第5组 Process patterns for requirement consistency analysis 读后感

胡俊驰 2023-05-29 16:50:10

导读

这篇读后感是关于PADMALATA V NISTALA, KESAV V NORI, SWAMINATHAN NATARAJAN等人于2016年发表的Process Patterns for Requirement Consistency Analysis这篇论文,论文主要从引言、相关工作、过程模式、案例研究以及结论与未来工作等几个方面入手,大致内容如下:

  • 引言:介绍了需求一致性分析的重要性和挑战,以及本文的目的和贡献。
  • 相关工作:回顾了需求一致性分析的定义、分类、方法和工具,以及它们的优缺点。
  • 过程模式:定义了过程模式的概念和结构,并提出了两种用于需求一致性分析的过程模式:需求覆盖分析需求追踪分析
  • 案例研究:展示了如何在两个不同类型的项目中应用过程模式来进行需求一致性分析,并评估了过程模式的有效性和适用性。
  • 结论与未来工作:总结了本文的主要发现和贡献,并提出了一些未来需要进一步研究和改进的方向。

我会从论文简介、具体实现、有效性评估以及总结四个方面讲解我对这篇论文的理解。

论文简介

在需求空间中,模式在捕获需求知识以供重用并帮助识别需求方面变得越来越重要。需求规格说明的质量对于有效理解和实施需求至关重要。

论文介绍了一组过程模式,这些模式使用组合可追溯性的概念来分析需求规范或用户故事的制定情况,并识别其包含元素之间的不一致之处。

论文提出了两种已成功应用并发现对执行需求一致性分析和检测需求不一致很有用的模式:需求覆盖率分析需求可追溯性分析。这些模式可以在需求阶段应用于项目,以审查和分析规定的需求。本文描述了这些模式,讨论了它的实施和项目案例研究的结果。

研究目的

需求分析侧重于评估记录需求的质量和识别需求中的错误的策略或技术。需求规范构成了主要利益相关者之间讨论、项目估算、开发规划和执行的基础。需求规格说明的质量对于有效理解和实施需求至关重要。

工业系统的统计数据显示,由于30-40%的需求缺陷的比例很高,导致返工和成本很高。 此外,与安全、性能目标等质量方面相关的要求也经常被遗漏。随后,在设计和开发阶段寻求对需求的许多澄清,导致在获得澄清、返工工作和里程碑延误方面损失了生产性开发时间

在本文中提出了两种模式,可以帮助有效地进行需求分析并检测需求中的错误或不一致。

过程模式

  1. 需求覆盖分析

    此模式适用于项目的需求阶段,用于审查客户提供的规定需求的活动。当团队必须审查需求、要求澄清并根据需求理解制定项目估算时,它特别有用。

    需求覆盖分析模式解决了与隐式非功能性需求(NFR) 或一般问题分析维度相关的需求缺失问题,并通过识别额外需求来帮助加强需求。以确保对这些维度的覆盖

  2. 需求可追溯性分析

    此模式适用于需求阶段的项目,用于审查和分析客户提供的规定需求的活动。当团队必须验证需求以确保跨多个需求工件的规范的一致性,并验证规范中是否有足够的细节以进行下一阶段时,它特别有用。

    需求可追溯性模式解决了项目中可追溯性实施不充分的问题,有助于创建具有向后和前向可追溯性的精心制定的需求可追溯性矩阵

具体实现

需求覆盖分析

传统需求分析中的问题:

  1. 隐式的或者非功能性需求,例如安全性、兼容性等,此类问题在验收测试甚至生产期间,很晚出现在生命周期中,导致生产系统的计划延迟和中断
  2. 当一些重要的逻辑和规则并未包含在需求规范中时,但是在设计和开发阶段经常寻求澄清,客户主题专家可能无法随时澄清,从而导致时间的损失和延误。
解决方案:

多维分析是需求覆盖分析的原理。该模式使用行业标准产品质量维度和标准推理维度提供全面的维度覆盖。从非功能性需求(NFR)、推理领域等多个维度进行需求覆盖率的分析。

分析步骤:

首先分析NFR维度的覆盖范围,ISO/IEC 25010软件产品质量模型中有一套全面的NFR定义。本模式以此为NFR覆盖率分析的参考模型。根据ISO模型中定义的质量特性(QC)来分析需求覆盖范围。

通过判断需求是否与QC/Sub QC的每个NFR分类相关。如果缺少QC的要求,则在覆盖跟踪器RCT)中标记覆盖缺口

NFR维度分类如下图:

img

质量特性主要分为:

安全性性能可靠性可用性兼容性可移植性可维护性

每个质量特性都涵盖相应的子特性:

例如性能方面考虑时间和资源利用率

可用性方面考虑用户界面美观和易学习性

可靠性方面考虑可恢复性和容错

其次分析推理维度的覆盖率,使用5W1H(who when where what why how)分析推理方法来分析需求,如果可以针对该需求跟踪5W1H维度的需求视角,则判断它的覆盖范围在推理维度上是完整的。

推理维度如图:

img

5W1H指:

Who When Where What Why How

在需求视角中分别对应:

  • WHAT:唯一引出需求
  • WHY:目标一致性,以验证为什么需求是必要的
  • WHERE:需求的适用领域
  • HOW:流程与规范,关于如何实现需求的详细信息
  • WHEN:在生产系统中执行需求的时间细节
  • WHO:可以访问需求的负责角色

接着分析领域特定维度的覆盖范围,当项目有特定领域或者法规遵从性标准时,必须针对这些维度和标准执行覆盖分析。将发现的差距作为不一致记录在RCT中。

最后合并需求覆盖不一致。RCT记录了关于三个维度的需求覆盖范围的差距。需要和主题专家讨论不一致之处,并确保解决所有已识别的不一致之处。

分析举例:

img

ID为R36的需求缺少安全要求——未指定报表的访问角色信息;来源US1的第三行未提供地理的具体规则,解决方案是将需求更新为美国和澳大利亚是适用的地区;R37的需求未规定与强制性数据保护法案合规性相关的要求

需求溯源分析

此模式适用于需求阶段的项目,用于审查和分析客户提供的规定需求的活动。当团队必须验证需求以确保跨多个需求工件的规范的一致性,并验证规范中是否有足够的细节以进行下一阶段时,它特别有用。

需求溯源分析模式的产生源于以下问题的出现:

  • 需求工程师不清楚跨多个需求工件陈述的需求是否一致,以及需求规格说明中的差距是什么,无法继续进行设计阶段。
  • 无法清楚地看到需求地可追溯路径:需求地来源和相应地实现规范,使得难以识别更改需求的后果和识别依赖关系,在后期阶段寻求许多澄清,导致延迟和生成开发时间的损失。
使用场景
  • 需要在短时间内审查需求并提供估计
  • 需要延迟识别需求间的差距
  • 项目团队缺乏经验来分析各种需求工件之间的不一致性,并在需求研讨会和审查期间提出相关问题,缺乏结构化的方法用于分析需求
  • 在需求分析阶段之后,难以联系或得到客户主题专家的帮助
使用步骤
  1. 识别项目需求的可追溯元素

在项目中,需求信息通常被指定为跨工件的多层信息,例如项目章程,用户需求规范和软件需求规范。每个工件都包含一组需求元素。通用需求组合可以被视为包含四个关键层的元素:业务层,流程层,需求层,规范层。可追溯性元素可被识别为此四层,并创建需求可追溯性矩阵。

  1. 将需求填充到可追溯性矩阵(RTM)中,如下图

img

  1. 建立需求的向后可追溯性

对于向后可追溯性,每个需求都需要在部分或完全实现业务目标方面为项目章程做出贡献。为了向后追溯,需要分析和建立每个需求到一个或多个项目目标和业务流程的可追溯性。主要是此分析根据为什么需要它来验证需求

