公开(公告)号：US11379456B2

公开(公告)日：2022-07-05

申请号：US17060999

申请日：2020-10-01

Applicant: Oracle International Corporation

Inventor： Onur Kocberber ,  Mayur Bency ,  Marc Jolles ,  Seema Sundara ,  Nipun Agarwal

IPC: G06F16/23 ,  G06F16/245

Abstract: Systems and methods for adjusting parameters for a spin-lock implementation of concurrency control are described herein. In an embodiment, a system continuously retrieves, from a resource management system, one or more state values defining a state of the resource management system. Based on the one or more state values, the system determines that the resource management system has reached a steady state and, in response adjusts a plurality of parameters for spin-locking performed by said resource management system to identify optimal values for the plurality of parameters. After adjusting the plurality of parameters, the system detects, based on one or more current state values, a workload change in the resource management system and, in response, readjusts the plurality of parameters for spin-locking performed by said resource management system to identify new optimal values for the parameters.

公开(公告)号：US12248444B1

公开(公告)日：2025-03-11

申请号：US18539928

申请日：2023-12-14

Applicant: Oracle International Corporation

Inventor： Fotis Savva ,  Farhan Tauheed ,  Marc Jolles ,  Onur Kocberber ,  Seema Sundara ,  Nipun Agarwal

IPC: G06F16/20 ,  G06F16/21 ,  G06F16/2455 ,  G06F16/28

Abstract: Auto-parallel-load techniques are provided for automatically loading database objects from an on-disk database system into an in-memory database system. The auto-parallel-load techniques involve a pipeline that includes several components. In one implementation, each of the pipeline components is configured to receive, extract information from, and add information to, a “state object”. One or more of the pipeline components include logic that is based on the output of a corresponding machine learning model. The machine learning models used by the pipeline components may be trained from training sets from which outliers have been excluded, and may be used as the basis for generating linear models that are used during runtime, to produce estimates that affect the parameters of the auto-parallel-load operation.

公开(公告)号：US20220107933A1

公开(公告)日：2022-04-07

申请号：US17060999

申请日：2020-10-01

Applicant: Oracle International Corporation

Inventor： Onur Kocberber ,  Mayur Bency ,  Marc Jolles ,  Seema Sundara ,  Nipun Agarwal

IPC: G06F16/23 ,  G06F16/245

Abstract: Systems and methods for adjusting parameters for a spin-lock implementation of concurrency control are described herein. In an embodiment, a system continuously retrieves, from a resource management system, one or more state values defining a state of the resource management system. Based on the one or more state values, the system determines that the resource management system has reached a steady state and, in response adjusts a plurality of parameters for spin-locking performed by said resource management system to identify optimal values for the plurality of parameters. After adjusting the plurality of parameters, the system detects, based on one or more current state values, a workload change in the resource management system and, in response, readjusts the plurality of parameters for spin-locking performed by said resource management system to identify new optimal values for the parameters.

公开(公告)号：US11907250B2

公开(公告)日：2024-02-20

申请号：US17871092

申请日：2022-07-22

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Urvashi Oswal ,  Marc Jolles ,  Onur Kocberber ,  Seema Sundara ,  Nipun Agarwal

IPC: G06F16/24 ,  G06F16/25 ,  G06F16/21 ,  G06F11/34 ,  G06F16/2458

CPC classification number: G06F16/258 ,  G06F11/3409 ,  G06F16/21 ,  G06F16/2462

Abstract: Techniques are described for executing machine learning models trained for specific operators with feature values that are based on the actual execution of a workload set. The machine learning models generate an estimate of benefit gain/cost for executing operations on data portions in the alternative encoding format. Such data potions may be sorted based on the estimated benefit, in an embodiment. Using cost estimation machine learning models for memory space, the data portions with the most benefits that comply with the existing memory space constraints are recommended and/or are automatically encoded into the alternative encoding format.