GENERATION AND OPTIMIZATION OF DATA SHARING AMONG MULTIPLE DATA SOURCES AND CONSUMERS
    11.
    发明申请
    GENERATION AND OPTIMIZATION OF DATA SHARING AMONG MULTIPLE DATA SOURCES AND CONSUMERS 有权
    数据来源和消费者数据共享的生成和优化

    公开(公告)号:US20130110574A1

    公开(公告)日:2013-05-02

    申请号:US13666438

    申请日:2012-11-01

    CPC classification number: G06Q10/06 G06Q10/0631 G06Q10/101 H04L41/5003

    Abstract: Systems and methods for data sharing include generating at least one sharing plan with a cheapest cost and/or a shortest execution time for one or more sharing arrangements. Admissibility of the one or more sharing arrangements is determined such that a critical time path of the at least one sharing plan does not exceed a staleness level and a cost of the at least one sharing plan does not exceed a capacity. Sharing plans of admissible sharing arrangements are executed while maintaining the staleness level.

    Abstract translation: 用于数据共享的系统和方法包括以最便宜的成本生成至少一个共享计划和/或用于一个或多个共享安排的最短执行时间。 确定一个或多个共享安排的可接受性,使得至少一个共享计划的关键时间路径不超过平均级别,并且至少一个共享计划的成本不超过容量。 共同安排的共享计划在保持平级的同时执行。

    LATENCY-AWARE LIVE MIGRATION FOR MULTITENANT DATABASE PLATFORMS
    14.
    发明申请
    LATENCY-AWARE LIVE MIGRATION FOR MULTITENANT DATABASE PLATFORMS 有权
    多媒体数据库平台的实时移动

    公开(公告)号:US20130085998A1

    公开(公告)日:2013-04-04

    申请号:US13645103

    申请日:2012-10-04

    CPC classification number: G06F9/455 G06F9/5088 G06F17/303

    Abstract: Methods and systems for database migration from a multitenant database include taking a snapshot of an original database to be migrated with a hot backup process, such that the database is still capable of answering queries during the hot backup process; maintaining a query log of all queries to the tenant database after the hot backup process begins; initializing a new database at a target server using the snapshot; replaying the query log synchronize the new database with the original database; and answering new queries with the new database and not the original database.

    Abstract translation: 从多租户数据库进行数据库迁移的方法和系统包括:使用热备份流程来迁移原始数据库的快照,以使得数据库仍然能够在热备份过程中回答查询; 在热备份过程开始之后,将所有查询的查询日志保存到租户数据库; 使用快照在目标服务器上初始化新数据库; 重播查询日志将新数据库与原始数据库同步; 并使用新的数据库而不是原始数据库来回答新的查询。

    Generation and optimization of data sharing among multiple data sources and consumers
    17.
    发明授权
    Generation and optimization of data sharing among multiple data sources and consumers 有权
    生成和优化多个数据源和消费者之间的数据共享

    公开(公告)号:US08825506B2

    公开(公告)日:2014-09-02

    申请号:US13666438

    申请日:2012-11-01

    CPC classification number: G06Q10/06 G06Q10/0631 G06Q10/101 H04L41/5003

    Abstract: Systems and methods for data sharing include generating at least one sharing plan with a cheapest cost and/or a shortest execution time for one or more sharing arrangements. Admissibility of the one or more sharing arrangements is determined such that a critical time path of the at least one sharing plan does not exceed a staleness level and a cost of the at least one sharing plan does not exceed a capacity. Sharing plans of admissible sharing arrangements are executed while maintaining the staleness level.

    Abstract translation: 用于数据共享的系统和方法包括以最便宜的成本生成至少一个共享计划和/或用于一个或多个共享安排的最短执行时间。 确定一个或多个共享安排的可接受性,使得至少一个共享计划的关键时间路径不超过平均级别,并且至少一个共享计划的成本不超过容量。 共同安排的共享计划在保持平级的同时执行。

    System and methods for Predicting Query Execution Time for Concurrent and Dynamic Database Workloads
    18.
    发明申请
    System and methods for Predicting Query Execution Time for Concurrent and Dynamic Database Workloads 有权
    用于预测并发和动态数据库工作负载的查询执行时间的系统和方法

    公开(公告)号:US20140214880A1

    公开(公告)日:2014-07-31

    申请号:US14073817

    申请日:2013-11-06

    CPC classification number: G06F17/30442

    Abstract: Systems and methods for predicting query execution time for concurrent and dynamic database workloads include decomposing each query into a sequence of query pipelines based on the query plan from a query optimizer, and predicting an execution time of each pipeline with a progress predictor for a progress chart of query pipelines.

    Abstract translation: 用于预测并发和动态数据库工作负载的查询执行时间的系统和方法包括基于来自查询优化器的查询计划将每个查询分解为查询流水线序列,并使用进度图的进度预测器预测每个流水线的执行时间 的查询管道。

    Cost-Effective Data Layout Optimization Over Heterogeneous Storage Classes
    19.
    发明申请
    Cost-Effective Data Layout Optimization Over Heterogeneous Storage Classes 审中-公开
    经济有效的数据布局优化在异构存储类中

    公开(公告)号:US20140214793A1

    公开(公告)日:2014-07-31

    申请号:US14167506

    申请日:2014-01-29

    CPC classification number: G06F16/2453 G06F16/217

    Abstract: A system to optimize layout of database objects in a relational database management system stored on a plurality of storage classes each characterized by a price and a storage capacity includes a time-based query optimizer and a layout recommender coupled to the time-based query optimizer to estimate a total cost of operation (TCO) for a query workload on each data layout. The layout recommender includes an auxiliary object selection comprising database objects that include auxiliary objects that are optional to place with auxiliary object candidates being given from an auxiliary object recommender component.

    Abstract translation: 一种优化存储在多个存储类别中的关系数据库管理系统中的数据库对象的布局的系统,每个存储类别以价格和存储容量为特征,包括基于时间的查询优化器和布局推荐器,其耦合到基于时间的查询优化器 估计每个数据布局的查询工作负载的总体运营成本(TCO)。 布局推荐器包括辅助对象选择,其包括数据库对象,数据库对象包括辅助对象,所述辅助对象是辅助对象,其辅助对象候选被从辅助对象推荐器组件给出。

    TENANT PLACEMENT IN MULTITENANT DATABASES FOR PROFIT MAXIMIZATION
    20.
    发明申请
    TENANT PLACEMENT IN MULTITENANT DATABASES FOR PROFIT MAXIMIZATION 有权
    用于利润最大化的多媒体数据库中的优先放置

    公开(公告)号:US20130346360A1

    公开(公告)日:2013-12-26

    申请号:US13858476

    申请日:2013-04-08

    CPC classification number: G06F17/30289 G06Q10/0639

    Abstract: A method for database consolidation includes generating a model for expected penalty estimation; determining a tenant's value as a function of query arrival rate and SLA penalty; placing a tenant to minimize a total expected cost in the order of the tenant value; and progressively using additional servers to prevent any server from being saturated to guarantee a tenant placement that costs no more than four times the cost of any other placement

    Abstract translation: 数据库合并的方法包括生成预期罚球估计的模型; 确定租户的价值作为查询到达率和SLA罚款的函数; 将租户按租户价值的顺序最小化总预计成本; 并逐步使用额外的服务器来防止任何服务器饱和,以保证租户的安置成本不超过任何其他安置费用的四倍

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