  1. 建立需求的前向可追溯性

对于前向可追溯性,规范元素需要在流程步骤,用户界面,计算逻辑等方面描述需求的系统实施指南,主要验证每个要求都是可实现的。

  1. 整合需求可追溯性数据

需求可追溯性矩阵整合了从需求起源到实施的完整需求追踪。矩阵的每一行对应一个要求,列分别从左到右依次是需求源、需求ID、业务层的需求元素、流程层的需求元素、规定的需求、需求元素规范层、跟踪标志、需求的不一致计数。

其中单元格中的差距表示需求中的差距,需要作为不一致提出并采取行动。

img

优点

该模式提供了一种结构化的方式来创建具有向后和向前可追溯性的格式良好的需求可追溯性矩阵。它有助于验证需求与业务目标的一致性,并检测需求规范中可能未检测到的许多不一致的地方。

手动维护大量需求和跨多个项目的表可能会变得困难,因此可以将此模式集成到整体需求流程和工具平台中,并和需求覆盖分析模式相辅相成。

有效性评估

当这两种模式应用于一个企业数据仓库报告系统时,该系统具有一组具有规定要求的用户故事。

从给定的集合中,六个用户故事被用于试点,涵盖35个需求。出于说明目的,考虑了用户故事US1"收入耗尽报告”。

该报告应该可供一组经理使用,以查看服务合同业务即将到来的和过去的收入用完的收入。

该用户故事对报表的过滤条件提出了要求:显示发票的金额;显示收入、计费天数等信息;从源数据库中提取数据,并将1000条记录导出到 Excel 的能力。

需求覆盖分析

在分析推理维度的需求时,发现需求中没有涵盖角色维度who)、时间(when)和规范部分(how)。可以追踪到其他推理维度。因此,在“”需要运行报告、“何时”需要运行报告以及“如何”实施方面存在需求差距。

同样,在对需求进行NFR覆盖分析时,发现遗漏了一些关键的NFR:已经讨论了对角色的**安全要求的差距,**并且没有说明报告的性能目标。这些差距条目被记录到Requirement Coverage Tracker( RCT )中。对于每一行,标记新的要求标志或计数器随着每一行的间隙数递增。

img

  • NFR维度上缺乏安全要求——未指定报告的访问角色信息,属于一个新需求,解决方案是限定报告的访问控制,即只能由财务经理访问。
  • NFR维度上缺乏对性能的限定,即未提供导出1000条记录的目标相应时间,这属于一个需求缺口。
  • 推理维度上没有提供地理where)的具体规则,这也属于一个需求缺口。
  • 领域维度中未规定与强制性数据保护法(DPA)合规性相关的要求。

在特定情况下,应用该模式的结果是需求数量从35个增加到63个,**覆盖率提高80%**,这表明基线需求得到了很好的扩展。

需求追溯分析

描述了合并到RTM中的项目需求元素的可追溯性的部分视图。红色标记的单元格表示需求不一致,其原因可能是缺乏业务层一致性或者缺乏字段映射逻辑规则导致的不规范。

img

  • 需求1的规范层中发票金额缺少来自源数据库的字段映射
  • 需求4的规范层中未指定货币转换的计算逻辑

在35个需求中,只有7个需求可以向前追溯,28个需求在领域或逻辑规范上存在差距。RTM会根据每个需求的需求差距数量进行更新。

评估

img

应用模式所需的工作量为65小时。表5中计算出的修复不一致的总工作量为420小时。A=65小时,B=420小时。因此,节省的开发工作量=(B–A)/A=546%,表明由于应用模式而节省了大量工作量。

总结

需求一致性分析是软件开发中非常重要的一环,它的目的是确保软件系统各个阶段的需求与设计的一致性,从而最终构建出符合用户需求的系统。

在进行需求一致性分析时,我们可以遵循一定的过程模式,以保证分析的准确性和完整性。

首先,需求一致性分析的过程模式必须具备系统性全面性。在进行分析时,我们不能只看某个需求或某个模块,而应该从整个系统的角度出发,全面地考虑每个需求的实现和相互之间的关系。只有这样才能保证系统的稳定性和可靠性

其次,需求一致性分析的过程模式需要具备灵活性。在软件开发中,需求随时都可能发生变化,因此我们需要针对不同的需求变化,灵活地调整分析过程模式。这样才能保证分析结果的准确性实用性

最后,需求一致性分析的过程模式需要具备透明性。在分析过程中,我们需要与客户和开发团队沟通交流,及时反馈分析结果和意见。这样既可以避免分析结果出现偏差,还可以加强开发团队与客户之间的信任和合作。

总之,需求一致性分析的过程模式是软件开发中不可或缺的一环,只有在严格遵循系统性全面性灵活性透明性等原则的基础上,才能保证分析结果的准确性实用性,从而构建出高质量的软件系统。

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kunkun711 2023-05-29
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要我说真行

