公开(公告)号：US20240302990A1

公开(公告)日：2024-09-12

申请号：US18178613

申请日：2023-03-06

申请人： SAP SE

发明人： Haotian Zhou ,  Yu Ma ,  Xiaotao Wang ,  Ge Yang ,  Jing He ,  Lei Huang

IPC分类号： G06F3/06 ,  G06N3/08

CPC分类号： G06F3/0655 ,  G06F3/0611 ,  G06F3/0673 ,  G06N3/08

摘要： Methods, systems, and computer-readable storage media for receiving a workload period, during which a workload is applied to a database system, providing a set of ML models based on historical data representative of historical executions of the workload over the workload period, each ML model configured to predict a cluster arrival rate curve (cARC), and during execution of the workload period and, for each timeslice of a plurality of timeslice of the workload period: providing a predicted cARC from each ML model, the predicted cARC representative of a predicted workload, determining column visiting times for each of a plurality of columns of each of a plurality of tables stored in the database system, generating a column list based on the column visiting times, and loading column data representative of columns included in the column list into low-latency memory prior to execution of a workload during the respective timeslice.

公开(公告)号：US11799739B1

公开(公告)日：2023-10-24

申请号：US17835115

申请日：2022-06-08

申请人： SAP SE

发明人： Yu Ma ,  Jing He ,  Haotian Zhou ,  Xiaotao Wang ,  Fu-qiang Lv

IPC分类号： H04L41/40 ,  H04L67/1001 ,  H04L41/0806 ,  G06F9/50 ,  G06F9/455

CPC分类号： H04L41/40 ,  G06F9/45558 ,  G06F9/5077 ,  H04L41/0806 ,  H04L67/10015 ,  G06F2009/4557 ,  G06F2009/45595

摘要： Methods, systems, and computer-readable storage media for providing a VM vector representative of resources that are to be consumed by the VM within the cloud computing environment, comparing the VM vector to each physical node vector in a set of physical node vectors to determine a distance, each physical node vector representative of resources available by a respective physical node, and selecting a physical node from a set of physical nodes based on a respective distance between the VM vector and a physical node vector representative of the physical node, and in response, automatically: deploying the VM to the physical node within the cloud computing environment at least partially by installing the VM on the physical node for execution thereon.

公开(公告)号：US20230376482A1

公开(公告)日：2023-11-23

申请号：US17748140

申请日：2022-05-19

申请人： SAP SE

发明人： Xiaotao Wang ,  Jing He

IPC分类号： G06F16/2452 ,  G06F16/242 ,  G06F16/28 ,  G06F16/22

CPC分类号： G06F16/24528 ,  G06F16/243 ,  G06F16/288 ,  G06F16/2237

摘要： Methods, systems, and computer-readable storage media for automatic index creation for relational database systems. Query statements from a relational database are processed to generate query patterns from the query statements. Vectorization of the query patterns is performed to transform each query pattern into a numerical vector. A clustering algorithm is executed to cluster the numerical vectors into multiple clusters. Each cluster has a respective cluster center. A frequent query pattern is determined, for at least some of the multiple clusters, that corresponds to a respective cluster center. Active columns in the frequent query patterns are determined and a database index is automatically created for each active column that does not currently have a database index.

公开(公告)号：US20230376202A1

公开(公告)日：2023-11-23

申请号：US17748145

申请日：2022-05-19

申请人： SAP SE

发明人： Xiaotao Wang ,  Jing He

IPC分类号： G06F3/06 ,  G06N3/04

CPC分类号： G06F3/0607 ,  G06N3/0445 ,  G06F3/0631 ,  G06F3/0653 ,  G06F3/0673

摘要： Methods, systems, and computer-readable storage media for machine learning database memory use prediction and adaptation. An example method includes determining a sampling interval for an application for sampling memory use by a database for the application. A plurality of historical memory use samples of amounts of memory used by the database are determined for the application based on the sampling interval. The plurality of historical memory use samples are provided for training of a machine learning model to predict memory use for the application by the database for a future time period. A set of current memory use samples are provided to the machine learning model and a memory use prediction for the application for an upcoming time period is received from the machine learning model. A determination is made as to whether to extend memory of the database for the application based on the memory use prediction.