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    • 2. 发明申请
    • Self-managing performance statistics repository for databases
    • 数据库的自我管理性能统计信息库
    • US20050086263A1
    • 2005-04-21
    • US10934771
    • 2004-09-03
    • Gary NgaiMichael FengAlex TsukermanBenoit DagevilleMark RamacherKarl DiasGraham WoodLeng Leng TanRichard SarwalSushil Kumar
    • Gary NgaiMichael FengAlex TsukermanBenoit DagevilleMark RamacherKarl DiasGraham WoodLeng Leng TanRichard SarwalSushil Kumar
    • G06F7/00
    • G06F17/30306
    • A self-managing workload repository (AWR) infrastructure useful for a database server to collect and manage selected sets of important system performance statistics. Based on a schedule, the AWR runs automatically to collect data about the operation of the database system, and stores the data that it captures into the database. The AWR is advantageously designed to be lightweight and to self manage its use of storage space so as to avoid ending up with a repository of performance data that is larger than the database that it is capturing data about. The AWR is configured to automatically capture snapshots of statistics data on a periodic basis as well as purge stale data on a periodic basis. Both the frequency of the statistics data capture and length of time for which data is kept is adjustable. Manual snapshots and purging may also be performed. The AWR captured data allows for both system level and user level analysis to be automatically performed without unduly impacting system performance, e.g., by eliminating or reducing the requirement to repeat the workload in order to diagnose problems.
    • 自管理工作负载存储库(AWR)基础架构可用于数据库服务器收集和管理所选的重要系统性能统计信息。 根据计划,AWR自动运行以收集有关数据库系统操作的数据,并将其捕获的数据存储到数据库中。 AWR有利地被设计为轻量级并且自我管理其对存储空间的使用,以避免最终获得比它正在捕获数据的数据库更大的性能数据库。 AWR配置为定期自动捕获统计数据的快照,并定期清除过期数据。 统计数据捕获的频率和保存数据的时间长短都是可调的。 也可以执行手动快照和清除。 AWR捕获的数据允许自动执行系统级别和用户级别分析,而不会不必要地影响系统性能,例如通过消除或减少重复工作负载以便诊断问题的要求。
    • 4. 发明授权
    • Self-managing performance statistics repository for databases
    • 数据库的自我管理性能统计信息库
    • US07774312B2
    • 2010-08-10
    • US10934771
    • 2004-09-03
    • Gary NgaiMichael FengAlex TsukermanBenoit DagevilleMark RamacherKarl DiasGraham S. WoodLeng Leng TanRichard SarwalSushil Kumar
    • Gary NgaiMichael FengAlex TsukermanBenoit DagevilleMark RamacherKarl DiasGraham S. WoodLeng Leng TanRichard SarwalSushil Kumar
    • G06F17/30
    • G06F17/30306
    • A self-managing workload repository (AWR) infrastructure useful for a database server to collect and manage selected sets of important system performance statistics. Based on a schedule, the AWR runs automatically to collect data about the operation of the database system, and stores the data that it captures into the database. The AWR is advantageously designed to be lightweight and to self manage its use of storage space so as to avoid ending up with a repository of performance data that is larger than the database that it is capturing data about. The AWR is configured to automatically capture snapshots of statistics data on a periodic basis as well as purge stale data on a periodic basis. Both the frequency of the statistics data capture and length of time for which data is kept is adjustable. Manual snapshots and purging may also be performed. The AWR captured data allows for both system level and user level analysis to be automatically performed without unduly impacting system performance, e.g., by eliminating or reducing the requirement to repeat the workload in order to diagnose problems.
