note that the Mem Usage column in Task Manager and corresponding performance counters do not count memory that is allocated through AWE. Thus the information is insufficient if AWE is enabled. In this case, you need to look at the memory distribution inside SQL Server to get a full picture.
You can use the sys.dm_os_memory_clerks DMV as follows to find out how much memory SQL Server has allocated through AWE mechanism.
選擇 sum(awe_allocated_kb) / 1024 as [AWE allocated, Mb] 從 sys.dm_os_memory_clerks
Note that in SQL Server, currently only buffer pool clerks (type = 'MEMORYCLERK_SQLBUFFERPOOL') use this mechanism and only when AWE is enabled.
Relieving external memory pressure by identifying and eliminating major physical memory consumers (if possible) and/or by adding more memory should generally resolve the problems related to memory.
External virtual memory pressure
You need to determine if page file(s) have enough space to accommodate current memory allocations. To check this, open Task Manager in Performance view and check the Commit Charge section. If Total is close to the Limit , then there exists the potential that page file space may be running low. Limit indicates the maximum amount of memory that can be committed without extending page file space. Note that the Commit Charge Total in Task Manager indicates the potential for page file use, not the actual use. Actual use of the page file will increase under physical memory pressure.
Equivalent information can be obtained from the following counters: Memory: Commit Limit , Paging File: %Usage , Paging File: %Usage Peak .
You can roughly estimate the amount of memory that is paged out per process by subtracting the value of Process: Working Set from the Process Private Bytescounters.
If Paging File: %Usage Peak (or Peak Commit Charge) is high, check the System Event Log for events indicating page file growth or notifications of “running low on virtual memory”. You may need to increase the size of your page file(s). High Paging File: %Usage indicates a physical memory over commitment and should be considered together with external physical memory pressure (large consumers, adequate amount of RAM installed).
Internal physical memory pressure
As internal memory pressure is set by SQL Server itself, a logical step is to look at the memory distribution inside SQL Server by checking for any anomalies in buffer distribution. Normally, the buffer pool accounts for the most of the memory committed by
SQL Server. To determine the amount of memory that belongs to the buffer pool, we can take a look at the DBCC MEMORYSTATUS output. In the Buffer Counts section, look for the Target value. The following shows part of DBCC
MEMORYSTATUS output after the server has reached its normal load.
Buffer Counts Buffers ------------------------------ -------------------- Committed 201120 Target 201120 Hashed 166517 Reserved Potential 143388 Stolen Potential 173556 External Reservation 0 Min Free 256 Visible 201120 Available Paging File 460640
Target is computed by SQL Server as the number of 8-KB pages it can commit without causing paging. Target is recomputed periodically and in response to memory low/high notifications from Windows.
A decrease in the number of target pages on a normally loaded server may indicate response to an external physical memory pressure.
If SQL Server consumed a lot of memory (as determined by Process: Private Bytes or the Mem Usage column in Task Manager), see if the Target count
amounts for a significant portion of the memory. Note that if AWE is enabled, you have to account for AWE allocated memory either from sys.dm_os_memory_clerks or DBCC MEMORYSTATUS output.
Consider the example shown above (AWE not enabled), Target * 8 KB = 1.53 GB, while the Process: Private Bytes for the server is approximately 1.62 GB or the Buffer Pool target accounts for 94% of the memory consumed
by SQL Server. Note that if the server is not loaded, Target is likely to exceed the amount reported by Process: Private Bytes performance counter, which is normal.
If Target is low, but the server Process: Private Bytes or the Mem Usage in Task Manager is high, we might be facing internal memory
pressure from components that use memory from outside the buffer pool. Components that are loaded into the SQL Server process, such as COM objects, linked servers, extended stored procedures, SQLCLR and others, contribute to memory consumption outside of the
buffer pool. There is no easy way to track memory consumed by these components especially if they do not use SQL Server memory interfaces.
Components that are aware of the SQL Server memory management mechanisms use the buffer pool for small memory allocations. If the allocation is bigger than 8 KB, these components use memory outside of the buffer pool through the multi-page allocator interface.
Following is a quick way to check the amount of memory that is consumed through the multi-page allocator.
Note: Some parts of the code snippet presented in the following table have been displayed in multiple lines only for better readability. These should be entered in a single line.
-- amount of mem allocated though multipage allocator interface select sum(multi_pages_kb) from sys.dm_os_memory_clerks
You can get a more detailed distribution of memory allocated through the multi-page allocator as:
選擇 type, sum(multi_pages_kb) 從 sys.dm_os_memory_clerks 哪裏 multi_pages_kb != 0 group by type 類型 ------------------------------------------ --------- MEMORYCLERK_SQLSTORENG 56 MEMORYCLERK_SQLOPTIMIZER 48 MEMORYCLERK_SQLGENERAL 2176 MEMORYCLERK_SQLBUFFERPOOL 536 MEMORYCLERK_SOSNODE 16288 CACHESTORE_STACKFRAMES 16 MEMORYCLERK_SQLSERVICEBROKER 192 MEMORYCLERK_SNI 32
If a significant amount of memory is allocated through the multi-page allocator (100-200 MB or more), further investigation is warranted.
If you are seeing large amounts of memory allocated through the multi-page allocator, check the server configuration and try to determine the components that consume most of the memory by using the previous or the following query.
If Target is low but percentage-wise it accounts for most of the memory consumed by SQL Server, look for sources of the external memory pressure as described in the previous subsection ( External
Physical Memory Pressure ) or check the server memory configuration parameters.
If you have the max server memory and/or min server memory options set, you should compare your target against these values. The max server memory option
limits the maximum amount of memory consumed by the buffer pool, while the server as a whole can still consume more. The min server memory option tells the server not to release buffer pool memory below the setting.
If Target is less than the min server memory setting and the server is under load, this may indicate that the server operates under the external memory pressure and was never
able to acquire the amount specified by this option. It may also indicate the pressure from internal components, as described above. Target count cannot exceed the max server memory option
setting.
First, check for stolen pages count from DBCC MEMORYSTATUS output.
Buffer Distribution Buffers ------------------------------ ----------- Stolen 32871 Free 17845 Cached 1513 Database (clean) 148864 Database (dirty) 259 I/O 0 Latched 0
A high percentage (>75-80%) of stolen pages relative to target (see the previous fragments of the output) is an indicator of the internal memory pressure.
More detailed information about memory allocation by the server components can be assessed by using the sys.dm_os_memory_clerks DMV.
Note: Some parts of the code snippet presented in the following table have been displayed in multiple lines only for better readability. These should be entered in a single line.
-- amount of memory consumed by components outside the Buffer pool -- note that we exclude single_pages_kb as they come from BPool -- BPool is accounted for by the next query 選擇 sum(multi_pages_kb + virtual_memory_committed_kb + shared_memory_committed_kb) as [Overall used w/o BPool, Kb] 從 sys.dm_os_memory_clerks 哪裏 type <> 'MEMORYCLERK_SQLBUFFERPOOL' -- amount of memory consumed by BPool -- note that currenlty only BPool uses AWE 選擇 sum(multi_pages_kb + virtual_memory_committed_kb + shared_memory_committed_kb + awe_allocated_kb) as [Used by BPool with AWE, Kb] 從 sys.dm_os_memory_clerks 哪裏 type = 'MEMORYCLERK_SQLBUFFERPOOL'
Detailed information per component can be obtained as follows. (This includes memory allocated from buffer pool as well as outside the buffer pool.)
Note: Some parts of the code snippet presented in the following table have been displayed in multiple lines only for better readability. These should be entered in a single line.
declare @total_alloc bigint
declare @tab table (
type nvarchar(128) collate database_default
,allocated bigint
,virtual_res bigint
,virtual_com bigint
,awe bigint
,shared_res bigint
,shared_com bigint
,topFive nvarchar(128)
,grand_total bigint
）;
-- note that this total excludes buffer pool
committed memory as it represents the largest
consumer which is normal
選擇
@total_alloc =
sum(single_pages_kb
+ multi_pages_kb
+ (CASE WHEN type <> 'MEMORYCLERK_SQLBUFFERPOOL'
THEN virtual_memory_committed_kb
ELSE 0 END)
+ shared_memory_committed_kb)
從
sys.dm_os_memory_clerks
打印
'Total allocated (including from Buffer Pool): '
+ CAST(@total_alloc as varchar(10)) + ' Kb'
insert into @tab
選擇
type
,sum(single_pages_kb + multi_pages_kb) as allocated
,sum(virtual_memory_reserved_kb) as vertual_res
,sum(virtual_memory_committed_kb) as virtual_com
,sum(awe_allocated_kb) as awe
,sum(shared_memory_reserved_kb) as shared_res
,sum(shared_memory_committed_kb) as shared_com
,case when (
(sum(single_pages_kb
+ multi_pages_kb
+ (CASE WHEN type <> 'MEMORYCLERK_SQLBUFFERPOOL'
THEN virtual_memory_committed_kb
ELSE 0 END)
+ shared_memory_committed_kb))/
(@total_alloc + 0.0)) >= 0.05
then type
else 'Other'
end as topFive
,(sum(single_pages_kb
+ multi_pages_kb
+ (CASE WHEN type <> 'MEMORYCLERK_SQLBUFFERPOOL'
THEN virtual_memory_committed_kb
ELSE 0 END)
+ shared_memory_committed_kb)) as grand_total
從
sys.dm_os_memory_clerks
group by type
order by (sum(single_pages_kb + multi_pages_kb
+ (CASE WHEN type <>
'MEMORYCLERK_SQLBUFFERPOOL' THEN
virtual_memory_committed_kb ELSE 0 END) +
shared_memory_committed_kb)) desc
select * from @tab
Note that the previous query treats Buffer Pool differently as it provides memory to other components via a single-page allocator. To determine the top ten consumers of the buffer pool pages (via a single-page allocator) you can use the following query.
-- top 10 consumers of memory from BPool 選擇 top 10 type, sum(single_pages_kb) as [SPA Mem, Kb] 從 sys.dm_os_memory_clerks group by type order by sum(single_pages_kb) desc
You do not usually have control over memory consumption by internal components. However, determining which components consume most of the memory will help narrow down the investigation of the problem.
System Monitor (Perfmon)
You can also check the following counters for signs of memory pressure (see SQL Server Books Online for detailed description):
SQL Server: Buffer Manager object
-
Low Buffer cache hit ratio
-
Low Page life expectancy
-
High number of Checkpoint pages/sec
-
High number Lazy writes/sec
Insufficient memory and I/O overhead are usually related bottlenecks. See I/O Bottlenecks in this paper.
Caches and memory pressure
An alternative way to look at external and internal memory pressure is to look at the behavior of memory caches.
One of the differences of internal implementation of SQL Server 2005 compared to SQL Server 2000 is uniform caching framework. In order to remove the least recently used entries from caches, the framework implements a clock algorithm. Currently it uses two clock hands—an internal clock hand and an external clock hand.
The internal clock hand controls the size of a cache relative to other caches. It starts moving when the framework predicts that the cache is about to reach its cap.
the external clock hand starts to move when SQL Server as a whole gets into memory pressure. Movement of the external clock hand can be due external as well as internal memory pressure. Do not confuse movement of the internal and external clock hands with internal and external memory pressure.
Information about clock hands movements is exposed through the sys.dm_os_memory_cache_clock_hands DMV as shown in the following code. Each cache entry has a separate row for the internal and the external clock hand.
If you see increasing rounds_count and removed_all_rounds_count , then the server is under the internal/external memory pressure.
選擇* 從 sys.dm_os_memory_cache_clock_hands 哪裏 rounds_count > 0 and removed_all_rounds_count > 0
You can get additional information about the caches such as their size by joining with sys.dm_os_cache_counters DMV as follows.
Note: Some parts of the code snippet presented in the following table have been displayed in multiple lines only for better readability. These should be entered in a single line.
選擇 distinct cc.cache_address, cc.name, cc.type, cc.single_pages_kb + cc.multi_pages_kb as total_kb, cc.single_pages_in_use_kb + cc.multi_pages_in_use_kb as total_in_use_kb, cc.entries_count, cc.entries_in_use_count, ch.removed_all_rounds_count, ch.removed_last_round_count 從 sys.dm_os_memory_cache_counters cc join sys.dm_os_memory_cache_clock_hands ch on (cc.cache_address =ch.cache_address) / * --uncomment this block to have the information only for moving hands caches 哪裏 ch.rounds_count > 0 and ch.removed_all_rounds_count > 0 * / order by total_kb desc
Note that for USERSTORE entries, the amount of pages in use is not reported and thus will be NULL.
Ring buffers
Significant amount of diagnostic memory information can be obtained from the sys.dm_os_ring_buffers ring buffers DMV. Each ring buffer keeps a record of the last number of notifications of a certain kind. Detailed information on specific ring buffers is provided next.
RING_BUFFER_RESOURCE_MONITOR
You can use information from resource monitor notifications to identify memory state changes. Internally, SQL Server has a framework that monitors different memory pressures. When the memory state changes, the resource monitor task generates a notification. This notification is used internally by the components to adjust their memory usage according to the memory state and it is exposed to the user through sys.dm_os_ring_buffers DMV as in the following code.
select record from sys.dm_os_ring_buffers where ring_buffer_type = 'RING_BUFFER_RESOURCE_MONITOR'
A record may look like this:
Note: Some parts of the code snippet presented in the following table have been displayed in multiple lines only for better readability. These should be entered in a single line.