金色的镇静剂 2023-05-29
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精彩,打赏了

胡俊驰 2023-05-29
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@金色的镇静剂 红豆泥阿里嘎多,在需求分析时采用需求覆盖分析和需求追踪分析一定会让你有所收获的
金色的镇静剂 2023-05-29
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@胡俊驰 真得分析,猛猛分析!
Contents Overview 1 Lesson 1: Concepts – Locks and Lock Manager 3 Lesson 2: Concepts – Batch and Transaction 31 Lesson 3: Concepts – Locks and Applications 51 Lesson 4: Information Collection and Analysis 63 Lesson 5: Concepts – Formulating and Implementing Resolution 81 Module 4: Troubleshooting Locking and Blocking Overview At the end of this module, you will be able to:  Discuss how lock manager uses lock mode, lock resources, and lock compatibility to achieve transaction isolation.  Describe the various transaction types and how transactions differ from batches.  Describe how to troubleshoot blocking and locking issues.  Analyze the output of blocking scripts and Microsoft® SQL Server™ Profiler to troubleshoot locking and blocking issues.  Formulate hypothesis to resolve locking and blocking issues. Lesson 1: Concepts – Locks and Lock Manager This lesson outlines some of the common causes that contribute to the perception of a slow server. What You Will Learn After completing this lesson, you will be able to:  Describe locking architecture used by SQL Server.  Identify the various lock modes used by SQL Server.  Discuss lock compatibility and concurrent access.  Identify different types of lock resources.  Discuss dynamic locking and lock escalation.  Differentiate locks, latches, and other SQL Server internal “locking” mechanism such as spinlocks and other synchronization objects. Recommended Reading  Chapter 14 “Locking”, Inside SQL Server 2000 by Kalen Delaney  SOX000821700049 – SQL 7.0 How to interpret lock resource Ids  SOX000925700237 – TITLE: Lock escalation in SQL 7.0  SOX001109700040 – INF: Queries with PREFETCH in the plan hold lock until the end of transaction Locking Concepts Delivery Tip Prior to delivering this material, test the class to see if they fully understand the different isolation levels. If the class is not confident in their understanding, review appendix A04_Locking and its accompanying PowerPoint® file. Transactions in SQL Server provide the ACID properties: Atomicity A transaction either commits or aborts. If a transaction commits, all of its effects remain. If it aborts, all of its effects are undone. It is an “all or nothing” operation. Consistency An application should maintain the consistency of a database. For example, if you defer constraint checking, it is your responsibility to ensure that the database is consistent. Isolation Concurrent transactions are isolated from the updates of other incomplete transactions. These updates do not constitute a consistent state. This property is often called serializability. For example, a second transaction traversing the doubly linked list mentioned above would see the list before or after the insert, but it will see only complete changes. Durability After a transaction commits, its effects will persist even if there are system failures. Consistency and isolation are the most important in describing SQL Server’s locking model. It is up to the application to define what consistency means, and isolation in some form is needed to achieve consistent results. SQL Server uses locking to achieve isolation. Definition of Dependency: A set of transactions can run concurrently if their outputs are disjoint from the union of one another’s input and output sets. For example, if T1 writes some object that is in T2’s input or output set, there is a dependency between T1 and T2. Bad Dependencies These include lost updates, dirty reads, non-repeatable reads, and phantoms. ANSI SQL Isolation Levels An isolation level determines the degree to which data is isolated for use by one process and guarded against interference from other processes. Prior to SQL Server 7.0, REPEATABLE READ and SERIALIZABLE isolation levels were synonymous. There was no way to prevent non-repeatable reads while not preventing phantoms. By default, SQL Server 2000 operates at an isolation level of READ COMMITTED. To make use of either more or less strict isolation levels in applications, locking can be customized for an entire session by setting the isolation level of the session with the SET TRANSACTION ISOLATION LEVEL statement. To determine the transaction isolation level currently set, use the DBCC USEROPTIONS statement, for example: USE pubs GO SET TRANSACTION ISOLATION LEVEL REPEATABLE READ GO DBCC USEROPTIONS GO Multigranular Locking Multigranular Locking In our example, if one transaction (T1) holds an exclusive lock at the table level, and another transaction (T2) holds an exclusive lock at the row level, each of the transactions believe they have exclusive access to the resource. In this scenario, since T1 believes it locks the entire table, it might inadvertently make changes to the same row that T2 thought it has locked exclusively. In a multigranular locking environment, there must be a way to effectively overcome this scenario. Intent lock is the answer to this problem. Intent Lock Intent Lock is the term used to mean placing a marker in a higher-level lock queue. The type of intent lock can also be called the multigranular lock mode. An intent lock indicates that SQL Server wants to acquire a shared (S) lock or exclusive (X) lock on some of the resources lower down in the hierarchy. For example, a shared intent lock placed at the table level means that a transaction intends on placing shared (S) locks on pages or rows within that table. Setting an intent lock at the table level prevents another transaction from subsequently acquiring an exclusive (X) lock on the table containing that page. Intent locks improve performance because SQL Server examines intent locks only at the table level to determine whether a transaction can safely acquire a lock on that table. This removes the requirement to examine every row or page lock on the table to determine whether a transaction can lock the entire table. Lock Mode The code shown in the slide represents how the lock mode is stored internally. You can see these codes by querying the master.dbo.spt_values table: SELECT * FROM master.dbo.spt_values WHERE type = N'L' However, the req_mode column of master.dbo.syslockinfo has lock mode code that is one less than the code values shown here. For example, value of req_mode = 3 represents the Shared lock mode rather than the Schema Modification lock mode. Lock Compatibility These locks can apply at any coarser level of granularity. If a row is locked, SQL Server will apply intent locks at both the page and the table level. If a page is locked, SQL Server will apply an intent lock at the table level. SIX locks imply that we have shared access to a resource and we have also placed X locks at a lower level in the hierarchy. SQL Server never asks for SIX locks directly, they are always the result of a conversion. For example, suppose a transaction scanned a page using an S lock and then subsequently decided to perform a row level update. The row would obtain an X lock, but now the page would require an IX lock. The resultant mode on the page would be SIX. Another type of table lock is a schema stability lock (Sch-S) and is compatible with all table locks except the schema modification lock (Sch-M). The schema modification lock (Sch-M) is incompatible with all table locks. Locking Resources Delivery Tip Note the differences between Key and Key Range locks. Key Range locks will be covered in a couple of slides. SQL Server can lock these resources: Item Description DB A database. File A database file Index An entire index of a table. Table An entire table, including all data and indexes. Extent A contiguous group of data pages or index pages. Page An 8-KB data page or index page. Key Row lock within an index. Key-range A key-range. Used to lock ranges between records in a table to prevent phantom insertions or deletions into a set of records. Ensures serializable transactions. RID A Row Identifier. Used to individually lock a single row within a table. Application A lock resource defined by an application. The lock manager knows nothing about the resource format. It simply compares the 'strings' representing the lock resources to determine whether it has found a match. If a match is found, it knows that resource is already locked. Some of the resources have “sub-resources.” The followings are sub-resources displayed by the sp_lock output: Database Lock Sub-Resources: Full Database Lock (default) [BULK-OP-DB] – Bulk Operation Lock for Database [BULK-OP-LOG] – Bulk Operation Lock for Log Table Lock Sub-Resources: Full Table Lock (default) [UPD-STATS] – Update statistics Lock [COMPILE] – Compile Lock Index Lock sub-Resources: Full Index Lock (default) [INDEX_ID] – Index ID Lock [INDEX_NAME] – Index Name Lock [BULK_ALLOC] – Bulk Allocation Lock [DEFRAG] – Defragmentation Lock For more information, see also… SOX000821700049 SQL 7.0 How to interpret lock resource Ids Lock Resource Block The resource type has the following resource block format: Resource Type (Code) Content DB (2) Data 1: sub-resource; Data 2: 0; Data 3: 0 File (3) Data 1: File ID; Data 2: 0; Data 3: 0 Index (4) Data 1: Object ID; Data 2: sub-resource; Data 3: Index ID Table (5) Data 1: Object ID; Data 2: sub-resource; Data 3: 0. Page (6) Data 1: Page Number; Data 3: 0. Key (7) Data 1: Object ID; Data 2: Index ID; Data 3: Hashed Key Extent (8) Data 1: Extent ID; Data 3: 0. RID (9) Data 1: RID; Data 3: 0. Application (10) Data 1: Application resource name The rsc_bin column of master..syslockinfo contains the resource block in hexadecimal format. For an example of how to decode value from this column using the information above, let us assume we have the following value: 0x000705001F83D775010002014F0BEC4E With byte swapping within each field, this can be decoded as: Byte 0: Flag – 0x00 Byte 1: Resource Type – 0x07 (Key) Byte 2-3: DBID – 0x0005 Byte 4-7: ObjectID – 0x 75D7831F (1977058079) Byte 8-9: IndexID – 0x0001 Byte 10-16: Hash Key value – 0x 02014F0BEC4E For more information about how to decode this value, see also… Inside SQL Server 2000, pages 803 and 806. Key Range Locking Key Range Locking To support SERIALIZABLE transaction semantics, SQL Server needs to lock sets of rows specified by a predicate, such as WHERE salary BETWEEN 30000 AND 50000 SQL Server needs to lock data that does not exist! If no rows satisfy the WHERE condition the first time the range is scanned, no rows should be returned on any subsequent scans. Key range locks are similar to row locks on index keys (whether clustered or not). The locks are placed on individual keys rather than at the node level. The hash value consists of all the key components and the locator. So, for a nonclustered index over a heap, where columns c1 and c2 where indexed, the hash would contain contributions from c1, c2 and the RID. A key range lock applied to a particular key means that all keys between the value locked and the next value would be locked for all data modification. Key range locks can lock a slightly larger range than that implied by the WHERE clause. Suppose the following select was executed in a transaction with isolation level SERIALIZABLE: SELECT * FROM members WHERE first_name between ‘Al’ and ‘Carl’ If 'Al', 'Bob', and 'Dave' are index keys in the table, the first two of these would acquire key range locks. Although this would prevent anyone from inserting either 'Alex' or 'Ben', it would also prevent someone from inserting 'Dan', which is not within the range of the WHERE clause. Prior to SQL Server 7.0, page locking was used to prevent phantoms by locking the entire set of pages on which the phantom would exist. This can be too conservative. Key Range locking lets SQL Server lock only a much more restrictive area of the table. Impact Key-range locking ensures that these scenarios are SERIALIZABLE:  Range scan query  Singleton fetch of nonexistent row  Delete operation  Insert operation However, the following conditions must be satisfied before key-range locking can occur:  The transaction-isolation level must be set to SERIALIZABLE.  The operation performed on the data must use an index range access. Range locking is activated only when query processing (such as the optimizer) chooses an index path to access the data. Key Range Lock Mode Again, the req_mode column of master.dbo.syslockinfo has lock mode code that is one less than the code values shown here. Dynamic Locking When modifying individual rows, SQL Server typically would take row locks to maximize concurrency (for example, OLTP, order-entry application). When scanning larger volumes of data, it would be more appropriate to take page or table locks to minimize the cost of acquiring locks (for example, DSS, data warehouse, reporting). Locking Decision The decision about which unit to lock is made dynamically, taking many factors into account, including other activity on the system. For example, if there are multiple transactions currently accessing a table, SQL Server will tend to favor row locking more so than it otherwise would. It may mean the difference between scanning the table now and paying a bit more in locking cost, or having to wait to acquire a more coarse lock. A preliminary locking decision is made during query optimization, but that decision can be adjusted when the query is actually executed. Lock Escalation When the lock count for the transaction exceeds and is a multiple of ESCALATION_THRESHOLD (1250), the Lock Manager attempts to escalate. For example, when a transaction acquired 1250 locks, lock manager will try to escalate. The number of locks held may continue to increase after the escalation attempt (for example, because new tables are accessed, or the previous lock escalation attempts failed due to incompatible locks held by another spid). If the lock count for this transaction reaches 2500 (1250 * 2), Lock Manager will attempt escalation again. The Lock Manager looks at the lock memory it is using and if it is more than 40 percent of SQL Server’s allocated buffer pool memory, it tries to find a scan (SDES) where no escalation has already been performed. It then repeats the search operation until all scans have been escalated or until the memory used drops under the MEMORY_LOAD_ESCALATION_THRESHOLD (40%) value. If lock escalation is not possible or fails to significantly reduce lock memory footprint, SQL Server can continue to acquire locks until the total lock memory reaches 60 percent of the buffer pool (MAX_LOCK_RESOURCE_MEMORY_PERCENTAGE=60). Lock escalation may be also done when a single scan (SDES) holds more than LOCK_ESCALATION_THRESHOLD (765) locks. There is no lock escalation on temporary tables or system tables. Trace Flag 1211 disables lock escalation. Important Do not relay this to the customer without careful consideration. Lock escalation is a necessary feature, not something to be avoided completely. Trace flags are global and disabling lock escalation could lead to out of memory situations, extremely poor performing queries, or other problems. Lock escalation tracing can be seen using the Profiler or with the general locking trace flag, -T1200. However, Trace Flag 1200 shows all lock activity so it should not be usable on a production system. For more information, see also… SOX000925700237 “TITLE: SQL 7.0 Lock escalation in SQL 7.0” Lock Timeout Application Lock Timeout An application can set lock timeout for a session with the SET option: SET LOCK_TIMEOUT N where N is a number of milliseconds. A value of -1 means that there will be no timeout, which is equivalent to the version 6.5 behavior. A value of 0 means that there will be no waiting; if a process finds a resource locked, it will generate error message 1222 and continue with the next statement. The current value of LOCK_TIMEOUT is stored in the global variable @@lock_timeout. Note After a lock timeout any transaction containing the statement, is rolled back or canceled by SQL Server 2000 (bug#352640 was filed). This behavior is different from that of SQL Server 7.0. With SQL Server 7.0, the application must have an error handler that can trap error 1222 and if an application does not trap the error, it can proceed unaware that an individual statement within a transaction has been canceled, and errors can occur because statements later in the transaction may depend on the statement that was never executed. Bug#352640 is fixed in hotfix build 8.00.266 whereby a lock timeout will only Internal Lock Timeout At time, internal operations within SQL Server will attempt to acquire locks via lock manager. Typically, these lock requests are issued with “no waiting.” For example, the ghost record processing might try to clean up rows on a particular page, and before it can do that, it needs to lock the page. Thus, the ghost record manager will request a page lock with no wait so that if it cannot lock the page, it will just move on to other pages; it can always come back to this page later. If you look at SQL Profiler Lock: Timeout events, internal lock timeout typically have a duration value of zero. Lock Duration Lock Mode and Transaction Isolation Level For REPEATABLE READ transaction isolation level, update locks are held until data is read and processed, unless promoted to exclusive locks. "Data is processed" means that we have decided whether the row in question matched the search criteria; if not then the update lock is released, otherwise, we get an exclusive lock and make the modification. Consider the following query: use northwind go dbcc traceon(3604, 1200, 1211) -- turn on lock tracing -- and disable escalation go set transaction isolation level repeatable read begin tran update dbo.[order details] set discount = convert (real, discount) where discount = 0.0 exec sp_lock Update locks are promoted to exclusive locks when there is a match; otherwise, the update lock is released. The sp_lock output verifies that the SPID does not hold any update locks or shared locks at the end of the query. Lock escalation is turned off so that exclusive table lock is not held at the end. Warning Do not use trace flag 1200 in a production environment because it produces a lot of output and slows down the server. Trace flag 1211 should not be used unless you have done extensive study to make sure it helps with performance. These trace flags are used here for illustration and learning purposes only. Lock Ownership Most of the locking discussion in this lesson relates to locks owned by “transactions.” In addition to transaction, cursor and session can be owners of locks and they both affect how long locks are held. For every row that is fetched, when SCROLL_LOCKS option is used, regardless of the state of a transaction, a cursor lock is held until the next row is fetched or when the cursor is closed. Locks owned by session are outside the scope of a transaction. The duration of these locks are bounded by the connection and the process will continue to hold these locks until the process disconnects. A typical lock owned by session is the database (DB) lock. Locking – Read Committed Scan Under read committed isolation level, when database pages are scanned, shared locks are held when the page is read and processed. The shared locks are released “behind” the scan and allow other transactions to update rows. It is important to note that the shared lock currently acquired will not be released until shared lock for the next page is successfully acquired (this is commonly know as “crabbing”). If the same pages are scanned again, rows may be modified or deleted by other transactions. Locking – Repeatable Read Scan Under repeatable read isolation level, when database pages are scanned, shared locks are held when the page is read and processed. SQL Server continues to hold these shared locks, thus preventing other transactions to update rows. If the same pages are scanned again, previously