Visionary query processing in Hadoop utilizing opportunistic views

    公开(公告)号:US09740739B2

    公开(公告)日:2017-08-22

    申请号:US14506625

    申请日:2014-10-04

    CPC classification number: G06F17/30466

    Abstract: Systems and methods are disclosed for query processing in a big data analytics platform by enumerating plans for a current query using a processor; building a dominance graph for the current query; for each plan, determining a regret value and a score for the plan based on the regret value and cost; and selecting query plans in an online fashion for query processing in big data analytics platforms where intermediate results are materialized and can be reused later.

    Visionary Query Processing in Hadoop Utilizing Opportunistic Views
    2.
    发明申请
    Visionary Query Processing in Hadoop Utilizing Opportunistic Views 有权
    Hadoop中的远见查询处理利用机会观点

    公开(公告)号:US20150149434A1

    公开(公告)日:2015-05-28

    申请号:US14506625

    申请日:2014-10-04

    CPC classification number: G06F17/30466

    Abstract: Systems and methods are disclosed for query processing in a big data analytics platform by enumerating plans for a current query using a processor; building a dominance graph for the current query; for each plan, determining a regret value and a score for the plan based on the regret value and cost; and selecting query plans in an online fashion for query processing in big data analytics platforms where intermediate results are materialized and can be reused later.

    Abstract translation: 通过枚举使用处理器的当前查询的计划,在大数据分析平台中公开了用于查询处理的系统和方法; 构建当前查询的优势图; 对于每个计划,根据遗憾价值和成本确定计划的遗憾价值和得分; 并以在线方式选择大型数据分析平台中的查询处理查询计划,其中中间结果实现并可以稍后重用。

    SYSTEMS AND METHODS FOR TUNING MULTI-STORE SYSTEMS TO SPEED UP BIG DATA QUERY WORKLOAD
    4.
    发明申请
    SYSTEMS AND METHODS FOR TUNING MULTI-STORE SYSTEMS TO SPEED UP BIG DATA QUERY WORKLOAD 审中-公开
    用于调整多存储系统以加快大量数据查询工作的系统和方法

    公开(公告)号:US20150081668A1

    公开(公告)日:2015-03-19

    申请号:US14321875

    申请日:2014-07-02

    CPC classification number: G06F16/24539 G06F16/2282 G06F16/2393 G06F16/285

    Abstract: Systems and methods are disclosed to run a multistore system by receiving by-products of query processing in the multistore system, wherein the by-products include views or materializations of intermediate data; placing the views or materializations across the stores based on recently observed queries as indicative of a future query workload; determining a benefit score for each view based on a predicted future query workload, wherein each store has an allotted view storage budget, and there is a view transfer budget for transferring views between the stores; and tuning a physical design of the multistore system.

    Abstract translation: 公开了通过在多存储系统中接收查询处理的副产品来运行多存储系统的系统和方法,其中副产品包括中间数据的视图或实现; 根据最近观察到的查询将视图或实现放置在整个商店中,以表示未来的查询工作量; 基于预测的未来查询工作负载来确定每个视图的利益分数,其中每个商店具有分配的视图存储预算,并且存在用于在商店之间传送视图的视图传送预算; 并调整多存储系统的物理设计。

    Method and System for Database Cloud Bursting
    5.
    发明申请
    Method and System for Database Cloud Bursting 审中-公开
    数据库云突发的方法和系统

    公开(公告)号:US20140019415A1

    公开(公告)日:2014-01-16

    申请号:US13939652

    申请日:2013-07-11

    CPC classification number: G06F16/214 G06Q10/0639

    Abstract: A computer implemented method for cloud bursting applied to a database includes employing a database live migration using a database hot backup capability to support database cloud bursting without client service interruption in multitenant databases, ascertaining a critical time to start/redo the database cloud bursting to a public cloud so as to meet a service level agreement SLA while leveraging a private cloud for the database to a maximum level, and determining tenants of the database to burst into the public cloud to responsive to costs and benefits.

    Abstract translation: 应用于数据库的计算机实现的云突发方法包括采用数据库实时迁移,使用数据库热备份功能来支持数据库云突发,而无需多租户数据库中的客户端服务中断,确定启动/重做数据库云突发的关键时间 公共云,以便满足服务水平协议SLA,同时将数据库的私有云最大限度地利用,并确定数据库的租户突破公共云以响应成本和收益。

    MISO (multistore-online-tuning) system
    6.
    发明授权
    MISO (multistore-online-tuning) system 有权
    MISO(多存储在线调优)系统

    公开(公告)号:US09569491B2

    公开(公告)日:2017-02-14

    申请号:US14321881

    申请日:2014-07-02

    Abstract: A system includes first and second data stores, each store having a set of materialized views of the base data and the views comprise a multistore physical design; an execution layer coupled to the data stores; a query optimizer coupled to the execution layer; and a tuner coupled to the query optimizer and the execution layer, wherein the tuner determines a placement of the materialized views across the stores to improve workload performance upon considering each store's view storage budget and a transfer budget when moving views across the stores.

    Abstract translation: 系统包括第一和第二数据存储,每个存储具有一组基本数据的物化视图,并且视图包括多存储物理设计; 耦合到数据存储的执行层; 耦合到执行层的查询优化器; 以及耦合到所述查询优化器和所述执行层的调谐器,其中,所述调谐器在跨所述商店移动视图时,在考虑每个商店的视图存储预算和转移预算时,确定跨所述商店的物化视图的放置以改善工作负载性能。

    MISO (MultIStore-Online-tuning) System
    7.
    发明申请
    MISO (MultIStore-Online-tuning) System 有权
    MISO(Multistore-Online-tuning)系统

    公开(公告)号:US20160147832A1

    公开(公告)日:2016-05-26

    申请号:US14321881

    申请日:2014-07-02

    Abstract: A system includes first and second data stores, each store having a set of materialized views of the base data and the views comprise a multistore physical design; an execution layer coupled to the data stores; a query optimizer coupled to the execution layer; and a tuner coupled to the query optimizer and the execution layer, wherein the tuner determines a placement of the materialized views across the stores to improve workload performance upon considering each store's view storage budget and a transfer budget when moving views across the stores.

    Abstract translation: 系统包括第一和第二数据存储,每个存储具有一组基本数据的物化视图,并且视图包括多存储物理设计; 耦合到数据存储的执行层; 耦合到执行层的查询优化器; 以及耦合到所述查询优化器和所述执行层的调谐器,其中,所述调谐器在跨所述商店移动视图时,在考虑每个商店的视图存储预算和转移预算时,确定跨所述商店的物化视图的放置以改善工作负载性能。

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