<Record id="1701" type="RING_BUFFER_RESOURCE_MONITOR"
time="149740267">
<ResourceMonitor>
<Notification>RESOURCE_MEMPHYSICAL_LOW<
/Notification>
<Indicators>2</Indicators>
<NodeId>0</NodeId>
</ResourceMonitor>
<MemoryNode id="0">
<ReservedMemory>1646380</ReservedMemory>
<CommittedMemory>432388</CommittedMemory>
<SharedMemory>0</SharedMemory>
<AWEMemory>0</AWEMemory>
<SinglePagesMemory>26592</SinglePagesMemory>
<MultiplePagesMemory>17128</MultiplePagesMemory>
<CachedMemory>17624</CachedMemory>
</MemoryNode>
<MemoryRecord>
<MemoryUtilization>50</MemoryUtilization>
<TotalPhysicalMemory>3833132</TotalPhysicalMemory>
<AvailablePhysicalMemory>3240228<
/AvailablePhysicalMemory>
<TotalPageFile>5732340</TotalPageFile>
<AvailablePageFile>5057100</AvailablePageFile>
<TotalVirtualAddressSpace>2097024<
/TotalVirtualAddressSpace>
<AvailableVirtualAddressSpace>336760
</AvailableVirtualAddressSpace>
<AvailableExtendedVirtualAddressSpace>0
</AvailableExtendedVirtualAddressSpace>
</MemoryRecord>
</Record>
From this record, you can deduce that the server received a low physical memory notification. You can also see the amounts of memory in kilobytes. You can query this information by using the XML capabilities of SQL Server, for example in the following code.
Note: Some parts of the code snippet presented in the following table have been displayed in multiple lines only for better readability. These should be entered in a single line.
選擇 x.value('(//Notification)[1]', 'varchar(max)') as [Type], x.value('(//Record/@time)[1]', 'bigint') as [Time Stamp], x.value('(//AvailablePhysicalMemory)[1]', 'int') as [Avail Phys Mem, Kb], x.value('(//AvailableVirtualAddressSpace)[1]', 'int') as [Avail VAS, Kb] 從 (select cast(record as xml) from sys.dm_os_ring_buffers where ring_buffer_type = 'RING_BUFFER_RESOURCE_MONITOR') as R(x) order by [Time Stamp] desc
Upon receiving a memory low notification, the buffer pool recalculates its target. Note that the target count stays within the limits specified by the min server memoryand max server memory options. If the new committed target for the buffer pool is lower than the currently committed buffers, the buffer pool starts shrinking until external physical memory pressure is removed. Note that SQL Server 2000 did not react to physical memory pressure when running with AWE enabled.
RING_BUFFER_OOM
This ring buffer will contain records indicating server out-of-memory conditions as in the following code example.
select record from sys.dm_os_ring_buffers where ring_buffer_type = 'RING_BUFFER_OOM'
A record may look like this:
<Record id="7301" type="RING_BUFFER_OOM" time="345640123">
<OOM>
<Action>FAIL_VIRTUAL_COMMIT</Action>
<Resources>4096</Resources>
</OOM>
This record tells which operation has failed (commit, reserve, or page allocation) and the amount of memory requested.
RING_BUFFER_MEMORY_BROKER and Internal Memory Pressure
As internal memory pressure is detected, low memory notification is turned on for components that use the buffer pool as the source of memory allocations. Turning on low memory notification allows reclaiming the pages from caches and other components using them.
Internal memory pressure can also be triggered by adjusting the max server memory option or when the percentage of the stolen pages from the buffer pool exceeds 80%.
Internal memory pressure notifications ('Shrink') can be observed by querying memory broker ring buffer as in the following code example.
選擇 x.value('(//Record/@time)[1]', 'bigint') as [Time Stamp], x.value('(//Notification)[1]', 'varchar(100)') as [Last Notification] 從 (select cast(record as xml) from sys.dm_os_ring_buffers where ring_buffer_type = 'RING_BUFFER_MEMORY_BROKER') as R(x) 整理 [Time Stamp] desc
RING_BUFFER_BUFFER_POOL
This ring buffer will contain records indicating severe buffer pool failures, including buffer pool out of memory conditions.
select record from sys.dm_os_ring_buffers where ring_buffer_type = 'RING_BUFFER_BUFFER_POOL'
A record may look like this:
<Record id="1234" type="RING_BUFFER_BUFFER_POOL"
time="345640123">
< BufferPoolFailure id="FAIL_OOM">
<CommittedCount>84344 </CommittedCount>
<CommittedTarget>84350 </CommittedTarget >
<FreeCount>20</FreeCount>
<HashedCount>20345</HashedCount>
<StolenCount>64001 </StolenCount>
<ReservedCount>64001 </ReservedCount>
</ BufferPoolFailure >
This record will tell what failure (FAIL_OOM, FAIL_MAP, FAIL_RESERVE_ADJUST, FAIL_LAZYWRITER_NO_BUFFERS) and the buffer pool status at the time.
Internal virtual memory pressure
VAS consumption can be tracked by using the sys.dm_os_virtual_address_dump DMV. VAS summary can be queries using the following view.
Note: Some parts of the code snippet presented in the following table have been displayed in multiple lines only for better readability. These should be entered in a single line.
-- virtual address space summary view -- generates a list of SQL Server regions -- showing number of reserved and free regions of a given size CREATE VIEW VASummary AS 選擇 Size = VaDump.Size, Reserved = SUM(CASE(CONVERT(INT, VaDump.Base)^0) WHEN 0 THEN 0 ELSE 1 END), Free = SUM(CASE(CONVERT(INT, VaDump.Base)^0) WHEN 0 THEN 1 ELSE 0 END) 從 （ --- combine all allocation according with allocation base, don't take into --- account allocations with zero allocation_base SELECT CONVERT(VARBINARY, SUM(region_size_in_bytes)) AS Size, region_allocation_base_address AS Base FROM sys.dm_os_virtual_address_dump WHERE region_allocation_base_address <> 0x0 GROUP BY region_allocation_base_address 聯合 --- we shouldn't be grouping allocations with zero allocation base --- just get them as is SELECT CONVERT(VARBINARY, region_size_in_bytes), region_allocation_base_address FROM sys.dm_os_virtual_address_dump WHERE region_allocation_base_address = 0x0 ） AS VaDump GROUP BY Size
The following queries can be used to assess VAS state.
-- available memory in all free regions SELECT SUM(Size*Free)/1024 AS [Total avail mem, KB] FROM VASummary WHERE Free <> 0 -- get size of largest availble region SELECT CAST(MAX(Size) AS INT)/1024 AS [Max free size, KB] FROM VASummary WHERE Free <> 0
If the largest available region is smaller than 4 MB, we are likely to be experiencing VAS pressure. SQL Server 2005 monitors and responds to VAS pressure. SQL Server 2000 does not actively monitor for VAS pressure, but reacts by clearing caches when an out-of-virtual-memory error occurs.
General troubleshooting steps in case of memory errors
The following list outlines general steps that will help you troubleshoot memory errors.
-
Verify if the server is operating under external memory pressure. If external pressure is present, try resolving it first, and then see if the problem/errors still exist.
-
Start collecting performance monitor counters for SQL Server: Buffer Manager, SQL Server: Memory Manager.
-
Verify the memory configuration parameters ( sp_configure ), min memory per query , min/max server memory , awe enabled , and the Lock Pages in Memory privilege. Watch for unusual settings. Correct them as necessary. Account for increased memory requirements for SQL Server 2005.
-
Check for any nondefault sp_configure parameters that might indirectly affect the server.
-
Check for internal memory pressures.
-
Observe DBCC MEMORYSTATUS output and the way it changes when you see memory error messages.
-
Check the workload (number of concurrent sessions, currently executing queries).
Memory errors
701 - There is insufficient system memory to run this query.
原因
This is very generic out-of-memory error for the server. It indicates a failed memory allocation. It can be due to a variety of reasons, including hitting memory limits on the current workload. With increased memory requirements for SQL Server 2005 and certain configuration settings (such as the max server memory option) users are more likely to see this error as compared to SQL Server 2000. Usually the transaction that failed is not the cause of this error.
故障排除
Regardless of whether the error is consistent and repeatable (same state) or random (appears at random times with different states), you will need to investigate server memory distribution during the time you see this error. When this error is present, it is possible that the diagnostic queries will fail. Start investigation from external assessment. Follow the steps outlined in General troubleshooting steps in case of memory errors .
Possible solutions include: Remove external memory pressure. Increase the max server memory setting. Free caches by using one of the following commands: DBCC FREESYSTEMCACHE, DBCC FREESESSIONCACHE, or DBCC FREEPROCCACHE. If the problem reappears, reduce workload.
802 - There is insufficient memory available in the buffer pool.
原因
This error does not necessarily indicate an out-of-memory condition. It might indicate that the buffer pool memory is used by someone else. In SQL Server 2005, this error should be relatively rare.
故障排除
Use the general troubleshooting steps and recommendations outlined for the 701 error.
8628 - A time out occurred while waiting to optimize the query. Rerun the query.
原因
This error indicates that a query compilation process failed because it was unable to obtain the amount of memory required to complete the process. As a query undergoes through the compilation process, which includes parsing, algebraization, and optimization, its memory requirements may increase. Thus the query will compete for memory resources with other queries. If the query exceeds a predefined timeout (which increases as the memory consumption for the query increases) while waiting for resources, this error is returned. The most likely reason for this is the presence of a number of large query compilations on the server.
故障排除
-
Follow general troubleshooting steps to see if the server memory consumption is affected in general.
-
Check the workload. Verify the amounts of memory consumed by different components. (See Internal Physical Memory Pressure earlier in this paper.)
-
Check the output of DBCC MEMORYSTATUS for the number of waiters at each gateway (this information will tell you if there are other queries running that consume significant amounts of memory).
Small Gateway Value ------------------------------ -------------------- Configured Units 8 Available Units 8 Acquires 0 Waiters 0 Threshold Factor 250000 Threshold 250000 (6 row(s) affected) Medium Gateway Value ------------------------------ -------------------- Configured Units 2 Available Units 2 Acquires 0 Waiters 0 Threshold Factor 12 (5 row(s) affected) Big Gateway Value ------------------------------ -------------------- Configured Units 1 Available Units 1 Acquires 0 Waiters 0 Threshold Factor 8
-
Reduce workload if possible.
8645 - A time out occurred while waiting for memory resources to execute the query. Rerun the query.
原因
This error indicates that many concurrent memory intensive queries are being executed on the server. Queries that use sorts (ORDER BY) and joins may consume significant amount of memory during execution. Query memory requirements are significantly increased if there is a high degree of parallelism enabled or if a query operates on a partitioned table with non-aligned indexes. A query that cannot get the memory resources it requires within the predefined timeout (by default, the timeout is 25 times the estimated query cost or the sp_configure 'query wait' amount if set) receives this error. Usually, the query that receives the error is not the one that is consuming the memory.
故障排除
-
Follow general steps to assess server memory condition.
-
Identify problematic queries: verify if there is a significant number of queries that operate on partitioned tables, check if they use non-aligned indexes, check if there are many queries involving joins and/or sorts.
-
Check the sp_configure parameters degree of parallelism and min memory per query . Try reducing the degree of parallelism and verify if min memory per query is not set to a high value. If it is set to a high value, even small queries will acquire the specified amount of memory.
-
To find out if queries are waiting on RESOURCE_SEMAPHORE, see Blocking later in this paper.
8651 - Could not perform the requested operation because the minimum query memory is not available. Decrease the configured value for the 'min memory per query' server configuration option.
原因
Causes in part are similar to the 8645 error; it may also be an indication of general memory low condition on the server. A min memory per query option setting that is too high may also generate this error.
故障排除
-
Follow general memory error troubleshooting steps.
-
Verify the sp_configure min memory per query option setting.
I / O瓶頸
SQL Server performance depends heavily on the I/O subsystem. Unless your database fits into physical memory, SQL Server constantly brings database pages in and out of the buffer pool. This generates substantial I/O traffic. Similarly, the log records need to be flushed to the disk before a transaction can be declared committed. And finally, SQL Server uses tempdb for various purposes such as to store intermediate results, to sort, to keep row versions and so on. So a good I/O subsystem is critical to the performance of SQL Server.
Access to log files is sequential except when a transaction needs to be rolled back while access to data files, including tempdb , is randomly accessed. So as a general rule, you should have log files on a separate physical disk than data files for better performance. The focus of this paper is not how to configure your I/O devices but to describe ways to identify if you have I/O bottleneck. Once an I/O bottleneck is identified, you may need to reconfigure your I/O subsystem.
If you have a slow I/O subsystem, your users may experience performance problems such as slow response times, and tasks that abort due to timeouts.
You can use the following performance counters to identify I/O bottlenecks. Note, these AVG values tend to be skewed (to the low side) if you have an infrequent collection interval. For example, it is hard to tell the nature of an I/O spike with 60-second snapshots. Also, you should not rely on one counter to determine a bottleneck; look for multiple counters to cross check the validity of your findings.
