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).

    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).

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