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    • 12. 发明申请
    • Anchor for database synchronization excluding uncommitted transaction modifications
    • 锚定数据库同步,不包括未提交的事务修改
    • US20080109494A1
    • 2008-05-08
    • US11592588
    • 2006-11-03
    • Sudarshan A. ChitreRafik RobealShaoyu Zhou
    • Sudarshan A. ChitreRafik RobealShaoyu Zhou
    • G06F17/30
    • G06F17/30575
    • Described is a technology in which an anchor value is determined, for example to synchronize a destination database or data store with modifications made to a source database. The new anchor value is determined in a manner that excludes modifications corresponding to any uncommitted transactions. The new anchor value may be based on a counter value or a date and time value stored with each modification. The new anchor value may be determined by comparing a first set of committed modifications that do not include uncommitted modifications against a second set of modifications that includes committed modifications and uncommitted modifications. Alternatively, the new anchor value may be determined from the earliest start date and time among the modifications that are part of any uncommitted transactions. The anchor may be used (e.g., via queries) to enumerate modifications for synchronization, and also for detecting conflicts between the source and destination databases.
    • 描述了一种技术,其中确定锚值,例如使目标数据库或数据存储与对源数据库的修改同步。 新的锚点值以排除与任何未提交交易相对应的修改的方式确定。 新的锚值可以基于每个修改存储的计数器值或日期和时间值。 可以通过将不包括未提交的修改的第一组提交的修改与包括已提交的修改和未提交的修改的第二组修改进行比较来确定新的锚值。 或者,可以从作为任何未提交事务的一部分的修改中的最早开始日期和时间来确定新的锚点值。 可以使用锚点(例如,经由查询)来枚举用于同步的修改,并且还用于检测源数据库和目的地数据库之间的冲突。
    • 14. 发明授权
    • Systems and methods for the utilization of metadata for synchronization optimization
    • 利用元数据进行同步优化的系统和方法
    • US08046424B2
    • 2011-10-25
    • US10927726
    • 2004-08-27
    • Lev NovikTomas TaliusYunxin WuShaoyu Zhou
    • Lev NovikTomas TaliusYunxin WuShaoyu Zhou
    • G06F15/167G06F15/16G06F7/00G06F17/00
    • G06F17/30176G06F17/30575Y10S707/99955
    • Various embodiments of the present invention are directed to synchronization utilizing one or more optimizations through the utilization of metadata. For several embodiments of the present invention, one method for optimizing synchronization is to reduce the overhead required for said synchronization by having each peer only tracking changes for itself and other peers within its change community (or communities) (a.k.a., “Intra-Community-Only Change Tracking Optimization”). For certain embodiments of the present invention, another method for optimizing synchronization is to not create synchronization overhead until required. For numerous embodiments of the present invention, yet another method for optimizing synchronization is to minimize redundant use of a partner's unique global ID—a large and cumbersome number—and to instead maintain a table that cross-references each partner (and its unique global ID) with a smaller and much less cumbersome partner key.
    • 本发明的各种实施例涉及通过利用元数据利用一个或多个优化的同步。 对于本发明的几个实施例,用于优化同步的一种方法是通过使每个对等体仅跟踪其变化社区(或社区)(或社区)内的其他对等体(也称为“共同体内社区”)来减少所述同步所需的开销, 只有更改跟踪优化“)。 对于本发明的某些实施例,用于优化同步的另一种方法是在需要之前不产生同步开销。 对于本发明的许多实施例,用于优化同步的另一种方法是最小化伙伴的唯一全局ID(冗余和繁琐的数量)的冗余使用,并且替代地维护交叉引用每个伙伴的表(及其唯一的全局ID )具有更小和更少的繁琐的合作伙伴密钥。
    • 17. 发明申请
    • Systems and methods for the utilization of metadata for synchronization optimization
    • 利用元数据进行同步优化的系统和方法
    • US20050256907A1
    • 2005-11-17
    • US10927726
    • 2004-08-27
    • Lev NovikTomas TaliusYunxin WuShaoyu Zhou
    • Lev NovikTomas TaliusYunxin WuShaoyu Zhou
    • G06F13/00G06F17/30
    • G06F17/30176G06F17/30575Y10S707/99955
    • Various embodiments of the present invention are directed to synchronization utilizing one or more optimizations through the utilization of metadata. For several embodiments of the present invention, one method for optimizing synchronization is to reduce the overhead required for said synchronization by having each peer only tracking changes for itself and other peers within its change community (or communities) (a.k.a., “Intra-Community-Only Change Tracking Optimization”). For certain embodiments of the present invention, another method for optimizing synchronization is to not create synchronization overhead until required. For numerous embodiments of the present invention, yet another method for optimizing synchronization is to minimize redundant use of a partner's unique global ID—a large and cumbersome number—and to instead maintain a table that cross-references each partner (and its unique global ID) with a smaller and much less cumbersome partner key.
    • 本发明的各种实施例涉及通过利用元数据利用一个或多个优化的同步。 对于本发明的几个实施例,用于优化同步的一种方法是通过使每个对等体仅跟踪其变化社区(或社区)(或社区)内的其他对等体(也称为“共同体内社区”)来减少所述同步所需的开销, 只有更改跟踪优化“)。 对于本发明的某些实施例,用于优化同步的另一种方法是在需要之前不产生同步开销。 对于本发明的许多实施例,用于优化同步的另一种方法是最小化伙伴的唯一全局ID(冗余和繁琐的数量)的冗余使用,并且替代地维护交叉引用每个伙伴的表(及其唯一的全局ID )具有更小和更少的繁琐的合作伙伴密钥。
    • 19. 发明授权
    • Optimizer with neural network estimator
    • 优化器与神经网络估计器
    • US6108648A
    • 2000-08-22
    • US896931
    • 1997-07-18
    • Seetha M. LakshmiShaoyu Zhou
    • Seetha M. LakshmiShaoyu Zhou
    • G06F15/18G06F12/00G06F17/30G06N3/00
    • G06F17/30469Y10S706/934Y10S707/99932Y10S707/99933
    • A computer operated apparatus estimates values needed by an optimizer in a database management system (DBMS). The DBMS has one or more tables for storing data, each table having zero or more columns of user-definable data types and zero or more associated user-defined routines (UDRs). The apparatus has a feature vector extractor connected to the database tables for converting the UDR inputs into a base type representation. A neural network receives the feature vector and generates estimated values which are provided to the optimizer of the DBMS. The neural network can be trained periodically using randomly generated queries, or it can be trained dynamically by capturing data generated during a query. During operation, the optimizer dynamically invokes the neural network to generate estimates such as selectivity and cost per call for determining optimum query search sequence.
    • 计算机操作的装置估计优化器在数据库管理系统(DBMS)中所需的值。 DBMS具有用于存储数据的一个或多个表,每个表具有零个或多个用户可定义数据类型的列和零个或多个相关联的用户定义例程(UDR)。 该装置具有连接到数据库表的特征向量提取器,用于将UDR输入转换为基本类型表示。 神经网络接收特征向量并产生提供给DBMS的优化器的估计值。 可以使用随机生成的查询周期性地训练神经网络,或者可以通过捕获在查询期间生成的数据来动态训练神经网络。 在操作期间,优化器动态地调用神经网络以产生估计,例如用于确定最佳查询搜索序列的每个呼叫的选择性和成本。