-
PhysicalDisk Object: Avg. Disk Queue Length represents the average number of physical read and write requests that were queued on the selected physical disk during the sampling period. If your I/O system is overloaded, more read/write operations will be waiting. If your disk queue length frequently exceeds a value of 2 during peak usage of SQL Server, then you might have an I/O bottleneck.
-
平均。 Disk Sec/Read is the average time, in seconds, of a read of data from the disk. Any number
Less than 10 ms - very good Between 10 - 20 ms - okay Between 20 - 50 ms - slow, needs attention Greater than 50 ms – Serious I/O bottleneck
-
平均。 Disk Sec/Write is the average time, in seconds, of a write of data to the disk. Please refer to the guideline in the previous bullet.
-
Physical Disk: %Disk Time is the percentage of elapsed time that the selected disk drive was busy servicing read or write requests. A general guideline is that if this value is greater than 50 percent, it represents an I/O bottleneck.
-
平均。 Disk Reads/Sec is the rate of read operations on the disk. You need to make sure that this number is less than 85 percent of the disk capacity. The disk access time increases exponentially beyond 85 percent capacity.
-
平均。 Disk Writes/Sec is the rate of write operations on the disk. Make sure that this number is less than 85 percent of the disk capacity. The disk access time increases exponentially beyond 85 percent capacity.
When using above counters, you may need to adjust the values for RAID configurations using the following formulas.
Raid 0 -- I/Os per disk = (reads + writes) / number of disks Raid 1 -- I/Os per disk = [reads + (2 * writes)] / 2 Raid 5 -- I/Os per disk = [reads + (4 * writes)] / number of disks Raid 10 -- I/Os per disk = [reads + (2 * writes)] / number of disks
For example, you have a RAID-1 system with two physical disks with the following values of the counters.
Disk Reads/sec 80
Disk Writes/sec 70
平均。 Disk Queue Length 5
In that case, you are encountering (80 + (2 * 70))/2 = 110 I/Os per disk and your disk queue length = 5/2 = 2.5 which indicates a border line I/O bottleneck.
You can also identify I/O bottlenecks by examining the latch waits. These latch waits account for the physical I/O waits when a page is accessed for reading or writing and the page is not available in the buffer pool. When the page is not found in the buffer pool, an asynchronous I/O is posted and then the status of the I/O is checked. If I/O has already completed, the worker proceeds normally. Otherwise, it waits on PAGEIOLATCH_EX or PAGEIOLATCH_SH, depending upon the type of request. The following DMV query can be used to find I/O latch wait statistics.
Select wait_type,
waiting_tasks_count,
wait_time_ms
from sys.dm_os_wait_stats
where wait_type like 'PAGEIOLATCH%'
order by wait_type
wait_type waiting_tasks_count wait_time_ms signal_wait_time_ms
-------------------------------------------------- ---------------------
PAGEIOLATCH_DT 0 0 0
PAGEIOLATCH_EX 1230 791 11
PAGEIOLATCH_KP 0 0 0
PAGEIOLATCH_NL 0 0 0
PAGEIOLATCH_SH 13756 7241 180
PAGEIOLATCH_UP 80 66 0
Here the latch waits of interest are the underlined ones. When the I/O completes, the worker is placed in the runnable queue. The time between I/O completions until the time the worker is actually scheduled is accounted under the signal_wait_time_ms column.
You can identify an I/O problem if your waiting_task_counts andwait_time_ms deviate significantly from what you see normally. For this, it is important to get a baseline of performance counters
and key DMV query outputs when SQL Server is running smoothly. These wait_types can indicate whether your I/O subsystem is experiencing a bottleneck, but they do not provide any visibility on the physical disk(s) that
are experiencing the problem.
You can use the following DMV query to find currently pending I/O requests. You can execute this query periodically to check the health of I/O subsystem and to isolate physical disk(s) that are involved in the I/O bottlenecks.
選擇
database_id,
file_id,
io_stall,
io_pending_ms_ticks,
scheduler_address
from sys.dm_io_virtual_file_stats(NULL, NULL)t1,
sys.dm_io_pending_io_requests as t2
where t1.file_handle = t2.io_handle
A sample output is as follows. It shows that on a given database, there are three pending I/Os at this moment. You can use the database_id and file_id to find the physical disk the
files are mapped to. The io_pending_ms_ticks represent the total time individual I/Os are waiting in the pending queue.
Database_id File_Id io_stall io_pending_ms_ticks scheduler_address
-------------------------------------------------- --------------------
6 1 10804 78 0x0227A040
6 1 10804 78 0x0227A040
6 2 101451 31 0x02720040
決議
When you have identified an I/O bottleneck, you can address it by doing one or more of the following:
-
Check the memory configuration of SQL Server. If SQL Server has been configured with insufficient memory, it will incur more I/O overhead. You can examine following counters to identify memory pressure
-
Buffer Cache hit ratio
-
Page Life Expectancy
-
Checkpoint pages/sec
-
Lazywrites/sec
For more information on the memory pressure, see Memory Bottlenecks .
-
-
Increase I/O bandwidth.
-
Add more physical drives to the current disk arrays and/or replace your current disks with faster drives. This helps to boost both read and write access times. But don't add more drives to the array than your I/O controller can support.
-
Add faster or additional I/O controllers. Consider adding more cache (if possible) to your current controllers.
-
-
Examine execution plans and see which plans lead to more I/O being consume. It is possible that a better plan (for example, index) can minimize I/O. If there are missing indexes, you may want to run Database Engine Tuning Advisor to find missing indexes
The following DMV query can be used to find which batches/requests are generating the most I/O. You will notice that we are not accounting for physical writes. This is ok if you consider how databases work. The DML/DDL statements within a request do not directly write data pages to disk. Instead, the physical writes of pages to disks is triggered by statements only by committing transactions. Usually physical writes are done by either by Checkpoint or by the SQL Server lazy writer. A DMV query like the following can be used to find the top five requests that generate the most I/Os. Tuning those queries so that they perform fewer logical reads can relieve pressure on the buffer pool. This allows other requests to find the necessary data in the buffer pool in repeated executions (instead of performing physical I/O). Hence, overall system performance is improved.
select top 5 (total_logical_reads/execution_count) as avg_logical_reads, (total_logical_writes/execution_count) as avg_logical_writes, (total_physical_reads/execution_count) as avg_phys_reads, Execution_count, statement_start_offset as stmt_start_offset, sql_handle, plan_handle from sys.dm_exec_query_stats order by (total_logical_reads + total_logical_writes) DescYou can, of course, change this query to get different views on the data. For example, to generate the top five requests that generate most I/Os in single execution, you can order by:
(total_logical_reads + total_logical_writes)/execution_count
Alternatively, you may want to order by physical I/Os and so on. However, logical read/write numbers are very helpful in determining whether or not the plan chosen by the query is optimal. For example, it may be doing a table scan instead of using an index. Some queries, such as those that use nested loop joins may have high logical counters but be more cache-friendly since they revisit the same pages.
Example : Let us take the following two batches consisting of two SQL queries where each table has 1000 rows and rowsize > 8000 (one row per page).
Batch-1
選擇 c1, c5 from t1 INNER HASH JOIN t2 ON t1.c1 = t2.c4 order by c2 Batch-2 select * from t1For the purpose of this example, before running the DMV query, we clear the buffer pool and the procedure cache by running the following commands.
檢查站 dbcc freeproccache dbcc dropcleanbuffersHere is the output of the DMV query. You will notice two rows representing the two batches.
Avg_logical_reads Avg_logical_writes Avg_phys_reads Execution_count stmt_start_offset -------------------------------------------------- --------------------- --------------- 2794 1 385 1 0 1005 0 0 1 146 sql_handle plan_handle -------------------------------------------------- --------------------- ----- 0x0200000099EC8520EFB222CEBF59A72B9BDF4DBEFAE2B6BB x0600050099EC8520A8619803000000000000000000000000 0x0200000099EC8520EFB222CEBF59A72B9BDF4DBEFAE2B6BB x0600050099EC8520A8619803000000000000000000000000
You will notice that the second batch only incurs logical reads but no physical I/O. This is because the data it needs was already cached by the first query (assuming there was sufficient memory).
You can get the text of the query by running the following query.
select text from sys.dm_exec_sql_text( 0x0200000099EC8520EFB222CEBF59A72B9BDF4DBEFAE2B6BB) Here is the output. 選擇 c1, c5 from t1 INNER HASH JOIN t2 ON t1.c1 = t2.c4 order by c2You can also find out the string for the individual statement by executing the following:
選擇 substring(text, (<statement_start_offset>/2), (<statement_end_offset> -<statement_start_offset>)/2) from sys.dm_exec_sql_text (0x0200000099EC8520EFB222CEBF59A72B9BDF4DBEFAE2B6BB)The value of
statement_start_offestandstatement_end_offsetneed to be divided by two in order to compensate for the fact that SQL Server stores this kind of data in Unicode. Astatement_end_offsetvalue of -1, indicates that the statement does go up to the end of the batch. However thesubstring() function does not accommodate -1 as a valid value. Instead of using -1 as(<statement_end_offset> -<statement_start_offset>)/2, one should enter the value 64000, which should make sure that the statement is covered in all cases. With this method, a long-running or resource-consuming statement can be filtered out of a large stored procedure or batch.Similarly, you can run the following query to find to the query plan to identify if the large number of I/Os is a result of a poor plan choice.
選擇* from sys.dm_exec_query_plan (0x0600050099EC8520A8619803000000000000000000000000)
Tempdb
Tempdb globally stores both internal and user objects and the temporary tables, objects, and stored procedures that are created during SQL Server operation.
There is a single tempdb for each SQL Server instance. It can be a performance and disk space bottleneck. The tempdb can become overloaded in terms of space available and excessive DDL/DML operations. This can cause unrelated applications running on the server to slow down or fail.
Some of the common issues with tempdb are as follows:
-
Running out of storage space in tempdb .
-
Queries that run slowly due to the I/O bottleneck in tempdb . This is covered under I/O Bottlenecks .
-
Excessive DDL operations leading to a bottleneck in the system tables.
-
Allocation contention.
Before we start diagnosing problems with tempdb , let us first look at how the space in tempdb is used. It can be grouped into four main categories.
|
User objects |
These are explicitly created by user sessions and are tracked in system catalog. 它們包括以下內容：
|
|
Internal objects |
These are statement scoped objects that are created and destroyed by SQL Server to process queries. These are not tracked in the system catalog. 它們包括以下內容：
As an optimization, when a work table is dropped, one IAM page and an extent is saved to be used with a new work table. There are two exceptions; the temporary LOB storage is batch scoped and cursor worktable is session scoped. |
|
Version Store |
This is used for storing row versions. MARS, online index, triggers and snapshot-based isolation levels are based on row versioning. This is new in SQL Server 2005. |
|
自由空間 |
This represents the disk space that is available in tempdb . |
The total space used by tempdb equal to the User Objects plus the Internal Objects plus the Version Store plus the Free Space.
This free space is same as the performance counter free space in tempdb .
Monitoring tempdb space
It is better to prevent a problem then work to solve it later. You can use the following performance counters to monitor the amount of space tempdb is using.
-
Free Space in tempdb (KB). This counter tracks free space in tempdb in kilobytes. Administrators can use this counter to determine if tempdb is running low on free space.
However, identifying how the different categories, as defined above, are using the disk space in tempdb is a more interesting, and productive, question.
The following query returns the tempdb space used by user and by internal objects. Currently, it provides information for tempdb only.
選擇
SUM (user_object_reserved_page_count)*8 as user_objects_kb,
SUM (internal_object_reserved_page_count)*8 as internal_objects_kb,
SUM (version_store_reserved_page_count)*8 as version_store_kb,
SUM (unallocated_extent_page_count)*8 as freespace_kb
From sys.dm_db_file_space_usage
Where database_id = 2
Here is one sample output (with space in KBs).
user_objets_kb internal_objects_kb version_store_kb freespace_kb ---------------- -------------------- ------------------ ------------ 8736 128 64 448
Note that these calculations don't account for pages in mixed extents. The pages in mixed extents can be allocated to user and internal objects.
Troubleshooting space issues
User objects, internal objects, and version storage can all cause space issues in tempdb . In this section, we consider how you can troubleshoot each of these categories.
User objects
Since user objects are not owned by any specific sessions, you need to understand the specifications of the application that created them and adjust the tempdb size requirements accordingly. You can find the space
used by individual user objects by executing exec sp_spaceused @objname='<user-object>' . For example, you can run the following script to enumerate all the tempdb objects.
DECLARE userobj_cursor CURSOR FOR 選擇 sys.schemas.name + '.' + sys.objects.name from sys.objects, sys.schemas where object_id > 100 and type_desc = 'USER_TABLE'and sys.objects.schema_id = sys.schemas.schema_id 去 open userobj_cursor 去 declare @name varchar(256) fetch userobj_cursor into @name while (@@FETCH_STATUS = 0) 開始 exec sp_spaceused @objname = @name fetch userobj_cursor into @name end close userobj_cursor
Version store
SQL Server 2005 provides a row versioning framework that is used to implement new and existing features. Currently, the following features use row versioning framework. For more information about the following features, see SQL Server Books Online.