scanned rows will not change but new rows may be added by other transactions. Locking – Serializable Read Scan Under serializable read isolation level, when database pages are scanned, shared locks are held not only on rows but also on scanned key range. SQL Server continues to hold these shared locks until the end of transaction. Because key range locks are held, not only will this prevent other transactions from modifying the rows, no new rows can be inserted. Prefetch and Isolation Level Prefetch and Locking Behavior The prefetch feature is available for use with SQL Server 7.0 and SQL Server 2000. When searching for data using a nonclustered index, the index is searched for a particular value. When that value is found, the index points to the disk address. The traditional approach would be to immediately issue an I/O for that row, given the disk address. The result is one synchronous I/O per row and, at most, one disk at a time working to evaluate the query. This does not take advantage of striped disk sets. The prefetch feature takes a different approach. It continues looking for more record pointers in the nonclustered index. When it has collected a number of them, it provides the storage engine with prefetch hints. These hints tell the storage engine that the query processor will need these particular records soon. The storage engine can now issue several I/Os simultaneously, taking advantage of striped disk sets to execute multiple operations simultaneously. For example, if the engine is scanning a nonclustered index to determine which rows qualify but will eventually need to visit the data page as well to access columns that are not in the index, it may decide to submit asynchronous page read requests for a group of qualifying rows. The prefetch data pages are then revisited later to avoid waiting for each individual page read to complete in a serial fashion. This data access path requires that a lock be held between the prefetch request and the row lookup to stabilize the row on the page so it is not to be moved by a page split or clustered key update. For our example, the isolation level of the query is escalated to REPEATABLE READ, overriding the transaction isolation level. With SQL Server 7.0 and SQL Server 2000, portions of a transaction can execute at a different transaction isolation level than the entire transaction itself. This is implemented as lock classes. Lock classes are used to control lock lifetime when portions of a transaction need to execute at a stricter isolation level than the underlying transaction. Unfortunately, in SQL Server 7.0 and SQL Server 2000, the lock class is created at the topmost operator of the query and hence released only at the end of the query. Currently there is no support to release the lock (lock class) after the row has been discarded or fetched by the filter or join operator. This is because isolation level can be set at the query level via a lock class, but no lower. Because of this, locks acquired during the query will not be released until the query completes. If prefetch is occurring you may see a single SPID that holds hundreds of Shared KEY or PAG locks even though the connection’s isolation level is READ COMMITTED. Isolation level can be determined from DBCC PSS output. For details about this behavior see “SOX001109700040 INF: Queries with PREFETCH in the plan hold lock until the end of transaction”. Other Locking Mechanism Lock manager does not manage latches and spinlocks. Latches Latches are internal mechanisms used to protect pages while doing operations such as placing a row physically on a page, compressing space on a page, or retrieving rows from a page. Latches can roughly be divided into I/O latches and non-I/O latches. If you see a high number of non-I/O related latches, SQL Server is usually doing a large number of hash or sort operations in tempdb. You can monitor latch activities via DBCC SQLPERF(‘WAITSTATS’) command. Spinlock A spinlock is an internal data structure that is used to protect vital information that is shared within SQL Server. On a multi-processor machine, when SQL Server tries to access a particular resource protected by a spinlock, it must first acquire the spinlock. If it fails, it executes a loop that will check to see if the lock is available and if not, decrements a counter. If the counter reaches zero, it yields the processor to another thread and goes into a “sleep” (wait) state for a pre-determined amount of time. When it wakes, hopefully, the lock is free and available. If not, the loop starts again and it is terminated only when the lock is acquired. The reason for implementing a spinlock is that it is probably less costly to “spin” for a short time rather than yielding the processor. Yielding the processor will force an expensive context switch where:  The old thread’s state must be saved  The new thread’s state must be reloaded  The data stored in the L1 and L2 cache are useless to the processor On a single-processor computer, the loop is not useful because no other thread can be running and thus, no one can release the spinlock for the currently executing thread to acquire. In this situation, the thread yields the processor immediately. Lesson 2: Concepts – Batch and Transaction This lesson outlines some of the common causes that contribute to the perception of a slow server. What You Will Learn After completing this lesson, you will be able to:  Review batch processing and error checking.  Review explicit, implicit and autocommit transactions and transaction nesting level.  Discuss how commit and rollback transaction done in stored procedure and trigger affects transaction nesting level.  Discuss various transaction isolation level and their impact on locking.  Discuss the difference between aborting a statement, a transaction, and a batch.  Describe how @@error, @@transcount, and @@rowcount can be used for error checking and handling. Recommended Reading  Charter 12 “Transactions and Triggers”, Inside SQL Server 2000 by Kalen Delaney Batch Definition SQL Profiler Statements and Batches To help further your understanding of what is a batch and what is a statement, you can use SQL Profiler to study the definition of batch and statement.  Try This: Using SQL Profiler to Analyze Batch 1. Log on to a server with Query Analyzer 2. Startup the SQL Profiler against the same server 3. Start a trace using the “StandardSQLProfiler” template 4. Execute the following using Query Analyzer: SELECT @@VERSION SELECT @@SPID The ‘SQL:BatchCompleted’ event is captured by the trace. It shows both the statements as a single batch. 5. Now execute the following using Query Analyzer {call sp_who()} What shows up? The ‘RPC:Completed’ with the sp_who information. RPC is simply another entry point to the SQL Server to call stored procedures with native data types. This allows one to avoid parsing. The ‘RPC:Completed’ event should be considered the same as a batch for the purposes of this discussion. Stop the current trace and start a new trace using the “SQLProfilerTSQL_SPs” template. Issue the same command as outlines in step 5 above. Looking at the output, not only can you see the batch markers but each statement as executed within the batch. Autocommit, Explicit, and Implicit Transaction Autocommit Transaction Mode (Default) Autocommit mode is the default transaction management mode of SQL Server. Every Transact-SQL statement, whether it is a standalone statement or part of a batch, is committed or rolled back when it completes. If a statement completes successfully, it is committed; if it encounters any error, it is rolled back. A SQL Server connection operates in autocommit mode whenever this default mode has not been overridden by either explicit or implicit transactions. Autocommit mode is also the default mode for ADO, OLE DB, ODBC, and DB-Library. A SQL Server connection operates in autocommit mode until a BEGIN TRANSACTION statement starts an explicit transaction, or implicit transaction mode is set on. When the explicit transaction is committed or rolled back, or when implicit transaction mode is turned off, SQL Server returns to autocommit mode. Explicit Transaction Mode An explicit transaction is a transaction that starts with a BEGIN TRANSACTION statement. An explicit transaction can contain one or more statements and must be terminated by either a COMMIT TRANSACTION or a ROLLBACK TRANSACTION statement. Implicit Transaction Mode SQL Server can automatically or, more precisely, implicitly start a transaction for you if a SET IMPLICIT_TRANSACTIONS ON statement is run or if the implicit transaction option is turned on globally by running sp_configure ‘user options’ 2. (Actually, the bit mask 0x2 must be turned on for the user option so you might have to perform an ‘OR’ operation with the existing user option value.) See SQL Server 2000 Books Online on how to turn on implicit transaction under ODBC and OLE DB (acdata.chm::/ac_8_md_06_2g6r.htm). Transaction Nesting Explicit transactions can be nested. Committing inner transactions is ignored by SQL Server other than to decrements @@TRANCOUNT. The transaction is either committed or rolled back based on the action taken at the end of the outermost transaction. If the outer transaction is committed, the inner nested transactions are also committed. If the outer transaction is rolled back, then all inner transactions are also rolled back, regardless of whether the inner transactions were individually committed. Each call to COMMIT TRANSACTION applies to the last executed BEGIN TRANSACTION. If the BEGIN TRANSACTION statements are nested, then a COMMIT statement applies only to the last nested transaction, which is the innermost transaction. Even if a COMMIT TRANSACTION transaction_name statement within a nested transaction refers to the transaction name of the outer transaction, the commit applies only to the innermost transaction. If a ROLLBACK TRANSACTION statement without a transaction_name parameter is executed at any level of a set