Query processing using logical query steps having canonical forms

    公开(公告)号:US11940997B2

    公开(公告)日:2024-03-26

    申请号:US17446679

    申请日:2021-09-01

    CPC classification number: G06F16/2433 G06F16/2255 G06F16/2455

    Abstract: A query processing device includes a communication interface accessing a database and database catalog, a memory storing instructions, and a processor coupled to the memory and the communication interface. The processor executes the instructions to parse a query and generate first and second execution plans for the query, retrieve respective previously determined cardinality values for previously executed logical steps of the first and second execution plans from the database catalog, select an execution plan from the first execution plan or the second execution plan, the selected execution plan having a lower cost based on the previously determined cardinality values, and execute the selected execution plan on data accessed from the database. The query processing system stores actual cardinality values determined during the execution of the logical steps in the database catalog for use by subsequent queries. The query processing device, therefore, re-uses previously determined cardinality values.

    SYSTEM AND METHOD FOR COLUMN-SPECIFIC MATERIALIZATION SCHEDULING
    4.
    发明申请
    SYSTEM AND METHOD FOR COLUMN-SPECIFIC MATERIALIZATION SCHEDULING 审中-公开
    用于柱特异性材料化调度的系统和方法

    公开(公告)号:US20150269202A1

    公开(公告)日:2015-09-24

    申请号:US14663210

    申请日:2015-03-19

    Abstract: A method of dynamically computing an optimal materialization schedule for each column in a column oriented RDBMS. Dynamic column-specific materialization scheduling in a distributed column oriented RDBMS is optimized by choosing a materialization strategy based on execution cost including central processing unit (CPU), disk, and network costs for each individual exchange operator. The dynamic programming approach is computationally feasible because the optimal schedule for a sub-plan is path independent.

    Abstract translation: 一种动态计算面向列的RDBMS中每列的最优实现时间表的方法。 通过选择基于执行成本的实现策略,优化了基于分布式列的RDBMS中的动态列特定实现调度,包括每个单独交换运算符的中央处理单元(CPU),磁盘和网络成本。 动态规划方法在计算上是可行的,因为子计划的最优调度是路径独立的。

    QUERY PROCESSING USING LOGICAL QUERY STEPS HAVING CANONICAL FORMS

    公开(公告)号:US20220004551A1

    公开(公告)日:2022-01-06

    申请号:US17446679

    申请日:2021-09-01

    Abstract: A query processing device includes a communication interface accessing a database and database catalog, a memory storing instructions, and a processor coupled to the memory and the communication interface. The processor executes the instructions to parse a query and generate first and second execution plans for the query, retrieve respective previously determined cardinality values for previously executed logical steps of the first and second execution plans from the database catalog, select an execution plan from the first execution plan or the second execution plan, the selected execution plan having a lower cost based on the previously determined cardinality values, and execute the selected execution plan on data accessed from the database. The query processing system stores actual cardinality values determined during the execution of the logical steps in the database catalog for use by subsequent queries. The query processing device, therefore, re-uses previously determined cardinality values.

    Intelligent System of Information Broker under a Data and Energy Storage Internet Infrastructure

    公开(公告)号:US20170257450A1

    公开(公告)日:2017-09-07

    申请号:US15057665

    申请日:2016-03-01

    CPC classification number: H04L67/22 H02J3/14 H02J13/0006 H04L67/12

    Abstract: A method implemented in a network element (NE) configured to operate as an Ensemble Information Broker (EIB) within a data and energy storage internet architecture, the method comprising collecting device data, human presence data, and human activity data; determining predicted human behaviors for the user; determining a predicted energy metric for the smart system during a future time slot; calibrating weighted objective metrics of an operating status of the devices, a human comfort level, and a human productivity level according to the predicted human behaviors and user defined preference levels defined for the smart system; generating a set of control commands for the devices within the smart system by executing the dynamic human-centric Objective Function on the predicted energy metric; and transmitting, via a transmitter, the set of control commands to corresponding devices within the smart system.

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