-
觸發
-
火星
-
Online index
-
Row versioning-based isolation levels: requires setting an option at database level
Row versions are shared across sessions. The creator of the row version has no control over when the row version can be reclaimed. You will need to find and then possibly kill the longest running transaction that is preventing the row version cleanup.
The following query returns the top two longest running transactions that depend on the versions in the version store.
select top 2
transaction_id,
transaction_sequence_num,
elapsed_time_seconds
from sys.dm_tran_active_snapshot_database_transactions
order by elapsed_time_seconds DESC
Here is a sample output that shows that a transaction with XSN 3 and Transaction ID 8609 has been active for 6523 seconds.
transaction_id transaction_sequence_num elapsed_time_seconds -------------------- ------------------------ -------------------- 8609 3 6523 20156 25 783
Since the second transaction has been active for a relatively short period, you can possibly free up a significant amount of version store by killing the first transaction. However, there is no way to estimate how much version space will be freed up by killing this transaction. You may need to kill few a more transactions to free up significant space.
You can mitigate this problem by either sizing your tempdb properly to account for the version store or by eliminating, where possible, long running transactions under snapshot isolation or long running queries under read-committed-snapshot. You can roughly estimate the size of the version store that is needed by using the following formula. (A factor of two is needed to account for the worst-case scenario, which occurs when the two longest running transactions overlap.)
[Size of version store] = 2 * [version store data generated per minute] * [longest running time (minutes) of the transaction]
In all databases that are enabled for row versioning based isolation levels, the version store data generated per minute for a transaction is about the same as log generated per minute. 不過。 there are some exceptions: only differences are logged for updates; and a newly inserted data row is not versioned but may be logged depending if it is a bulk-logged operation and the recovery mode is not set to full recovery.
You can also use the Version Generation Rate and Version Cleanup Rate performance counters to fine tune your computation. If your Version Cleanup Rate is 0, this implies that there is a long running transaction that is preventing the version store cleanup.
Incidentally, before generating an out of tempdb space error, SQL Server 2005 makes a last ditch attempt by forcing the version stores to shrink. During the shrink process, the longest running transactions that have not yet generated any row versions are marked as victims. This frees up the version space used by them. Message 3967 is generated in the error log for each such victim transaction. If a transaction is marked as a victim, it can no longer read the row versions in the version store or create new ones. Message 3966 is generated and the transaction is rolled back when the victim transaction attempts to read row versions. If the shrink of the version store succeeds, then more space is available in tempdb . Otherwise, tempdb runs out of space.
Internal Objects
Internal objects are created and destroyed for each statement, with exceptions as outlined in the previous table . If you notice that a huge amount of tempdb space is allocated, you will need to know which session or tasks are consuming the space and then possibly take the corrective action.
SQL Server 2005 provides two additional DMVs: sys.dm_db_session_space_usage and sys.dm_db_task_space_usage to track tempdb space that is allocated to sessions and tasks respectively. Though tasks are run in the context of sessions, the space used by tasks is accounted for under sessions only after the task complete.
You can use the following query to find the top sessions that are allocating internal objects. Note that this query includes only the tasks that have been completed in the sessions.
選擇
session_id,
internal_objects_alloc_page_count,
internal_objects_dealloc_page_count
from sys.dm_db_session_space_usage
order by internal_objects_alloc_page_count DESC
You can use the following query to find the top user sessions that are allocating internal objects, including currently active tasks.
選擇
t1.session_id,
(t1.internal_objects_alloc_page_count + task_alloc) as allocated,
(t1.internal_objects_dealloc_page_count + task_dealloc) as
deallocated
from sys.dm_db_session_space_usage as t1,
(select session_id,
sum(internal_objects_alloc_page_count)
as task_alloc,
sum (internal_objects_dealloc_page_count) as
task_dealloc
from sys.dm_db_task_space_usage group by session_id) as t2
where t1.session_id = t2.session_id and t1.session_id >50
order by allocated DESC
Here is a sample output.
session_id allocated deallocated ---------- -------------------- -------------------- 52 5120 5136 51 16 0
Once you have isolated the task or tasks that are generating a lot of internal object allocations, you can find out which Transact-SQL statement it is and its query plan for a more detailed analysis.
選擇
t1.session_id,
t1.request_id,
t1.task_alloc,
t1.task_dealloc,
t2.sql_handle,
t2.statement_start_offset,
t2.statement_end_offset,
t2.plan_handle
from (Select session_id,
request_id,
sum(internal_objects_alloc_page_count) as task_alloc,
sum (internal_objects_dealloc_page_count) as task_dealloc
from sys.dm_db_task_space_usage
group by session_id, request_id) as t1,
sys.dm_exec_requests as t2
where t1.session_id = t2.session_id and
(t1.request_id = t2.request_id)
order by t1.task_alloc DESC
Here is a sample output.
session_id request_id task_alloc task_dealloc
---------------------------------------------------------
52 0 1024 1024
sql_handle statement_start_offset
-------------------------------------------------- ---------------------
0x02000000D490961BDD2A8BE3B0FB81ED67655EFEEB360172 356
statement_end_offset plan_handle
---------------------------------
-1 0x06000500D490961BA8C19503000000000000000000000000
You can use the sql_handle and plan_handle to get the SQL statement and the query plan as follows:
select text from sys.dm_exec_sql_text(@sql_handle) select * from sys.dm_exec_query_plan(@plan_handle)
Note that it is possible that a query plan may not be in the cache when you want to access it. To guarantee the availability of the query plans, you will need to poll the plan cache frequently and save the results, preferably in a table, so that it can be queried later.
When SQL Server is restarted, the tempdb size goes back to the initially configured size and it grows based on the requirements. This can lead to fragmentation of thetempdb and can incur an overhead, including the blocking of the allocation of new extents during the database auto-grow, and expanding the size of the tempdb . This can impact the performance of your workload. It is recommended that you pre-allocate tempdb to the appropriate size.
Excessive DDL and allocation operations
Two sources of contention in tempdb can result in the following situations.
-
Creating and dropping large number of temporary tables and table variables can cause contention on metadata. In SQL Server 2005, local temporary tables and table variables are cached to minimize metadata contention. However, the following conditions must be satisfied, otherwise the table is not cached.
-
No named constraints on the table.
-
No DDL on the table after the creating statement (for example, CREATE INDEX, and CREATE STATISTICS).
-
-
Typically, most temporary/work tables are heaps; therefore, an insert, delete, or drop operation can cause heavy contention on Page Free Space (PFS) pages. If most of these tables are under 64 KB and use mixed extent for allocation or deal location, this can put heavy contention on Shared Global Allocation Map (SGAM) pages. SQL Server 2005 caches one data page and one IAM page for local temporary tables to minimize allocation contention. This caching was already done for work tables starting with SQL Server 2000.
Since SGAM and PFS pages occur at fixed intervals in data files, it is easy to find their resource description. So, for example, 2:1:1 represents the first PFS page in thetempdb (database-id = 2, file-id =1, page-id = 1) and 2:1:3 represents the first SGAM page. SGAM pages occur after every 511232 pages and each PFS page occurs after every 8088 pages. You can use this to find all other PFS and SGAM pages across all files in tempdb . Any time a task is waiting to acquire latch on these pages, it will show up in sys.dm_os_waiting_tasks . Since latch waits are transient, you will need to query this table frequently (about once every 10 seconds) and collect this data for analysis later. For example, you can use the following query to load all tasks waiting on tempdb pages into a waiting_tasks table in the analysis database.
-- get the current timestamp
declare @now datetime
select @now = getdate()
-- insert data into a table for later analysis
insert into analysis..waiting_tasks
select
session_id,
wait_duration_ms,
resource_description,
@now
from sys.dm_os_waiting_tasks
where wait_type like 'PAGE%LATCH_%' and
resource_description like '2:%'
Any time you see tasks waiting to acquire latches on tempdb pages, you can analyze to see if it is due to PFS or SGAM pages. If it is, this implies allocation contention intempdb . If you see contention on other pages in tempdb , and if you can identify that a page belongs to the system table, this implies contention due to excessive DDL operations.
You can also monitor the following Perfmon counters for any unusual increase in the temporary objects allocation/deal location activity.
-
SQL Server: Access Methods \ Workfiles Created /Sec
-
SQL Server: Access Methods \ Worktables Created /Sec
-
SQL Server: Access Methods \ Mixed Page Allocations /Sec
-
SQL Server: General Statistics \ Temp Tables Created /Sec
-
SQL Server: General Statistics \ Temp Tables for destruction
決議
If the contention in tempdb is due to excessive DDL operation, you will need to look at your application and see if you can minimize the DDL operation. You can try the following suggestions.
-
If you use stored procedure scoped temporary tables, consider if these tables can be moved outside of the stored procedure. Otherwise, each execution of the stored procedure will cause a create/drop of the temporary table.
-
Look at query plans to see if some plans create lot of temporary objects, spools, sorts, or worktables. You may need to eliminate some temporary objects. For example, creating an index on a column that is used in ORDER BY may eliminate the sort.
If the contention is due to the contention in SGAM and PFS pages, you can mitigate it by trying the following:
-
Increase the tempdb data files by an equal amount to distribute the workload across all of the disks and files. Ideally, you want to have as many files as there are CPUs (taking into account the affinity).
-
Use TF-1118 to eliminate mixed extent allocations.
Slow-Running Queries
Slow or long running queries can contribute to excessive resource consumption and be the consequence of blocked queries.
Excessive resource consumption is not restricted to CPU resources, but can also include I/O storage bandwidth and memory bandwidth. Even if SQL Server queries are designed to avoid full table scans by restricting the result set with a reasonable WHERE clause, they might not perform as expected if there is not an appropriate index supporting that particular query. Also, WHERE clauses can be dynamically constructed by applications, depending on the user input. Given this, existing indexes cannot cover all possible cases of restrictions. Excessive CPU, I/O, and memory consumption by Transact-SQL statements are covered earlier in this white paper.
In addition to missing indexes, there may be indexes that are not used. As all indexes have to be maintained, this does not impact the performance of a query, but does impact the DML queries.
Queries can also run slowly because of wait states for logical locks and for system resources that are blocking the query. The cause of the blocking can be a poor application design, bad query plans, the lack of useful indexes, and an SQL Server instance that is improperly configured for the workload.
This section focuses on two causes of a slow running query—blocking and index problems.
阻塞
Blocking is primarily waits for logical locks, such as the wait to acquire an X lock on a resource or the waits that results from lower level synchronization primitives such as latches.
Logical lock waits occur when a request to acquire a non-compatible lock on an already locked resource is made. While this is needed to provide the data consistency based on the transaction isolation level at which a particular Transact-SQL statement is running, it does give the end user a perception that SQL Server is running slowly. When a query is blocked, it is not consuming any system resources so you will find it is taking longer but the resource consumption is low. For details on the concurrency control and blocking, see SQL Server Books Online.
Waits on lower level synchronization primitives can result if your system is not configured to handle the workload.
The common scenarios for blocking/waits are:
-
Identifying the blocker
-
Identifying long blocks
-
Blocking per object
-
Page latching issues
-
Overall performance effect of blocking using SQL Server waits
A SQL Server session is placed in a wait state if system resources (or locks) are not currently available to service the request. In other words, the resource has a queue of outstanding requests. DMVs can provide information for any sessions that are waiting on resources.
SQL Server 2005 provides more detailed and consistent wait information, reporting approximately 125 wait types compared with the 76 wait types available in SQL Server 2000. The DMVs that provide this information range from sys.dm_os_wait_statistics for overall and cumulative waits for SQL Server to the session-specificsys.dm_os_waiting_tasks that breaks down waits by session. The following DMV provides details on the wait queue of the tasks that are waiting on some resource. It is a simultaneous representation of all wait queues in the system. For example, you can find out the details about the blocked session 56 by running the following query.
select * from sys.dm_os_waiting_tasks where session_id=56
waiting_task_address session_id exec_context_id wait_duration_ms
wait_type
resource_address blocking_task_address blocking_session_id
blocking_exec_context_id resource_description
-------------------- ---------- --------------- -------------------- -----
------------------------------------------------------- ------------------
--------------------- ------------------- ------------------------ -------
-------------------------------------------------- ------------------------
-------------------------------------------------- ------------------------
-------------------------------------------------- ------------------------
---------------------------
0x022A8898 56 0 1103500
LCK_M_S 0x03696820
0x022A8D48 53 NULL
ridlock fileid=1 pageid=143 dbid=9 id=lock3667d00 mode=X
associatedObjectId=72057594038321152
This result shows that session 56 is blocked by session 53 and that session 56 has been waiting for a lock for 1103500 milliseconds.
To find sessions that have been granted locks or waiting for locks, you can use the sys.dm_tran_locks DMV . Each row represents a currently active request to the lock manager that has either been granted or is waiting to be granted as the request is blocked by a request that has already been granted. For regular locks, a granted request indicates that a lock has been granted on a resource to the requestor. A waiting request indicates that the request has not yet been granted. For example, the following query shows that session 56 is blocked on the resource 1:143:3 that is held in X mode by session 53.