of nested transaction, it rolls back all the nested transactions, including the outermost transaction. The @@TRANCOUNT function records the current transaction nesting level. Each BEGIN TRANSACTION statement increments @@TRANCOUNT by one. Each COMMIT TRANSACTION statement decrements @@TRANCOUNT by one. A ROLLBACK TRANSACTION statement that does not have a transaction name rolls back all nested transactions and decrements @@TRANCOUNT to 0. A ROLLBACK TRANSACTION that uses the transaction name of the outermost transaction in a set of nested transactions rolls back all the nested transactions and decrements @@TRANCOUNT to 0. When you are unsure if you are already in a transaction, SELECT @@TRANCOUNT to determine whether it is 1 or more. If @@TRANCOUNT is 0 you are not in a transaction. You can also find the transaction nesting level by checking the sysprocess.open_tran column. See SQL Server 2000 Books Online topic “Nesting Transactions” (acdata.chm::/ac_8_md_06_66nq.htm) for more information. Statement, Transaction, and Batch Abort One batch can have many statements and one transaction can have multiple statements, also. One transaction can span multiple batches and one batch can have multiple transactions. Statement Abort Currently executing statement is aborted. This can be a bit confusing when you start talking about statements in a trigger or stored procedure. Let us look closely at the following trigger: CREATE TRIGGER TRG8134 ON TBL8134 AFTER INSERT AS BEGIN SELECT 1/0 SELECT 'Next command in trigger' END To fire the INSERT trigger, the batch could be as simple as ‘INSERT INTO TBL8134 VALUES(1)’. However, the trigger contains two statements that must be executed as part of the batch to satisfy the clients insert request. When the ‘SELECT 1/0’ causes the divide by zero error, a statement abort is issued for the ‘SELECT 1/0’ statement. Batch and Transaction Abort On SQL Server 2000 (and SQL Server 7.0) whenever a non-informational error is encountered in a trigger, the statement abort is promoted to a batch and transactional abort. Thus, in the example the statement abort for ‘select 1/0’ promotion results in an entire batch abort. No further statements in the trigger or batch will be executed and a rollback is issued. On SQL Server 6.5, the statement aborts immediately and results in a transaction abort. However, the rest of the statements within the trigger are executed. This trigger could return ‘Next command in trigger’ as a result set. Once the trigger completes the batch abort promotion takes effect. Conversely, submitting a similar set of statements in a standalone batch can result in different behavior. SELECT 1/0 SELECT 'Next command in batch' Not considering the set option possibilities, a divide by zero error generally results in a statement abort. Since it is not in a trigger, the promotion to a batch abort is avoided and subsequent SELECT statement can execute. The programmer should add an “if @@ERROR” check immediately after the ‘select 1/0’ to T-SQL execution to control the flow correctly. Aborting and Set Options ARITHABORT If SET ARITHABORT is ON, these error conditions cause the query or batch to terminate. If the errors occur in a transaction, the transaction is rolled back. If SET ARITHABORT is OFF and one of these errors occurs, a warning message is displayed, and NULL is assigned to the result of the arithmetic operation. When an INSERT, DELETE, or UPDATE statement encounters an arithmetic error (overflow, divide-by-zero, or a domain error) during expression evaluation when SET ARITHABORT is OFF, SQL Server inserts or updates a NULL value. If the target column is not nullable, the insert or update action fails and the user receives an error. XACT_ABORT When SET XACT_ABORT is ON, if a Transact-SQL statement raises a run-time error, the entire transaction is terminated and rolled back. When OFF, only the Transact-SQL statement that raised the error is rolled back and the transaction continues processing. Compile errors, such as syntax errors, are not affected by SET XACT_ABORT. For example: CREATE TABLE t1 (a int PRIMARY KEY) CREATE TABLE t2 (a int REFERENCES t1(a)) GO INSERT INTO t1 VALUES (1) INSERT INTO t1 VALUES (3) INSERT INTO t1 VALUES (4) INSERT INTO t1 VALUES (6) GO SET XACT_ABORT OFF GO BEGIN TRAN INSERT INTO t2 VALUES (1) INSERT INTO t2 VALUES (2) /* Foreign key error */ INSERT INTO t2 VALUES (3) COMMIT TRAN SELECT 'Continue running batch 1...' GO SET XACT_ABORT ON GO BEGIN TRAN INSERT INTO t2 VALUES (4) INSERT INTO t2 VALUES (5) /* Foreign key error */ INSERT INTO t2 VALUES (6) COMMIT TRAN SELECT 'Continue running batch 2...' GO /* Select shows only keys 1 and 3 added. Key 2 insert failed and was rolled back, but XACT_ABORT was OFF and rest of transaction succeeded. Key 5 insert error with XACT_ABORT ON caused all of the second transaction to roll back. Also note that 'Continue running batch 2...' is not Returned to indicate that the batch is aborted. */ SELECT * FROM t2 GO DROP TABLE t2 DROP TABLE t1 GO Compile and Run-time Errors Compile Errors Compile errors are encountered during syntax checks, security checks, and other general operations to prepare the batch for execution. These errors can prevent the optimization of the query and thus lead to immediate abort. The statement is not run and the batch is aborted. The transaction state is generally left untouched. For example, assume there are four statements in a particular batch. If the third statement has a syntax error, none of the statements in the batch is executed. Optimization Errors Optimization errors would include rare situations where the statement encounters a problem when attempting to build an optimal execution plan. Example: “too many tables referenced in the query” error is reported because a “work table” was added to the plan. Runtime Errors Runtime errors are those that are encountered during the execution of the query. Consider the following batch: SELECT * FROM pubs.dbo.titles UPDATE pubs.dbo.authors SET au_lname = au_lname SELECT * FROM foo UPDATE pubs.dbo.authors SET au_lname = au_lname If you run the above statements in a batch, the first two statements will be executed, the third statement will fail because table foo does not exist, and the batch will terminate. Deferred Name Resolution is the feature that allows this batch to start executing before resolving the object foo. This feature allows SQL Server to delay object resolution and place a “placeholder” in the query’s execution. The object referenced by the placeholder is resolved until the query is executed. In our example, the execution of the statement “SELECT * FROM foo” will trigger another compile process to resolve the name again. This time, error message 208 is returned. Error: 208, Level 16, State 1, Line 1 Invalid object name 'foo'. Message 208 can be encountered as a runtime or compile error depending on whether the Deferred Name Resolution feature is available. In SQL Server 6.5 this would be considered a compile error and on SQL Server 2000 (and SQL Server7.0) as a runtime error due to Deferred Name Resolution. In the following example, if a trigger referenced authors2, the error is detected as SQL Server attempts to execute the trigger. However, under SQL Server 6.5 the create trigger statement fails because authors2 does not exist at compile time. When errors are encountered in a trigger, generally, the statement, batch, and transaction are aborted. You should be able to observe this by running the following script in pubs database: Create table tblTest(iID int) go create trigger trgInsert on tblTest for INSERT as begin select * from authors select * from authors2 select * from titles end go begin tran select 'Before' insert into tblTest values(1) select 'After' go select @@TRANCOUNT go When run in a batch, the statement and the batch are aborted but the transaction remains active. The follow script illustrates this: begin tran select 'Before' select * from authors2 select 'After' go select @@TRANCOUNT go One other factor in a compile versus runtime error is implicit data type conversions. If you were to run the following statements on SQL Server 6.5 and SQL Server 2000 (and SQL Server 7.0): create table tblData(dtData datetime) go select 1 insert into tblData values(12/13/99) go On SQL Server 6.5, you get an error before execution of the batch begins so no statements are executed and the batch is aborted. Error: 206, Level 16, State 2, Line 2 Operand type clash: int is incompatible with datetime On SQL Server 2000, you get the default value (1900-01-01 00:00:00.000) inserted into the table. SQL Server 2000 implicit data type conversion treats this as integer division. The integer division of 12/13/99 is 0, so the default date and time value is inserted, no error returned. To correct the problem on either version is to wrap the date string with quotes. See Bug #56118 (sqlbug_70) for more details about this situation. Another example of a runtime error is a 605 message. Error: 605 Attempt to fetch logical page %S_PGID in database '%.*ls' belongs to object '%.*ls', not to object '%.