    • 自管理工作负载存储库(AWR)基础架构可用于数据库服务器收集和管理所选的重要系统性能统计信息。 根据计划,AWR自动运行以收集有关数据库系统操作的数据,并将其捕获的数据存储到数据库中。 AWR有利地被设计为轻量级并且自我管理其对存储空间的使用,以避免最终获得比它正在捕获数据的数据库更大的性能数据库。 AWR配置为定期自动捕获统计数据的快照,并定期清除过期数据。 统计数据捕获的频率和保存数据的时间长短都是可调的。 也可以执行手动快照和清除。 AWR捕获的数据允许自动执行系统级别和用户级别分析,而不会不必要地影响系统性能,例如通过消除或减少重复工作负载以便诊断问题的要求。
    • 9. 发明授权
    • Metric correlation and analysis
    • 公制相关分析
    • US08229953B2
    • 2012-07-24
    • US12731743
    • 2010-03-25
    • Venkata Ramana KapuramRajiv K. MaheshwariRichard Sarwal
    • Venkata Ramana KapuramRajiv K. MaheshwariRichard Sarwal
    • G06F17/30G06F3/048
    • G06Q10/06
    • Techniques for improved metric correlation and analysis include, during a modeling phase, a user familiar with the types of system components deployed in an enterprise network and the metrics available for those types of system components specifying dependencies between metrics in a metric dependency model. During a binding phase, the metric dependency model is provided to a modified enterprise management (MEM) system which binds the model to particular enterprise system environment. During a metric correlation and analysis phase, the MEM system provides a user-interface through which a user visually compares metric data for metrics collected from system components deployed in an enterprise system environment bound to the model. The improved metric correlation analysis techniques allow users to more easily identify whether degradation in the performance of one metric is caused by performance degradation of underlying information technology system components as measured by related metrics specified in the metric dependency model.
    • 用于改进的度量相关性和分析的技术包括在建模阶段期间,熟悉部署在企业网络中的系统组件的类型的用户以及可用于指定度量依赖关系模型中的度量之间的依赖关系的那些类型的系统组件的度量。 在绑定阶段期间,将度量依赖关系模型提供给将模型绑定到特定企业系统环境的修改后的企业管理(MEM)系统。 在度量相关和分析阶段期间,MEM系统提供用户界面,用户通过该界面可视地比较从部署在与模型绑定的企业系统环境中的系统组件收集的度量的度量数据。 改进的度量相关分析技术允许用户更容易地识别一个度量的性能的劣化是否由基础信息技术系统组件的性能下降引起,如由度量依赖模型中指定的相关度量所测量的。
    • 10. 发明申请
    • METRIC CORRELATION AND ANALYSIS
    • 公制相关与分析
    • US20110238687A1
    • 2011-09-29
    • US12731743
    • 2010-03-25
    • Venkata Ramana KarpuramRajiv K. MaheshwariRichard Sarwal
    • Venkata Ramana KarpuramRajiv K. MaheshwariRichard Sarwal
    • G06F3/048G06F17/30
    • G06Q10/06
    • Techniques for improved metric correlation and analysis include, during a modeling phase, a user familiar with the types of system components deployed in an enterprise network and the metrics available for those types of system components specifying dependencies between metrics in a metric dependency model. During a binding phase, the metric dependency model is provided to a modified enterprise management (MEM) system which binds the model to particular enterprise system environment. During a metric correlation and analysis phase, the MEM system provides a user-interface through which a user visually compares metric data for metrics collected from system components deployed in an enterprise system environment bound to the model. The improved metric correlation analysis techniques allow users to more easily identify whether degradation in the performance of one metric is caused by performance degradation of underlying information technology system components as measured by related metrics specified in the metric dependency model.
    • 用于改进的度量相关性和分析的技术包括在建模阶段期间,熟悉部署在企业网络中的系统组件的类型的用户以及可用于指定度量依赖关系模型中的度量之间的依赖关系的那些类型的系统组件的度量。 在绑定阶段期间,将度量依赖关系模型提供给将模型绑定到特定企业系统环境的修改后的企业管理(MEM)系统。 在度量相关和分析阶段期间,MEM系统提供用户界面,用户通过该界面可视地比较从部署在与模型绑定的企业系统环境中的系统组件收集的度量的度量数据。 改进的度量相关分析技术允许用户更容易地识别一个度量的性能的劣化是否由基础信息技术系统组件的性能下降引起,如由度量依赖模型中指定的相关度量所测量的。