選擇 request_session_id as spid, resource_type as rt, resource_database_id as rdb, (case resource_type WHEN 'OBJECT' then object_name(resource_associated_entity_id) WHEN 'DATABASE' then ' ' ELSE (select object_name(object_id) from sys.partitions where hobt_id=resource_associated_entity_id) END) as objname, resource_description as rd, request_mode as rm, request_status as rs from sys.dm_tran_locks Here is the sample output spid rt rdb objname rd rm rs -------------------------------------------------- ------------------------ --- 56 DATABASE 9 S GRANT 53 DATABASE 9 S GRANT 56 PAGE 9 t_lock 1:143 IS GRANT 53 PAGE 9 t_lock 1:143 IX GRANT 53 PAGE 9 t_lock 1:153 IX GRANT 56 OBJECT 9 t_lock IS GRANT 53 OBJECT 9 t_lock IX GRANT 53 KEY 9 t_lock (a400c34cb X GRANT 53 RID 9 t_lock 1:143:3 X GRANT 56 RID 9 t_lock 1:143:3 S WAIT
You can, in fact, join the above two DMVs as shown with stored proc sp_block . The block report in Figure 1 lists sessions that are blocked and the sessions that are blocking them. You can find the source code in Appendix B. You can alter the stored procedure, if needed, to add/remove the attributes in the Select List. The optional @spid parameter provides details on the lock request and the session that is blocking this particular spid.
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In SQL Server 2000, you can see what spids are blocked information by using the following statement.
select * from master..sysprocesses where blocked <> 0.
The associated locks can be seen with the stored procedure sp_lock .
Identifying long blocks
As mentioned earlier, blocking in SQL Server is common and is a manifestation of the logical locks that are needed to maintain the transactional consistency. However, when the wait for locks exceed a threshold, it may impact the response time. To identify long running blocking, you can use BlockedProcessThreshold configuration parameter to establish a user configured server-wide block threshold. The threshold defines a duration in seconds. Any block that exceeds this threshold will fire an event that can be captured by SQL Trace.
For example, a 200-second blocked process threshold can be configured in SQL Server Management Studio as follows:
-
Execute Sp_configure 'blocked process threshold', 200
-
Reconfigure with override
Once the blocked process threshold is established, the next step is to capture the trace event. The trace events of blocking events that exceed the user configured threshold can be captured with SQL Trace or Profiler.
-
If using SQL Trace, use sp_trace_setevent and event_id=137.
-
If using SQL Server Profiler, select the Blocked Process Report event class (under the Errors and Warnings object). See Figure 2.
![Cc966540.tsfprb02(en-us,TechNet.10).gif]()
Figure 2: Tracing long blocks and deadlocksNote This is a light weight trace, as events are only captured when (1) a block exceeds the threshold, or (2) a deadlock occurs. For each 200-second interval that a lock is blocked, a trace event fires. This means that a single lock that is blocked for 600 seconds results in 3 trace events. See Figure 3.
![Cc966540.tsfprb03(en-us,TechNet.10).gif]()
Figure 3: Reporting Blocking > block threshold
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The traced event includes the entire SQL statements of both the blocker and the one blocked. In this case the “Update Customers” statement is blocking the “Select from Customers” statement.
By comparison, checking for long blocking scenarios in SQL Server 2000 requires custom code to poll Sysprocesses and post-processing the results. Knowledge Base article 271509 contains a sample script that can be used to monitor blocking.
Blocking per object with sys.dm_db_index_operational_stats
The new SQL Server 2005 DMV Sys.dm_db_index_operational_stats provides comprehensive index usage statistics, including blocks. In terms of blocking, it provides a detailed accounting of locking statistics per table, index, and partition. Examples of this includes a history of accesses, locks (row_lock_count), blocks (row_lock_wait_count), and waits (row_lock_wait_in_ms) for a given index or table.
The type of information available through this DMV includes:
-
Count of locks held, for example, row or page.
-
Count of blocks or waits, for example, row, page.
-
Duration of blocks or waits, for example, row, page.
-
Count of page latches waits.
-
Duration of page_latch_wait: This involves contention for a particular page for say, ascending key inserts. In such cases, the hot spot is the last page so multiple writers to the same last page each try to get an exclusive page latch at same time. This will show up as Pagelatch waits.
-
Duration of page_io_latch_wait: I/O latch occurs when a user requests a page that is not in the buffer pool. A slow I/O subsystem, or overworked I/O subsystem will sometimes experience high PageIOlatch waits that are actually I/O issues. These issues can be compounded by cache flushes or missing indexes.
-
Duration of page latch waits.
Besides blocking related information, there is additional information kept for access to index.
-
Types of accesses, for example, range, singleton lookups.
-
Inserts, updates, deletes at the leaf level.
-
Inserts, updates, deletes above the leaf level. Activity above the leaf is index maintenance. The first row on each leaf page has an entry in the level above. If a new page is allocated at the leaf, the level above will have a new entry for the first row on the new leaf page.
-
Pages merged at the leaf level represent empty pages that are de-allocated because rows were deleted.
-
Index maintenance. Pages merged above the leaf level are empty pages de-allocated, due to rows deleted at leaf, thereby leaving intermediate level pages empty. The first row on each leaf page has an entry in the level above. If enough rows are deleted at the leaf level, intermediate level index pages that originally contained entries for the first row on leaf pages will be empty. This causes merges to occur above the leaf.
This information is cumulative from instance startup. The information is not retained across instance restarts, and there is no way to reset it. The data returned by this DMV exists only as long as the metadata cache object representing the heap or index is available. The values for each column are set to zero whenever the metadata for the heap or index is brought into the metadata cache. Statistics are accumulated until the cache object is removed from the metadata cache. However, you can periodically poll this table and collect this information in table that can be queried further.
Appendix B defines one such set of stored procedures that can be used to collect index operational data. You can then analyze the data for the time period of interest. Here are the steps to use the stored procedures defined in Appendix B.
-
Initialize the indexstats table by using init_index_operational_stats.
-
Capture a baseline with insert_indexstats .
-
Run the workload.
-
Capture the final snapshot of index statistics by using insert_indexstats .
-
To analyze the collected index statistics, run the stored procedure get_indexstats to generatethe average number of locks (Row_lock_count for an index and partition), blocks, and waits per index. A high blocking % and/or high average waits can indicate poor index or query formulation.
Here are some examples that show the kind of information you can get using the above set of stored procedures.
-
Get the top five indexes for all databases, order by index usage desc.
exec get_indexstats @dbid=-1, @top='top 5', @columns='index, usage', @order='index usage' -
Get the top five (all columns) index lock promotions where a lock promotion was attempted.
exec get_indexstats @dbid=-1, @top='top 5', @order='index lock promotions', @threshold='[index lock promotion attempts] > 0' -
Get the top five singleton lookups with avg row lock waits>2ms, return columns containing wait, scan, singleton.
exec get_indexstats @dbid=5, @top='top 5', @columns='wait,scan,singleton', @order='singleton lookups', @threshold='[avg row lock wait ms] > 2' -
Get the top ten for all databases, columns containing 'avg, wait', order by wait ms, where row lock waits > 1.
exec get_indexstats @dbid=-1, @top='top 10 ', @columns='wait,row', @order='row lock wait ms', @threshold='[row lock waits] > 1' -
Get the top five index stats, order by avg row lock waits desc.
exec get_indexstats @dbid=-1, @top='top 5', @order='avg row lock wait ms' -
Get the top five index stats, order by avg page latch lock waits desc.
exec get_indexstats @dbid=-1, @top='top 5', @order='avg page latch wait ms' -
Get the top 5 percent index stats, order by avg pageio latch waits.
exec get_indexstats @dbid=-1, @top='top 3 percent', @order='avg pageio latch wait ms', @threshold='[pageio latch waits] > 0' -
Get all index stats for the top ten in db=5, ordered by block% where block% > .1.
exec get_indexstats @dbid=-1, @top='top 10', @order='block %', @threshold='[block %] > 0.1'
See the sample Blocking Analysis Report in Figure 4.
.gif)
SQL Server 2000 does not provide any statistics for the utilization of objects or indexes.
Overall performance effect of blocking using SQL waits
SQL Server 2000 provides 76 wait types for reporting waits. SQL Server 2005 provides over 100 additional wait types for tracking application performance. Any time a user connection is waiting, SQL Server accumulates wait time. For example, the application requests resources such as I/O, locks, or memory and can wait for the resource to be available. This wait information is summarized and categorized across all connections so that a performance profile can be obtained for a given workload. Thus, SQL wait types identify and categorize user (or thread) waits from an application workload or user perspective.
This query lists the top 10 waits in SQL Server. These waits are cumulative but you can reset them using DBCC SQLPERF ([ sys.dm_os_wait_stats ], clear).
select top 10 * from sys.dm_os_wait_stats order by wait_time_ms desc
Following is the output. A few key points to notice are:
-
Some waits are normal such as the waits encountered by background threads such as lazy writer.
-
Some sessions waited a long time to get a SH lock.
-
The signal wait is the time between when a worker has been granted access to the resource and the time it gets scheduled on the CPU. A long signal wait may imply high CPU contention.
wait_type waiting_tasks_count wait_time_ms max_wait_time_ms signal_wait_time_ms ------------------ -------------------- -------------------- ------------- ------- ------- LAZYWRITER_SLEEP 415088 415048437 1812 156 SQLTRACE_BUFFER_FLUSH 103762 415044000 4000 0 LCK_M_S 6 25016812 23240921 0 WRITELOG 7413 86843 187 406 LOGMGR_RESERVE_APPEND 82 82000 1000 0 SLEEP_BPOOL_FLUSH 4948 28687 31 15 LCK_M_X 1 20000 20000 0 PAGEIOLATCH_SH 871 11718 140 15 PAGEIOLATCH_UP 755 9484 187 0 IO_COMPLETION 636 7031 203 0
To analyze the wait states, you need to poll the data periodically and then analyze it later. Appendix B provides the following two sample stored procedures.
-
Track_waitstats . Collects the data for the desired number of samples and interval between the samples. Here is a sample invocation.
exec dbo.track_waitstats @num_samples=6 ,@delay_interval=30 ,@delay_type='s' ,@truncate_history='y' ,@clear_waitstats='y' -
Get_waitstats . Analyzes the data collected in the previous steps. Here is a sample invocation.
exec [dbo].[get_waitstats_2005]
-
Spid is running. It then needs an resource that is currently unavailable. Since the resource is not available, it moves to the resource wait list at time T0.
-
A signal indicates that the resource is available, so spid moves to runnable queue at time T1.
-
Spid awaits running status until T2 as cpu works its way through runnable queue in order of arrival.
-
You can use these stored procedures to analyze the resource waits and signal waits and use this information to isolate the resource contention.
Figure 5 shows a sample report.
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The sample Waitstats Analysis Report in Figure 5 indicates a performance problem due to blocking (LCK_M_S) and memory allocation (RESOURCE_SEMAPHORE). Specifically 55% of all waits are for shared locks while 43% are due to memory requests. An analysis of blocking per object will identify the principal points of contention.
Monitoring index usage
Another aspect of query performance is related to DML queries, queries deleting, inserting and modifying data. The more indexes that are defined on a specific table, the more resources are needed to modify data. In combination with locks held over transactions, longer modification operations can hurt concurrency. Therefore, it can be very important to know which indexes are used by an application over time. You can then figure out whether there is a lot of weight in the database schema in the form of indices which never get used.
SQL Server 2005 provides the new sys.dm_db_index_usage_stats dynamic management view that shows which indexes are used, and whether they are in use by the user query or only by a system operation. With every execution of a query, the columns in this view are incremented according to the query plan that is used for the execution of that query. The data is collected while SQL Server is up and running. The data in this DMV is kept in memory only and is not persisted. So when the SQL Server instance is shut down, the data is lost. You can poll this table periodically and save the data for later analysis.
The operation on indexes is categorized into user type and system type. User type refers to SELECT and INSERT/DELETE/UPDATE operations. System type operations are commands like DBCC statements or DDL commands or update statistics. The columns for each category of statements differentiate into:
-
Seek Operations against an index (user_seeks or system_seeks)
-
Lookup Operations against an index (user_lookups or system_lookups)
-
Scan Operations against an index (user_scans or system_scans)
-
Update Operations against an index (user_updates or system_updates)
For each of these accesses of indexes, the timestamp of the last access is noted as well.
An index itself is identified by three columns covering its database_id, object_id and index_id. Whereas index_id=0 represents a heap table, index_id=1 represents a clustered index whereas index_id>1 represents nonclustered indexes
Over days of runtime of an application against a database, the list of indexes getting accessed in sys.dm_db_index_usage_stats will grow.
The rules and definitions for seek, scan, and lookup work as follows in SQL Server 2005.
-
SEEK: Indicates the count the B-tree structure was used to access the data. It doesn't matter whether the B-tree structure is used just to read a few pages of each level of the index in order to retrieve one data row or whether half of the index pages are read in order to read gigabytes of data or millions of rows out of the underlying table. So it should be expected that most of the hits against an index are accumulated in this category.
-
SCAN: Indicates the count the data layer of the table gets used for retrieval without using one of the index B-trees. In the case of tables that do not have any index defined, this would be the case. In the case of table with indexes defined on it, this can happen when the indexes defined on the table are of no use for the query executed against that statement.