*ls'. A 605 error is always a runtime error. However, depending on the transaction isolation level, (e.g. using the NOLOCK lock hint), established by the SPID the handling of the error can vary. Specifically, a 605 error is considered an ACCESS error. Errors associated with buffer and page access are found in the 600 series of errors. When the error is encountered, the isolation level of the SPID is examined to determine proper handling based on information or fatal error level. Transaction Error Checking Not all errors cause transactions to automatically rollback. Although it is difficult to determine exactly which errors will rollback transactions and which errors will not, the main idea here is that programmers must perform error checking and handle errors appropriately. Error Handling Raiserror Details Raiserror seems to be a source of confusion but is really rather simple. Raiserror with severity levels of 20 or higher will terminate the connection. Of course, when the connection is terminated a full rollback of any open transaction will immediately be instantiated by the SQL Server (except distributed transaction with DTC involved). Severity levels lower than 20 will simply result in the error message being returned to the client. They do not affect the transaction scope of the connection. Consider the following batch: use pubs begin tran update authors set au_lname = 'smith' raiserror ('This is bad', 19, 1) with log select @@trancount With severity set at 19, the 'select @@trancount' will be executed after the raiserror statement and will return a value of 1. If severity is changed to 20, then the select statement will not run and the connection is broken. Important Error handling must occur not only in T-SQL batches and stored procedures, but also in application program code. Transactions and Triggers (1 of 2) Basic behavior assumes the implicit transactions setting is set to OFF. This behavior makes it possible to identify business logic errors in a trigger, raise an error, rollback the action, and add an audit table entry. Logically, the insert to the audit table cannot take place before the ROLLBACK action and you would not want to build in the audit table insert into every applications error handler that violated the business rule of the trigger. For more information, see also… SQL Server 2000 Books Online topic “Rollbacks in stored procedure and triggers“ (acdata.chm::/ac_8_md_06_4qcz.htm) IMPLICIT_TRANSACTIONS ON Behavior The behavior of firing other triggers on the same table can be tricky. Say you added a trigger that checks the CODE field. Read only versions of the rows contain the code ‘RO’ and read/write versions use ‘RW.’ Whenever someone tries to delete a row with a code ‘RO’ the trigger issues the rollback and logs an audit table entry. However, you also have a second trigger that is responsible for cascading delete operations. One client could issue the delete without implicit transactions on and only the current trigger would execute and then terminate the batch. However, a second client with implicit transactions on could issue the same delete and the secondary trigger would fire. You end up with a situation in which the cascading delete operations can take place (are committed) but the initial row remains in the table because of the rollback operation. None of the delete operations should be allowed but because the transaction scope was restarted because of the implicit transactions setting, they did. Transactions and Triggers (2 of 2) It is extremely difficult to determine the execution state of a trigger when using explicit rollback statements in combination with implicit transactions. The RETURN statement is not allowed to return a value. The only way I have found to set the @@ERROR is using a ‘raiserror’ as the last execution statement in the last trigger to execute. If you modify the example, this following RAISERROR statement will set @@ERROR to 50000: CREATE TRIGGER trgTest on tblTest for INSERT AS BEGIN ROLLBACK INSERT INTO tblAudit VALUES (1) RAISERROR('This is bad', 14,1) END However, this value does not carry over to a secondary trigger for the same table. If you raise an error at the end of the first trigger and then look at @@ERROR in the secondary trigger the @@ERROR remains 0. Carrying Forward an Active/Open Transaction It is possible to exit from a trigger and carry forward an open transaction by issuing a BEGIN TRAN or by setting implicit transaction on and doing INSERT, UPDATE, or DELETE. Warning It is never recommended that a trigger call BEGIN TRANSACTION. By doing this you increment the transaction count. Invalid code logic, not calling commit transaction, can lead to a situation where the transaction count remains elevated upon exit of the trigger. Transaction Count The behavior is better explained by understanding how the server works. It does not matter whether you are in a transaction, when a modification takes place the transaction count is incremented. So, in the simplest form, during the processing of an insert the transaction count is 1. On completion of the insert, the server will commit (and thus decrement the transaction count). If the commit identifies the transaction count has returned to 0, the actual commit processing is completed. Issuing a commit when the transaction count is greater than 1 simply decrements the nested transaction counter. Thus, when we enter a trigger, the transaction count is 1. At the completion of the trigger, the transaction count will be 0 due to the commit issued at the end of the modification statement (insert). In our example, if the connection was already in a transaction and called the second INSERT, since implicit transaction is ON, the transaction count in the trigger will be 2 as long as the ROLLBACK is not executed. At the end of the insert, the commit is again issued to decrement the transaction reference count to 1. However, the value does not return to 0 so the transaction remains open/active. Subsequent triggers are only fired if the transaction count at the end of the trigger remains greater than or equal to 1. The key to continuation of secondary triggers and the batch is the transaction count at the end of a trigger execution. If the trigger that performs a rollback has done an explicit begin transaction or uses implicit transactions, subsequent triggers and the batch will continue. If the transaction count is not 1 or greater, subsequent triggers and the batch will not execute. Warning Forcing the transaction count after issuing a rollback is dangerous because you can easily loose track of your transaction nesting level. When performing an explicit rollback in a trigger, you should immediately issue a return statement to maintain consistent behavior between a connection with and without implicit transaction settings. This will force the trigger(s) and batch to terminate immediately. One of the methods of dealing with this issue is to run ‘SET IMPLICIT_TRANSACTIONS OFF’ as the first statement of any trigger. Other methods may entails checking @@TRANCOUNT at the end of the trigger and continue to COMMIT the transaction as long as @@TRANCOUNT is greater than 1. Examples The following examples are based on this table: create table tbl50000Insert (iID int NOT NULL) go Note If more than one trigger is used, to guarantee the trigger firing sequence, the sp_settriggerorder command should be used. This command is omitted in these examples to simplify the complexity of the statements. First Example In the first example, the second trigger was never fired and the batch, starting with the insert statement, was aborted. Thus, the print statement was never issued. print('Trigger issues rollback - cancels batch') go create trigger trg50000Insert on tbl50000Insert for INSERT as begin select 'Inserted', * from inserted rollback tran select 'End of trigger', @@TRANCOUNT as 'TRANCOUNT' end go create trigger trg50000Insert2 on tbl50000Insert for INSERT as begin select 'In Trigger2' select 'Trigger 2 Inserted', * from inserted end go insert into tbl50000Insert values(1) print('---------------------- In same batch') select * from tbl50000Insert go -- Cleanup drop trigger trg50000Insert drop trigger trg50000Insert2 go delete from tbl50000Insert Second Example The next example shows that since a new transaction is started, the second trigger will be fired and the print statement in the batch will be executed. Note that the insert is rolled back. print('Trigger issues rollback - increases tran count to continue batch') go create trigger trg50000Insert on tbl50000Insert for INSERT as begin select 'Inserted', * from inserted rollback tran begin tran end go create trigger trg50000Insert2 on tbl50000Insert for INSERT as begin select 'In Trigger2' select 'Trigger 2 Inserted', * from inserted end go insert into tbl50000Insert values(2) print('---------------------- In same batch') select * from tbl50000Insert go -- Cleanup drop trigger trg50000Insert drop trigger trg50000Insert2 go delete from tbl50000Insert Third Example In the third example, the raiserror statement is used to set the @@ERROR value and the BEGIN TRAN statement is used in the trigger to allow the batch to continue to run. print('Trigger issues rollback - uses raiserror to set @@ERROR') go create trigger trg50000Insert on tbl50000Insert for INSERT as begin select 'Inserted', * from inserted rollback tran begin tran -- Increase @@trancount to allow -- batch to continue select @@trancount as ‘Trancount’ raiserror('This is from the trigger', 14,1) end go insert into tbl50000Insert values(3) select @@ERROR as 'ERROR', @@TRANCOUNT as 'Trancount' go -- Cleanup drop trigger trg50000Insert go delete from tbl50000Insert Fourth Example For the fourth example, a second trigger is added to illustrate the fact that @@ERROR value set in the first trigger will not be seen in the second trigger nor will it show up in the batch after the second trigger is fired. print('Trigger issues rollback - uses raiserror to set @@ERROR, not seen in second trigger and cleared in batch') go create trigger trg50000Insert on tbl50000Insert for INSERT as begin select 'Inserted', * from inserted rollback begin tran -- Increase @@trancount to -- allow batch to continue select @@TRANCOUNT as 'Trancount' raiserror('This is from the trigger', 14,1) end go create trigger trg50000Insert2 on tbl50000Insert for INSERT as begin select @@ERROR as 'ERROR', @@TRANCOUNT as 'Trancount' end go insert into tbl50000Insert values(4) select @@ERROR as 'ERROR', @@TRANCOUNT as 'Trancount' go -- Cleanup drop trigger trg50000Insert drop trigger trg50000Insert2 go delete from tbl50000Insert Lesson 3: Concepts – Locks and Applications This lesson outlines some of the common causes that contribute to the perception of a slow server. What You Will Learn After completing this lesson, you will be able to:  Explain how lock hints are used and their impact.  Discuss the effect on locking when an application uses Microsoft Transaction Server.  