FRAMEWORK FOR WORKLOAD PREDICTION AND PHYSICAL DATABASE DESIGN

    公开(公告)号:US20230306009A1

    公开(公告)日:2023-09-28

    申请号:US17705728

    申请日:2022-03-28

    Applicant: SAP SE

    CPC classification number: G06F16/2282 G06F16/213 G06F16/256 G06F11/3414

    Abstract: According to some embodiments, methods and systems may be associated with a cloud computing environment. A workload prediction framework may receive observed workload information associated with a database in the cloud computing environment (e.g., a DataBase as a Service (“DBaaS”)). Based on the observed workload information, a Statement Arrival Rate (“SAR”) prediction may be generated. In addition, a host variable assignment prediction may be generated based on the observed workload information. The workload prediction framework may then use the SAR prediction and the host variable assignment prediction to automatically create a workload prediction for the database. A physical database design advisor (e.g., a table partitioning advisor) may receive the workload prediction and, responsive to the workload prediction, automatically generate a recommended physical layout for the database (e.g., using a cost model, the current physical layout, and an objective function).

    COMPUTER-IMPLEMENTED METHOD FOR DATABASE MANAGEMENT, COMPUTER PROGRAM PRODUCT AND DATABASE SYSTEM

    公开(公告)号:US20230004541A1

    公开(公告)日:2023-01-05

    申请号:US17410234

    申请日:2021-08-24

    Applicant: SAP SE

    Abstract: A computer-implemented method for database management is provided. The method comprises: receiving, from a client device, first data to be stored in a database system that comprises first data storage configured to store a data table and a deletion history table; storing the first data in second data storage that is external to the database system and that is in communication with the database system via a network; obtaining a link that enables access, via the network, to the first data stored in the second data storage; storing the link in the data table; and performing a deletion operation of the first data, in response to a request from the client device to delete the first data from the database system, wherein the deletion operation comprises: deleting the link from the data table without deleting the first data from the second data storage; and storing the link in the deletion history table with a timestamp corresponding to a point in time when the link is deleted from the data table.

    SCHEDULING OF QUERY PIPELINE EXECUTION
    3.
    发明公开

    公开(公告)号:US20230141462A1

    公开(公告)日:2023-05-11

    申请号:US17674313

    申请日:2022-02-17

    Applicant: SAP SE

    CPC classification number: G06F16/24544 G06F11/3409 G06F16/2255 G06F16/24539

    Abstract: A system includes reception of a query execution plan associated with a plurality of query execution pipelines, estimated execution costs and estimated intermediate result cardinalities, determination of one or more precedence relationships of the plurality of query execution pipelines, determination of an execution order of the plurality of query execution pipelines based on the estimated execution costs, the estimated intermediate result cardinalities, and the one or more precedence relationships, and providing of the execution order of the plurality of query execution pipelines and the query execution plan to a query execution engine.

    FRAMEWORK FOR WORKLOAD PREDICTION AND PHYSICAL DATABASE DESIGN

    公开(公告)号:US20240004855A1

    公开(公告)日:2024-01-04

    申请号:US18462513

    申请日:2023-09-07

    Applicant: SAP SE

    CPC classification number: G06F16/2282 G06F11/3414 G06F16/213 G06F16/256

    Abstract: According to some embodiments, methods and systems may be associated with a cloud computing environment. A workload prediction framework may receive observed workload information associated with a database in the cloud computing environment (e.g., a DataBase as a Service (“DBaaS”)). Based on the observed workload information, a Statement Arrival Rate (“SAR”) prediction may be generated. In addition, a host variable assignment prediction may be generated based on the observed workload information. The workload prediction framework may then use the SAR prediction and the host variable assignment prediction to automatically create a workload prediction for the database. A physical database design advisor (e.g., a table partitioning advisor) may receive the workload prediction and, responsive to the workload prediction, automatically generate a recommended physical layout for the database (e.g., using a cost model, the current physical layout, and an objective function).

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