-
LOOKUP: Indicates that a clustered index that is defined on a table did get used to look up data which was identified by 'seeking' through a nonclustered index that is defined on that table as well. This describes the scenario known as bookmark lookup in SQL Server 2000. It represents a scenario where a nonclustered index is used to access a table and the nonclustered index does not cover the columns of the query select list AND the columns defined in the where clause, SQL Server would increment the value of the column
user_seeks
for the nonclustered index used plus the columnuser_lookups
for the entry of the clustered index. This count can become very high if there are multiple nonclustered indexes defined on the table. If the number ofuser_seeks
against a clustered index of a table is pretty high, the number ofuser_lookups
is pretty high as well plus the number ofuser_seeks
of one particular nonclustered index is very high as well, one might be better off by making the nonclustered index with the high count to be the clustered index.
The following DMV query can be used to get useful information about the index usage for all objects in all databases.
select object_id, index_id, user_seeks, user_scans, user_lookups from sys.dm_db_index_usage_stats order by object_id index_id
One can see the following results for a given table.
object_id index_id user_seeks user_scans user_lookups
------------ ------------- -------------- -------------- -----------
------
521690298 1 0 251
123
521690298 2 123 0
0
In this case, there were 251 executions of a query directly accessing the data layer of the table without using one of the indexes. There were 123 executions of a query accessing the table by using the first nonclustered index, which does not cover either the select list of the query or the columns specified in the WHERE clause since we see 123 lookups on the clustered index.
The most interesting category to look at is the 'user type statement' category. Usage indication in the 'system category' can be seen as a result of the existence of the index. If the index did not exist, it would not have to be updated in statistics and it would not need to be checked for consistency. Therefore, the analysis needs to focus on the four columns that indicate usage by ad hoc statements or by the user application.
To get information about the indexes of a specific table that has not been used since the last start of SQL Server, this query can be executed in the context of the database that owns the object.
select i.name
from sys.indexes i
where i.object_id=object_id('<table_name>') and
i.index_id NOT IN (select s.index_id
from sys.dm_db_index_usage_stats s
where s.object_id=i.object_id and
i.index_id=s.index_id and
database_id = <dbid> )
All indexes which haven't been used yet can be retrieved with the following statement:
select object_name(i.object_id),
i.name,
s.user_updates,
s.user_seeks,
s.user_scans,
s.user_lookups
from sys.indexes i
left join sys.dm_db_index_usage_stats s
on s.object_id = i.object_id and
i.index_id = s.index_id and s.database_id = <dbid>>
where objectproperty(i.object_id, 'IsIndexable') = 1 and
-- index_usage_stats has no reference to this index (not being used)
s.index_id is null or
-- index is being updated, but not used by seeks/scans/lookups
(s.user_updates > 0 and s.user_seeks = 0
and s.user_scans = 0 and s.user_lookups = 0)
order by object_name(i.object_id) asc
In this case, the table name and the index name are sorted according to the table name.
The real purpose of this dynamic management view is to observe the usage of indexes in the long run. It might make sense to take a snapshot of that view or a snapshot of the result of the query and store it away every day to compare the changes over time. If you can identify that particular indexes did not get used for months or during periods such as quarter-end reporting or fiscal-year reporting, you could eventually delete those indexes from the database.
結論
欲瞭解更多信息：
http://www.microsoft.com/technet/prodtechnol/sql/default.mspx
Appendix A: DBCC MEMORYSTATUS Description
There is some information that is primarily available by using the DBCC MEMORYSTATUS command. However, some of this information is also available using the dynamic management views (DMVs).
SQL Server 2000 DBCC MEMORYSTATUS is described at
http://support.microsoft.com/?id=271624
SQL Server 2005 DBCC MEMORYSTATUS command is described at
http://support.microsoft.com/?id=907877
Appendix B: Blocking Scripts
This appendix provides the source listing of the stored procedures referred to in this white paper. You can use these stored procedures as they are or tailor them to suit your needs.
sp_block
create proc dbo.sp_block (@spid bigint=NULL) 如 -- This stored procedure is provided "AS IS" with no warranties, and -- confers no rights. -- Use of included script samples are subject to the terms specified at -- http://www.microsoft.com/info/cpyright.htm - -- T. Davidson -- This proc reports blocks -- 1. optional parameter @spid - 選擇 t1.resource_type, 'database'=db_name(resource_database_id), 'blk object' = t1.resource_associated_entity_id, t1.request_mode, t1.request_session_id, t2.blocking_session_id from sys.dm_tran_locks as t1, sys.dm_os_waiting_tasks as t2 哪裏 t1.lock_owner_address = t2.resource_address and t1.request_session_id = isnull(@spid,t1.request_session_id)
Analyzing operational index statistics
This set of stored procedures can be used to analyze index usage.
get_indexstats
create proc dbo.get_indexstats
(@dbid smallint=-1
,@top varchar(100)=NULL
,@columns varchar(500)=NULL
,@order varchar(100)='lock waits'
,@threshold varchar(500)=NULL)
如
-
-- This stored procedure is provided "AS IS" with no warranties, and
-- confers no rights.
-- Use of included script samples are subject to the terms specified at
-- http://www.microsoft.com/info/cpyright.htm
-
-- T. Davidson
-- This proc analyzes index statistics including accesses, overhead,
-- locks, blocks, and waits
-
-- Instructions: Order of execution is as follows:
-- (1) truncate indexstats with init_indexstats
-- (2) take initial index snapshot using insert_indexstats
-- (3) Run workload
-- (4) take final index snapshot using insert_indexstats
-- (5) analyze with get_indexstats
-- @dbid limits analysis to a database
-- @top allows you to specify TOP n
-- @columns is used to specify what columns from
-- sys.dm_db_index_operational_stats will be included in
-- the report
-- For example, @columns='scans,lookups,waits' will include
-- columns
-- containing these keywords
-- @order used to order results
-- @threshold used to add a threshold,
-- example: @threshold='[block %] > 5' only include if
-- blocking is over 5%
-
------ definition of some computed columns returned
-- [blk %] = percentage of locks that cause blocks eg blk% = 100 * lock
-- waits / locks
-- [index usage] = range_scan_count + singleton_lookup_count +
-- leaf_insert_count
-- [nonleaf index overhead]=nonleaf_insert_count + nonleaf_delete_count +
-- nonleaf_update_count
-- [avg row lock wait ms]=row_lock_wait_in_ms/row_lock_wait_count
-- [avg page lock wait ms]=page_lock_wait_in_ms/page_lock_wait_count
-- [avg page latch wait ms]=page_latch_wait_in_ms/page_latch_wait_count
-- [avg pageio latch wait
-- ms]=page_io_latch_wait_in_ms/page_io_latch_wait_count
-------------------------------------------------- ------------------------
-------------------------
--- Case 1 - only one snapshot of sys.dm_db_operational_index_stats was
-- stored in
--- indexstats. This is an error - return errormsg to user
--- Case 2 - beginning snapshot taken, however some objects were not
-- referenced
--- at the time of the beginning snapshot. Thus, they will
-- not be in the initial
--- snapshot of sys.dm_db_operational_index_stats, use 0 for
-- starting values.
--- Print INFO msg for informational purposes.
--- Case 3 - beginning and ending snapshots, beginning values for all
-- objects and indexes
--- this should be the normal case, especially if SQL Server
-- is up a long time
-------------------------------------------------- ------------------------
-------------------------
SET NOCOUNT ON
declare @orderby varchar(100), @where_dbid_is varchar(100), @temp
varchar(500), @threshold_temptab varchar(500)
declare @cmd varchar(max),@col_stmt varchar(500),@addcol varchar(500)
declare @begintime datetime, @endtime datetime, @duration datetime,
@mincount int, @maxcount int
select @begintime = min(now), @endtime = max(now) from indexstats
if @begintime = @endtime
begin
print 'Error: indexstats contains only 1 snapshot of
sys.dm_db_index_operational_stats'
print 'Order of execution is as follows: '
print ' (1) truncate indexstats with init_indexstats'
print ' (2) take initial index snapshot using insert_indexstats'
print ' (3) Run workload'
print ' (4) take final index snapshot using insert_indexstats'
print ' (5) analyze with get_indexstats'
return -99
end
select @mincount = count(*) from indexstats where now = @begintime
select @maxcount = count(*) from indexstats where now = @endtime
if @mincount < @maxcount
begin
print 'InfoMsg1: sys.dm_db_index_operational_stats only contains
entries for objects referenced since last SQL re-cycle'
print 'InfoMsg2: Any newly referenced objects and indexes captured
in the ending snapshot will use 0 as a beginning value'
end
select @top = case
when @top is NULL then ''
else lower(@top)
end,
@where_dbid_is = case (@dbid)
when -1 then ''
else ' and i1.database_id = ' + cast(@dbid as varchar(10))
end,
--- thresholding requires a temp table
@threshold_temptab = case
when @threshold is NULL then ''
else ' select * from #t where ' + @threshold
end
--- thresholding requires temp table, add 'into #t' to select statement
select @temp = case (@threshold_temptab)
when '' then ''
else ' into #t '
end
select @orderby=case(@order)
when 'leaf inserts' then 'order by [' + @order + ']'
when 'leaf deletes' then 'order by [' + @order + ']'
when 'leaf updates' then 'order by [' + @order + ']'
when 'nonleaf inserts' then 'order by [' + @order + ']'
when 'nonleaf deletes' then 'order by [' + @order + ']'
when 'nonleaf updates' then 'order by [' + @order + ']'
when 'nonleaf index overhead' then 'order by [' + @order + ']'
when 'leaf allocations' then 'order by [' + @order + ']'
when 'nonleaf allocations' then 'order by [' + @order + ']'
when 'allocations' then 'order by [' + @order + ']'
when 'leaf page merges' then 'order by [' + @order + ']'
when 'nonleaf page merges' then 'order by [' + @order + ']'
when 'range scans' then 'order by [' + @order + ']'
when 'singleton lookups' then 'order by [' + @order + ']'
when 'index usage' then 'order by [' + @order + ']'
when 'row locks' then 'order by [' + @order + ']'
when 'row lock waits' then 'order by [' + @order + ']'
when 'block %' then 'order by [' + @order + ']'
when 'row lock wait ms' then 'order by [' + @order + ']'
when 'avg row lock wait ms' then 'order by [' + @order + ']'
when 'page locks' then 'order by [' + @order + ']'
when 'page lock waits' then 'order by [' + @order + ']'
when 'page lock wait ms' then 'order by [' + @order + ']'
when 'avg page lock wait ms' then 'order by [' + @order + ']'
when 'index lock promotion attempts' then 'order by [' + @order + ']'
when 'index lock promotions' then 'order by [' + @order + ']'
when 'page latch waits' then 'order by [' + @order + ']'
when 'page latch wait ms' then 'order by [' + @order + ']'
when 'pageio latch waits' then 'order by [' + @order + ']'
when 'pageio latch wait ms' then 'order by [' + @order + ']'
else ''
結束
if @orderby <> '' select @orderby = @orderby + ' desc'
選擇
'start time'=@begintime,
'end time'=@endtime,
'duration (hh:mm:ss:ms)'=convert(varchar(50),
@endtime-@begintime,14),
'Report'=case (@dbid)
when -1 then 'all databases'
else db_name(@dbid)
end +
case
when @top = '' then ''
when @top is NULL then ''
when @top = 'none' then ''
else ', ' + @top
end +
case
when @columns = '' then ''
when @columns is NULL then ''
when @columns = 'none' then ''
else ', include only columns containing ' + @columns
end +
case(@orderby)
when '' then ''
when NULL then ''
when 'none' then ''
else ', ' + @orderby
end +
case
when @threshold = '' then ''
when @threshold is NULL then ''
when @threshold = 'none' then ''
else ', threshold on ' + @threshold
end
select @cmd = ' select i2.database_id, i2.object_id, i2.index_id,
i2.partition_number '
select @cmd = @cmd +' , begintime=case min(i1.now) when max(i2.now) then
NULL else min(i1.now) end '
select @cmd = @cmd +' , endtime=max(i2.now) '
select @cmd = @cmd +' into #i '
select @cmd = @cmd +' from indexstats i2 '
select @cmd = @cmd +' full outer join '