Identify the different kinds of deadlocks including distributed deadlock. Recommended Reading  Charter 14 “Locking”, Inside SQL Server 2000 by Kalen Delaney  Charter 16 “Query Tuning”, Inside SQL Server 2000 by Kalen Delaney Q239753 – Deadlock Situation Not Detected by SQL Server Q288752 – Blocked SPID Not Participating in Deadlock May Incorrectly be Chosen as victim Locking Hints UPDLOCK If update locks are used instead of shared locks while reading a table, the locks are held until the end of the statement or transaction. UPDLOCK has the advantage of allowing you to read data (without blocking other readers) and update it later with the assurance that the data has not changed since you last read it. READPAST READPAST is an optimizer hint for use with SELECT statements. When this hint is used, SQL Server will read past locked rows. For example, assume table T1 contains a single integer column with the values of 1, 2, 3, 4, and 5. If transaction A changes the value of 3 to 8 but has not yet committed, a SELECT * FROM T1 (READPAST) yields values 1, 2, 4, 5. Tip READPAST only applies to transactions operating at READ COMMITTED isolation and only reads past row-level locks. This lock hint can be used to implement a work queue on a SQL Server table. For example, assume there are many external work requests being thrown into a table and they should be serviced in approximate insertion order but they do not have to be completely FIFO. If you have 4 worker threads consuming work items from the queue they could each pick up a record using read past locking and then delete the entry from the queue and commit when they're done. If they fail, they could rollback, leaving the entry on the queue for the next worker thread to pick up. Caution The READPAST hint is not compatible with HOLDLOCK.  Try This: Using Locking Hints 1. Open a Query Window and connect to the pubs database. 2. Execute the following statements (--Conn 1 is optional to help you keep track of each connection): BEGIN TRANSACTION -- Conn 1 UPDATE titles SET price = price * 0.9 WHERE title_id = 'BU1032' 3. Open a second connection and execute the following statements: SELECT @@lock_timeout -- Conn 2 GO SELECT * FROM titles SELECT * FROM authors 4. Open a third connection and execute the following statements: SET LOCK_TIMEOUT 0 -- Conn 3 SELECT * FROM titles SELECT * FROM authors 5. Open a fourth connection and execute the following statement: SELECT * FROM titles (READPAST) -- Conn 4 WHERE title_ID < 'C' SELECT * FROM authors How many records were returned? 3 6. Open a fifth connection and execute the following statement: SELECT * FROM titles (NOLOCK) -- Conn 5 WHERE title_ID 0 the lock manager also checks for deadlocks every time a SPID gets blocked. So a single deadlock will trigger 20 seconds of more immediate deadlock detection, but if no additional deadlocks occur in that 20 seconds, the lock manager no longer checks for deadlocks at each block and detection again only happens every 5 seconds. Although normally not needed, you may use trace flag -T1205 to trace the deadlock detection process. Note Please note the distinction between application lock and other locks’ deadlock detection. For application lock, we do not rollback the transaction of the deadlock victim but simply return a -3 to sp_getapplock, which the application needs to handle itself. Deadlock Resolution How is a deadlock resolved? SQL Server picks one of the connections as a deadlock victim. The victim is chosen based on either which is the least expensive transaction (calculated using the number and size of the log records) to roll back or in which process “SET DEADLOCK_PRIORITY LOW” is specified. The victim’s transaction is rolled back, held locks are released, and SQL Server sends error 1205 to the victim’s client application to notify it that it was chosen as a victim. The other process can then obtain access to the resource it was waiting on and continue. Error 1205: Your transaction (process ID #%d) was deadlocked with another process and has been chosen as the deadlock victim. Rerun your transaction. Symptoms of deadlocking Error 1205 usually is not written to the SQL Server errorlog. Unfortunately, you cannot use sp_altermessage to cause 1205 to be written to the errorlog. If the client application does not capture and display error 1205, some of the symptoms of deadlock occurring are:  Clients complain of mysteriously canceled queries when using certain features of an application.  May be accompanied by excessive blocking. Lock contention increases the chances that a deadlock will occur. Triggers and Deadlock Triggers promote the deadlock priority of the SPID for the life of the trigger execution when the DEADLOCK PRIORITY is not set to low. When a statement in a trigger causes a deadlock to occur, the SPID executing the trigger is given preferential treatment and will not become the victim. Warning Bug 235794 is filed against SQL Server 2000 where a blocked SPID that is not a participant of a deadlock may incorrectly be chosen as a deadlock victim if the SPID is blocked by one of the deadlock participants and the SPID has the least amount of transaction logging. See KB article Q288752: “Blocked Spid Not Participating in Deadlock May Incorrectly be Chosen as victim” for more information. Distributed Deadlock – Scenario 1 Distributed Deadlocks The term distributed deadlock is ambiguous. There are many types of distributed deadlocks. Scenario 1 Client application opens connection A, begins a transaction, acquires some locks, opens connection B, connection B gets blocked by A but the application is designed to not commit A’s transaction until B completes. Note SQL Server has no way of knowing that connection A is somehow dependent on B – they are two distinct connections with two distinct transactions. This situation is discussed in scenario #4 in “Q224453 INF: Understanding and Resolving SQL Server 7.0 Blocking Problems”. Distributed Deadlock – Scenario 2 Scenario 2 Distributed deadlock involving bound connections. Two connections can be bound into a single transaction context with sp_getbindtoken/sp_bindsession or via DTC. Spid 60 enlists in a transaction with spid 61. A third spid 62 is blocked by spid 60, but spid 61 is blocked by spid 62. Because they are doing work in the same transaction, spid 60 cannot commit until spid 61 finishes his work, but spid 61 is blocked by 62 who is blocked by 60. This scenario is described in article “Q239753 - Deadlock Situation Not Detected by SQL Server.” Note SQL Server 6.5 and 7.0 do not detect this deadlock. The SQL Server 2000 deadlock detection algorithm has been enhanced to detect this type of distributed deadlock. The diagram in the slide illustrates this situation. Resources locked by a spid are below that spid (in a box). Arrows indicate blocking and are drawn from the blocked spid to the resource that the spid requires. A circle represents a transaction; spids in the same transaction are shown in the same circle. Distributed Deadlock – Scenario 3 Scenario 3 Distributed deadlock involving linked servers or server-to-server RPC. Spid 60 on Server 1 executes a stored procedure on Server 2 via linked server. This stored procedure does a loopback linked server query against a table on Server 1, and this connection is blocked by a lock held by Spid 60. Note No version of SQL Server is currently designed to detect this distributed deadlock. Lesson 4: Information Collection and Analysis This lesson outlines some of the common causes that contribute to the perception of a slow server. What You Will Learn After completing this lesson, you will be able to:  Identify specific information needed for troubleshooting issues.  Locate and collect information needed for troubleshooting issues.  Analyze output of DBCC Inputbuffer, DBCC PSS, and DBCC Page commands.  Review information collected from master.dbo.sysprocesses table.  Review information collected from master.dbo.syslockinfo table.  Review output of sp_who, sp_who2, sp_lock.  Analyze Profiler log for query usage pattern.  Review output of trace flags to help troubleshoot deadlocks. Recommended Reading Q244455 - INF: Definition of Sysprocesses Waittype and Lastwaittype Fields Q244456 - INF: Description of DBCC PSS Command for SQL Server 7.0 Q271509 - INF: How to Monitor SQL Server 2000 Blocking Q251004 - How to Monitor SQL Server 7.0 Blocking Q224453 - Understanding and Resolving SQL Server 7.0 Blocking Problem Q282749 – BUG: Deadlock information reported with SQL Server 2000 Profiler Locking and Blocking  Try This: Examine Blocked Processes 1. Open a Query Window and connect to the pubs database. Execute the following statements: BEGIN TRAN -- connection 1 UPDATE titles SET price = price + 1 2. Open another connection and execute the following statement: SELECT * FROM titles-- connection 2 3. Open a third connection and execute sp_who; note the process id (spid) of the blocked process. (Connection 3) 4. In the same connection, execute the following: SELECT spid, cmd, waittype FROM master..sysprocesses WHERE waittype 0 -- connection 3 5. Do not close any of the connections! What was the wait type of the blocked process?  Try This: Look at locks held Assumes all your connections are still open from the previous exercise. • Execute sp_lock -- Connection 3 What locks is the process from the previous example holding? Make sure you run ROLLBACK TRAN in Connection 1 to clean up your transaction. Collecting Information See Module 2 for more about how to gather this information using various tools. Recognizing Blocking Problems How to Recognize Blocking Problems  Users complain about poor performance at a certain time of day, or after a certain number of users connect.  SELECT * FROM sysprocesses or sp_who2 shows non-zero values in the blocked or BlkBy column.  More severe blocking incidents will have long blocking chains or large sysprocesses.waittime values for blocked spids.  Possibl

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