select @cmd = @cmd +' indexstats i1 '
select @cmd = @cmd +' on i1.database_id = i2.database_id '
select @cmd = @cmd +' and i1.object_id = i2.object_id '
select @cmd = @cmd +' and i1.index_id = i2.index_id '
select @cmd = @cmd +' and i1.partition_number = i2.partition_number '
select @cmd = @cmd +' where i1.now >= ''' +
convert(varchar(100),@begintime, 109) + ''''
select @cmd = @cmd +' and i2.now = ''' + convert(varchar(100),@endtime,
109) + ''''
select @cmd = @cmd + ' ' + @where_dbid_is + ' '
select @cmd = @cmd + ' group by i2.database_id, i2.object_id, i2.index_id,
i2.partition_number '
select @cmd = @cmd + ' select ' + @top + ' i.database_id,
db_name=db_name(i.database_id),
object=isnull(object_name(i.object_id),i.object_id), indid=i.index_id,
part_no=i.partition_number '
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[leaf inserts]=i2.leaf_insert_count -
isnull(i1.leaf_insert_count,0)'
select @cmd = @cmd +@addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,@col_stmt=' ,
[leaf deletes]=i2.leaf_delete_count –
isnull(i1.leaf_delete_count,0)'
select @cmd = @cmd + @addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[leaf updates]=i2.leaf_update_count –
isnull(i1.leaf_update_count,0)'
select @cmd = @cmd + @addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[nonleaf inserts]=i2.nonleaf_insert_count –
isnull(i1.nonleaf_insert_count,0)'
select @cmd = @cmd + @addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[nonleaf deletes]=i2.nonleaf_delete_count –
isnull(i1.nonleaf_delete_count,0)'
select @cmd = @cmd + @addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[nonleaf updates]=i2.nonleaf_update_count –
isnull(i1.nonleaf_update_count,0)'
select @cmd = @cmd + @addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[nonleaf index overhead]=(i2.nonleaf_insert_count –
isnull(i1.nonleaf_insert_count,0)) + (i2.nonleaf_delete_count –
isnull(i1.nonleaf_delete_count,0)) + (i2.nonleaf_update_count –
isnull(i1.nonleaf_update_count,0))'
select @cmd = @cmd + @addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[leaf allocations]=i2.leaf_allocation_count –
isnull(i1.leaf_allocation_count,0)'
select @cmd = @cmd + @addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[nonleaf allocations]=i2.nonleaf_allocation_count –
isnull(i1.nonleaf_allocation_count,0)'
select @cmd = @cmd +@addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[allocations]=(i2.leaf_allocation_count –
isnull(i1.leaf_allocation_count,0)) + (i2.nonleaf_allocation_count –
isnull(i1.nonleaf_allocation_count,0))'
select @cmd = @cmd +@addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[leaf page merges]=i2.leaf_page_merge_count –
isnull(i1.leaf_page_merge_count,0)'
select @cmd = @cmd + @addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[nonleaf page merges]=i2.nonleaf_page_merge_count –
isnull(i1.nonleaf_page_merge_count,0)'
select @cmd = @cmd + @addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[range scans]=i2.range_scan_count –
isnull(i1.range_scan_count,0)'
select @cmd = @cmd + @addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing= @columns,
@col_stmt=' ,[singleton lookups]=i2.singleton_lookup_count –
isnull(i1.singleton_lookup_count,0)'
select @cmd = @cmd +@addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[index usage]=(i2.range_scan_count –
isnull(i1.range_scan_count,0)) + (i2.singleton_lookup_count –
isnull(i1.singleton_lookup_count,0)) + (i2.leaf_insert_count –
isnull(i1.leaf_insert_count,0))'
select @cmd = @cmd + @addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[row locks]=i2.row_lock_count –
isnull(i1.row_lock_count,0)'
select @cmd = @cmd + @addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[row lock waits]=i2.row_lock_wait_count –
isnull(i1.row_lock_wait_count,0)'
select @cmd = @cmd + @addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[block %]=cast (100.0 * (i2.row_lock_wait_count –
isnull(i1.row_lock_wait_count,0)) / (1 + i2.row_lock_count –
isnull(i1.row_lock_count,0)) as numeric(5,2))'
select @cmd = @cmd + @addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[row lock wait ms]=i2.row_lock_wait_in_ms –
isnull(i1.row_lock_wait_in_ms,0)'
select @cmd = @cmd + @addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[avg row lock wait ms]=cast ((1.0*(i2.row_lock_wait_in_ms
- isnull(i1.row_lock_wait_in_ms,0)))/(1 + i2.row_lock_wait_count -
isnull(i1.row_lock_wait_count,0)) as numeric(20,1))'
select @cmd = @cmd +@addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[page locks]=i2.page_lock_count –
isnull(i1.page_lock_count,0)'
select @cmd = @cmd +@addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[page lock waits]=i2.page_lock_wait_count –
isnull(i1.page_lock_wait_count,0)'
select @cmd = @cmd +@addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[page lock wait ms]=i2.page_lock_wait_in_ms –
isnull(i1.page_lock_wait_in_ms,0)'
select @cmd = @cmd +@addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[avg page lock wait ms]=cast
((1.0*(i2.page_lock_wait_in_ms - isnull(i1.page_lock_wait_in_ms,0)))/(1 +
i2.page_lock_wait_count - isnull(i1.page_lock_wait_count,0)) as
numeric(20,1))'
select @cmd = @cmd +@addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[index lock promotion
attempts]=i2.index_lock_promotion_attempt_count –
isnull(i1.index_lock_promotion_attempt_count,0)'
select @cmd = @cmd +@addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[index lock promotions]=i2.index_lock_promotion_count –
isnull(i1.index_lock_promotion_count,0)'
select @cmd = @cmd +@addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[page latch waits]=i2.page_latch_wait_count –
isnull(i1.page_latch_wait_count,0)'
select @cmd = @cmd +@addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[page latch wait ms]=i2.page_latch_wait_in_ms –
isnull(i1.page_latch_wait_in_ms,0)'
select @cmd = @cmd +@addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[avg page latch wait ms]=cast
((1.0*(i2.page_latch_wait_in_ms - isnull(i1.page_latch_wait_in_ms,0)))/(1
+ i2.page_latch_wait_count - isnull(i1.page_latch_wait_count,0)) as
numeric(20,1))'
select @cmd = @cmd +@addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[pageio latch waits]=i2.page_io_latch_wait_count –
isnull(i1.page_latch_wait_count,0)'
select @cmd = @cmd +@addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[pageio latch wait ms]=i2.page_io_latch_wait_in_ms –
isnull(i1.page_latch_wait_in_ms,0)'
select @cmd = @cmd +@addcol
exec dbo.add_column
@add_stmt=@addcol out,
@cols_containing=@columns,
@col_stmt=' ,[avg pageio latch wait ms]=cast
((1.0*(i2.page_io_latch_wait_in_ms –
isnull(i1.page_io_latch_wait_in_ms,0)))/(1 + i2.page_io_latch_wait_count –
isnull(i1.page_io_latch_wait_count,0)) as numeric(20,1))'
select @cmd = @cmd +@addcol
select @cmd = @cmd + @temp
select @cmd = @cmd + ' from #ii '
select @cmd = @cmd + ' left join indexstats i1 on i.begintime = i1.now and
i.database_id = i1.database_id and i.object_id = i1.object_id and
i.index_id = i1.index_id and i.partition_number = i1.partition_number '
select @cmd = @cmd + ' left join indexstats i2 on i.endtime = i2.now and
i.database_id = i2.database_id and i.object_id = i2.object_id and
i.index_id = i2.index_id and i.partition_number = i2.partition_number '
select @cmd = @cmd + ' ' + @orderby + ' '
select @cmd = @cmd + @threshold_temptab
exec ( @cmd )
去
insert_indexstats
create proc insert_indexstats (@dbid smallint=NULL,
@objid int=NULL,
@indid int=NULL,
@partitionid int=NULL)
如
-
-- This stored procedure is provided "AS IS" with no warranties, and
confers no rights.
-- Use of included script samples are subject to the terms specified at
http://www.microsoft.com/info/cpyright.htm
-- This stored procedure stores a snapshot of
sys.dm_db_index_operational_stats into the table indexstas
-- for later analysis by the stored procedure get_indexstats. 請注意：
that the indexstats table has an additional
-- column to store the timestamp when the snapshot is taken
-
-- T. Davidson
-- snapshot sys.dm_db_index_operational_stats
-
declare @now datetime
select @now = getdate()
insert into indexstats
(database_id
,object_id
,index_id
,partition_number
,leaf_insert_count
,leaf_delete_count
,leaf_update_count
,leaf_ghost_count
,nonleaf_insert_count
,nonleaf_delete_count
,nonleaf_update_count
,leaf_allocation_count
,nonleaf_allocation_count
,leaf_page_merge_count
,nonleaf_page_merge_count
,range_scan_count
,singleton_lookup_count
,forwarded_fetch_count
,lob_fetch_in_pages
,lob_fetch_in_bytes
,lob_orphan_create_count
,lob_orphan_insert_count
,row_overflow_fetch_in_pages
,row_overflow_fetch_in_bytes
,column_value_push_off_row_count
,column_value_pull_in_row_count
,row_lock_count
,row_lock_wait_count
,row_lock_wait_in_ms
,page_lock_count
,page_lock_wait_count
,page_lock_wait_in_ms
,index_lock_promotion_attempt_count
,index_lock_promotion_count
,page_latch_wait_count
,page_latch_wait_in_ms
,page_io_latch_wait_count
,page_io_latch_wait_in_ms,
now)
select database_id
,object_id
,index_id
,partition_number
,leaf_insert_count
,leaf_delete_count
,leaf_update_count
,leaf_ghost_count
,nonleaf_insert_count
,nonleaf_delete_count
,nonleaf_update_count
,leaf_allocation_count
,nonleaf_allocation_count
,leaf_page_merge_count
,nonleaf_page_merge_count
,range_scan_count
,singleton_lookup_count
,forwarded_fetch_count
,lob_fetch_in_pages
,lob_fetch_in_bytes
,lob_orphan_create_count
,lob_orphan_insert_count
,row_overflow_fetch_in_pages
,row_overflow_fetch_in_bytes
,column_value_push_off_row_count
,column_value_pull_in_row_count
,row_lock_count
,row_lock_wait_count
,row_lock_wait_in_ms
,page_lock_count
,page_lock_wait_count
,page_lock_wait_in_ms
,index_lock_promotion_attempt_count
,index_lock_promotion_count
,page_latch_wait_count
,page_latch_wait_in_ms
,page_io_latch_wait_count
,page_io_latch_wait_in_ms
,@now
from sys.dm_db_index_operational_stats(@dbid,@objid,@indid,@partitionid)
去
init_index_operational_stats
CREATE proc dbo.init_index_operational_stats 如 - -- This stored procedure is provided "AS IS" with no warranties, and -- confers no rights. -- Use of included script samples are subject to the terms specified at -- http://www.microsoft.com/info/cpyright.htm - -- T. Davidson - -- create indexstats table if it doesn't exist, otherwise truncate - SET NOCOUNT ON if not exists (select 1 from dbo.sysobjects where id=object_id(N'[dbo].[indexstats]') and OBJECTPROPERTY(id, N'IsUserTable') = 1) create table dbo.indexstats ( database_id smallint NOT NULL ,object_id int NOT NULL ,index_id int NOT NULL ,partition_number int NOT NULL ,leaf_insert_count bigint NOT NULL ,leaf_delete_count bigint NOT NULL ,leaf_update_count bigint NOT NULL ,leaf_ghost_count bigint NOT NULL ,nonleaf_insert_count bigint NOT NULL ,nonleaf_delete_count bigint NOT NULL ,nonleaf_update_count bigint NOT NULL ,leaf_allocation_count bigint NOT NULL ,nonleaf_allocation_count bigint NOT NULL ,leaf_page_merge_count bigint NOT NULL ,nonleaf_page_merge_count bigint NOT NULL ,range_scan_count bigint NOT NULL ,singleton_lookup_count bigint NOT NULL ,forwarded_fetch_count bigint NOT NULL ,lob_fetch_in_pages bigint NOT NULL ,lob_fetch_in_bytes bigint NOT NULL ,lob_orphan_create_count bigint NOT NULL ,lob_orphan_insert_count bigint NOT NULL ,row_overflow_fetch_in_pages bigint NOT NULL ,row_overflow_fetch_in_bytes bigint NOT NULL ,column_value_push_off_row_count bigint NOT NULL ,column_value_pull_in_row_count bigint NOT NULL ,row_lock_count bigint NOT NULL ,row_lock_wait_count bigint NOT NULL ,row_lock_wait_in_ms bigint NOT NULL ,page_lock_count bigint NOT NULL ,page_lock_wait_count bigint NOT NULL ,page_lock_wait_in_ms bigint NOT NULL ,index_lock_promotion_attempt_count bigint NOT NULL ,index_lock_promotion_count bigint NOT NULL ,page_latch_wait_count bigint NOT NULL ,page_latch_wait_in_ms bigint NOT NULL ,page_io_latch_wait_count bigint NOT NULL ,page_io_latch_wait_in_ms bigint NOT NULL ,now datetime default getdate()) else truncate table dbo.indexstats 去
add_column
create proc dbo.add_column (
@add_stmt varchar(500) output,
@find varchar(100)=NULL,
@cols_containing varchar(500)=NULL,
@col_stmt varchar(max))
如
-
-- This stored procedure is provided "AS IS" with no warranties, and
-- confers no rights.
-- Use of included script samples are subject to the terms specified at
-- http://www.microsoft.com/info/cpyright.htm
-
-- T. Davidson
-- @add_stmt is the result passed back to the caller
-- @find is a keyword from @cols_containing
-- @cols_containing is the list of keywords to include in the report
-- @col_stmt is the statement that will be compared with @find.
-- If @col_stmt contains @find, include this statement.
-- set @add_stmt = @col_stmt
-
declare @length int, @strindex int, @EOS bit
if @cols_containing is NULL
begin
select @add_stmt=@col_stmt
return
end
select @add_stmt = '', @EOS = 0
while @add_stmt is not null and @EOS = 0
@dbid=-1,
select @strindex = charindex(',',@cols_containing)
if @strindex = 0
select @find = @cols_containing, @EOS = 1
else
begin
select @find = substring(@cols_containing,1,@strindex-1)
select @cols_containing =
substring(@cols_containing,
@strindex+1,
datalength(@cols_containing) - @strindex)
end
select @add_stmt=case
--when @cols_containing is NULL then NULL
when charindex(@find,@col_stmt) > 0 then NULL
else ''
end
結束
--- NULL indicates this statement is to be passed back through out parm
@add_stmt
if @add_stmt is NULL select @add_stmt=@col_stmt
去
Wait states
This set of stored procedures can be used to analyze the blocking in SQL Server.
track_waitstats_2005
CREATE proc [dbo].[track_waitstats_2005] (
@num_samples int=10,
@delay_interval int=1,
@delay_type nvarchar(10)='minutes',
@truncate_history nvarchar(1)='N',
@clear_waitstats nvarchar(1)='Y')
如
-
-- This stored procedure is provided "AS IS" with no warranties, and
-- confers no rights.
-- Use of included script samples are subject to the terms specified at
-- http://www.microsoft.com/info/cpyright.htm
-
-- T. Davidson
-- @num_samples is the number of times to capture waitstats, default is 10
-- times
-- default delay interval is 1 minute
-- delaynum is the delay interval - can be minutes or seconds
-- delaytype specifies whether the delay interval is minutes or seconds
-- create waitstats table if it doesn't exist, otherwise truncate
-- Revision: 4/19/05
--- (1) added object owner qualifier
--- (2) optional parameters to truncate history and clear waitstats
SET NOCOUNT ON
if not exists (select 1
from sys.objects
where object_id = object_id ( N'[dbo].[waitstats]') and
OBJECTPROPERTY(object_id, N'IsUserTable') = 1)
create table [dbo].[waitstats]
([wait_type] nvarchar(60) not null,
[waiting_tasks_count] bigint not null,
[wait_time_ms] bigint not null,
[max_wait_time_ms] bigint not null,
[signal_wait_time_ms] bigint not null,
now datetime not null default getdate())
If lower(@truncate_history) not in (N'y',N'n')
begin
raiserror ('valid @truncate_history values are ''y'' or
''n''',16,1) with nowait
end
If lower(@clear_waitstats) not in (N'y',N'n')
begin
raiserror ('valid @clear_waitstats values are ''y'' or
''n''',16,1) with nowait
end
If lower(@truncate_history) = N'y'
truncate table dbo.waitstats
If lower (@clear_waitstats) = N'y'
-- clear out waitstats
dbcc sqlperf ([sys.dm_os_wait_stats],clear) with no_infomsgs
declare @i int,
@delay varchar(8),
@dt varchar(3),
@now datetime,
@totalwait numeric(20,1),
@endtime datetime,
@begintime datetime,
@hr int,
@min int,
@sec int
select @i = 1
select @dt = case lower(@delay_type)
when N'minutes' then 'm'
when N'minute' then 'm'
when N'min' then 'm'
when N'mi' then 'm'
when N'n' then 'm'
when N'm' then 'm'
when N'seconds' then 's'
when N'second' then 's'
when N'sec' then 's'
when N'ss' then 's'
when N's' then 's'
else @delay_type
結束
if @dt not in ('s','m')
開始
raiserror ('delay type must be either ''seconds'' or
''minutes''',16,1) with nowait
return
結束
if @dt = 's'
開始
select @sec = @delay_interval % 60, @min = cast((@delay_interval / 60)
as int), @hr = cast((@min / 60) as int)
結束
if @dt = 'm'
開始
select @sec = 0, @min = @delay_interval % 60, @hr =
cast((@delay_interval / 60) as int)
結束
select @delay= right('0'+ convert(varchar(2),@hr),2) + ':' +
+ right('0'+convert(varchar(2),@min),2) + ':' +
+ right('0'+convert(varchar(2),@sec),2)
if @hr > 23 or @min > 59 or @sec > 59
開始
select 'delay interval and type: ' + convert
(varchar(10),@delay_interval) + ',' + @delay_type + ' converts to ' +
@delay
raiserror ('hh:mm:ss delay time cannot > 23:59:59',16,1) with nowait
return
結束
while (@i <= @num_samples)
開始
select @now = getdate()
insert into [dbo].[waitstats] (
[wait_type],
[waiting_tasks_count],
[wait_time_ms],
[max_wait_time_ms],
[signal_wait_time_ms],
now)
select
[wait_type],
[waiting_tasks_count],
[wait_time_ms],
[max_wait_time_ms],
[signal_wait_time_ms],
@now
from sys.dm_os_wait_stats
insert into [dbo].[waitstats] (
[wait_type],
[waiting_tasks_count],
[wait_time_ms],
[max_wait_time_ms],
[signal_wait_time_ms],
now)
select
'Total',
sum([waiting_tasks_count]),
sum([wait_time_ms]),
0,
sum([signal_wait_time_ms]),
@now
from [dbo].[waitstats]
where now = @now
select @i = @i + 1
waitfor delay @delay
結束
--- create waitstats report
execute dbo.get_waitstats_2005
去
exec dbo.track_waitstats @num_samples=6
,@delay_interval=30
,@delay_type='s'
,@truncate_history='y'
,@clear_waitstats='y'
get_waitstats_2005
CREATE proc [dbo].[get_waitstats_2005] (
@report_format varchar(20)='all',
@report_order varchar(20)='resource')
如
-- This stored procedure is provided "AS IS" with no warranties, and
-- confers no rights.
-- Use of included script samples are subject to the terms specified at
-- http://www.microsoft.com/info/cpyright.htm
-
-- this proc will create waitstats report listing wait types by
-- percentage.
-- (1) total wait time is the sum of resource & signal waits,
-- @report_format='all' reports resource & signal
-- (2) Basics of execution model (simplified)
-- a. spid is running then needs unavailable resource, moves to
-- resource wait list at time T0
-- b. a signal indicates resource available, spid moves to
-- runnable queue at time T1
-- c. spid awaits running status until T2 as cpu works its way
-- through runnable queue in order of arrival
-- (3) resource wait time is the actual time waiting for the
-- resource to be available, T1-T0
-- (4) signal wait time is the time it takes from the point the
-- resource is available (T1)
-- to the point in which the process is running again at T2.
-- Thus, signal waits are T2-T1
-- (5) Key questions: Are Resource and Signal time significant?
-- a. Highest waits indicate the bottleneck you need to solve
-- for scalability
-- b. Generally if you have LOW% SIGNAL WAITS, the CPU is
-- handling the workload eg spids spend move through
-- runnable queue quickly
-- c. HIGH % SIGNAL WAITS indicates CPU can't keep up,
-- significant time for spids to move up the runnable queue
-- to reach running status
-- (6) This proc can be run when track_waitstats is executing
-
-- Revision 4/19/2005
-- (1) add computation for CPU Resource Waits = Sum(signal waits /
-- total waits)
-- (2) add @report_order parm to allow sorting by resource, signal
-- or total waits
-
SET NOCOUNT ON
declare @now datetime,
@totalwait numeric(20,1),
@totalsignalwait numeric(20,1),
@totalresourcewait numeric(20,1),
@endtime datetime,@begintime datetime,
@hr int,
@min int,
@sec int
if not exists (select 1
from sysobjects
where id = object_id ( N'[dbo].[waitstats]') and
OBJECTPROPERTY(id, N'IsUserTable') = 1)
開始
raiserror('Error [dbo].[waitstats] table does not exist',
16, 1) with nowait
return
結束
if lower(@report_format) not in ('all','detail','simple')
begin
raiserror ('@report_format must be either ''all'',
''detail'', or ''simple''',16,1) with nowait
return
end
if lower(@report_order) not in ('resource','signal','total')
begin
raiserror ('@report_order must be either ''resource'',
''signal'', or ''total''',16,1) with nowait
return
end
if lower(@report_format) = 'simple' and lower(@report_order) <> 'total'
begin
raiserror ('@report_format is simple so order defaults to
''total''',
16,1) with nowait
select @report_order = 'total'
end
選擇
@now=max(now),
@begintime=min(now),
@endtime=max(now)
from [dbo].[waitstats]
where [wait_type] = 'Total'
--- subtract waitfor, sleep, and resource_queue from Total
select @totalwait = sum([wait_time_ms]) + 1, @totalsignalwait =
sum([signal_wait_time_ms]) + 1
from waitstats
where [wait_type] not in (
'CLR_SEMAPHORE',
'LAZYWRITER_SLEEP',
'RESOURCE_QUEUE',
'SLEEP_TASK',
'SLEEP_SYSTEMTASK',
'Total' ,'WAITFOR',
'***total***') and
now = @now
select @totalresourcewait = 1 + @totalwait - @totalsignalwait
-- insert adjusted totals, rank by percentage descending
delete waitstats
where [wait_type] = '***total***' and
now = @now
insert into waitstats
選擇
'***total***',
0,@totalwait,
0,
@totalsignalwait,
@now
select 'start time'=@begintime,'end time'=@endtime,
'duration (hh:mm:ss:ms)'=convert(varchar(50),@endtime-
@begintime,14),
'report format'=@report_format, 'report order'=@report_order
if lower(@report_format) in ('all','detail')
開始
----- format=detail, column order is resource, signal, total. 整理
resource desc
if lower(@report_order) = 'resource'
select [wait_type],[waiting_tasks_count],
'Resource wt (T1-T0)'=[wait_time_ms]-[signal_wait_time_ms],
'res_wt_%'=cast (100*([wait_time_ms] -
[signal_wait_time_ms]) /@totalresourcewait as
numeric(20,1)),
'Signal wt (T2-T1)'=[signal_wait_time_ms],
'sig_wt_%'=cast (100*[signal_wait_time_ms]/@totalsignalwait as
numeric(20,1)),
'Total wt (T2-T0)'=[wait_time_ms],
'wt_%'=cast (100*[wait_time_ms]/@totalwait as numeric(20,1))
from waitstats
where [wait_type] not in (
'CLR_SEMAPHORE',
'LAZYWRITER_SLEEP',
'RESOURCE_QUEUE',
'SLEEP_TASK',
'SLEEP_SYSTEMTASK',
'Total',
'WAITFOR') and
now = @now
order by 'res_wt_%' desc
----- format=detail, column order signal, resource, total. order by signal
遞減
if lower(@report_order) = 'signal'
select [wait_type],
[waiting_tasks_count],
'Signal wt (T2-T1)'=[signal_wait_time_ms],
'sig_wt_%'=cast (100*[signal_wait_time_ms]/@totalsignalwait
as numeric(20,1)),
'Resource wt (T1-T0)'=[wait_time_ms]-[signal_wait_time_ms],
'res_wt_%'=cast (100*([wait_time_ms] -
[signal_wait_time_ms]) /@totalresourcewait as
numeric(20,1)),
'Total wt (T2-T0)'=[wait_time_ms],
'wt_%'=cast (100*[wait_time_ms]/@totalwait as
numeric(20,1))
from waitstats
where [wait_type] not in (
'CLR_SEMAPHORE',
'LAZYWRITER_SLEEP',
'RESOURCE_QUEUE',
'SLEEP_TASK',
'SLEEP_SYSTEMTASK',
'Total',
'WAITFOR') and
now = @now
order by 'sig_wt_%' desc
----- format=detail, column order total, resource, signal. order by total
遞減
if lower(@report_order) = 'total'
select
[wait_type],
[waiting_tasks_count],
'Total wt (T2-T0)'=[wait_time_ms],
'wt_%'=cast (100*[wait_time_ms]/@totalwait as numeric(20,1)),
'Resource wt (T1-T0)'=[wait_time_ms]-[signal_wait_time_ms],
'res_wt_%'=cast (100*([wait_time_ms] -
[signal_wait_time_ms]) /@totalresourcewait as numeric(20,1)),
'Signal wt (T2-T1)'=[signal_wait_time_ms],
'sig_wt_%'=cast (100*[signal_wait_time_ms]/@totalsignalwait as
numeric(20,1))
from waitstats
where [wait_type] not in (
'CLR_SEMAPHORE',
'LAZYWRITER_SLEEP',
'RESOURCE_QUEUE',
'SLEEP_TASK',
'SLEEP_SYSTEMTASK',
'Total',
'WAITFOR') and
now = @now
order by 'wt_%' desc
結束
其他
---- simple format, total waits only
select
[wait_type],
[wait_time_ms],
percentage=cast (100*[wait_time_ms]/@totalwait as numeric(20,1))
from waitstats
where [wait_type] not in (
'CLR_SEMAPHORE',
'LAZYWRITER_SLEEP',
'RESOURCE_QUEUE',
'SLEEP_TASK',
'SLEEP_SYSTEMTASK',
'Total',
'WAITFOR') and
now = @now
order by percentage desc
---- compute cpu resource waits
選擇
'total waits'=[wait_time_ms],
'total signal=CPU waits'=[signal_wait_time_ms],
'CPU resource waits % = signal waits / total waits'=
cast (100*[signal_wait_time_ms]/[wait_time_ms] as
numeric(20,1)),
now
from [dbo].[waitstats]
where [wait_type] = '***total***'
order by now
去
declare @now datetime
select @now = getdate()
select getdate()