公开(公告)号：US11928760B2

公开(公告)日：2024-03-12

申请号：US17186411

申请日：2021-02-26

Applicant: Oracle International Corporation

Inventor： Dustin Garvey ,  Uri Shaft ,  Sampanna Shahaji Salunke ,  Lik Wong

IPC: G06N20/00 ,  G06F9/50 ,  G06F11/34 ,  G06F17/18 ,  G06F18/2431 ,  G06F21/55 ,  G06Q10/04 ,  G06Q10/06 ,  G06Q10/0631 ,  G06Q10/1093 ,  G06Q30/0202 ,  G06T11/00 ,  G06T11/20 ,  H04L41/0896

CPC classification number: G06T11/206 ,  G06F11/3452 ,  G06F17/18 ,  G06F18/2431 ,  G06F21/55 ,  G06N20/00 ,  G06Q10/04 ,  G06Q10/06 ,  G06Q10/0631 ,  G06Q10/1093 ,  G06Q30/0202 ,  G06T11/001 ,  G06F9/505 ,  G06F2218/12 ,  G06Q10/06315 ,  H04L41/0896

Abstract: Techniques are described for automatically detecting and accommodating state changes in a computer-generated forecast. In one or more embodiments, a representation of a time-series signal is generated within volatile and/or non-volatile storage of a computing device. The representation may be generated in such a way as to approximate the behavior of the time-series signal across one or more seasonal periods. Once generated, a set of one or more state changes within the representation of the time-series signal is identified. Based at least in part on at least one state change in the set of one or more state changes, a subset of values from the sequence of values is selected to train a model. An analytical output is then generated, within volatile and/or non-volatile storage of the computing device, using the trained model.

公开(公告)号：US20210183120A1

公开(公告)日：2021-06-17

申请号：US17186411

申请日：2021-02-26

Applicant: Oracle International Corporation

Inventor： Dustin Garvey ,  Uri Shaft ,  Sampanna Shahaji Salunke ,  Lik Wong

IPC: G06T11/20 ,  G06Q30/02 ,  G06N20/00 ,  G06Q10/04 ,  G06F17/18 ,  G06F21/55 ,  G06Q10/06 ,  G06K9/00 ,  G06K9/62 ,  G06F11/34 ,  G06Q10/10 ,  G06T11/00

Abstract: Techniques are described for automatically detecting and accommodating state changes in a computer-generated forecast. In one or more embodiments, a representation of a time-series signal is generated within volatile and/or non-volatile storage of a computing device. The representation may be generated in such a way as to approximate the behavior of the time-series signal across one or more seasonal periods. Once generated, a set of one or more state changes within the representation of the time-series signal is identified. Based at least in part on at least one state change in the set of one or more state changes, a subset of values from the sequence of values is selected to train a model. An analytical output is then generated, within volatile and/or non-volatile storage of the computing device, using the trained model.

公开(公告)号：US10997171B2

公开(公告)日：2021-05-04

申请号：US16024868

申请日：2018-07-01

Applicant: Oracle International Corporation

Inventor： Arvind Kumar Maheshwari ,  Uri Shaft ,  Karl Dias ,  Vishwanath Karra ,  Stephen Wexler ,  Anil Kumar Kothuri

IPC: G06F16/2453

Abstract: Techniques for analyzing an execution of a query statement based on a random archive are disclosed. A plurality of query statements that are executed during a particular time period are identified. A random sampling function is executed to randomly select a set of query statements from the plurality of query statements. Execution plans and/or performance metrics associated with each execution of the randomly-selected query statements are stored into a random archive. Responsive to determining that a performance metric for a current execution of a particular query statement does not satisfy a performance criteria, information associated with the particular query statement from the random archive is analyzed. A model plan characteristic associated with an execution of the particular query statement stored in the random archive is determined. An execution plan associated with the model plan characteristic is determined for another execution of the particular query statement.

公开(公告)号：US10733528B2

公开(公告)日：2020-08-04

申请号：US15057062

申请日：2016-02-29

Applicant: Oracle International Corporation

Inventor： Dustin Garvey ,  Uri Shaft ,  Lik Wong

IPC: G06N20/00

Abstract: Techniques are described for classifying seasonal patterns in a time series. In an embodiment, a set of time series data is decomposed to generate a noise signal and a dense signal, where the noise signal includes a plurality of sparse features from the set of time series data and the dense signal includes a plurality of dense features from the set of time series data. A set of one or more sparse features from the noise signal is selected for retention. After selecting the sparse features, a modified set of time series data is generated by combining the set of one or more sparse features with a set of one or more dense features from the plurality of dense features. At least one seasonal pattern is identified from the modified set of time series data. A summary for the seasonal pattern may then be generated and stored.

公开(公告)号：US20190361693A1

公开(公告)日：2019-11-28

申请号：US16534896

申请日：2019-08-07

Applicant: Oracle International Corporation

Inventor： Dustin Garvey ,  Timothy Mark Frazier ,  Shriram Krishnan ,  Uri Shaft ,  Amit Ganesh ,  Prasad Ravuri ,  Sampanna Shahaji Salunke ,  Sumathi Gopalakrishnan

IPC: G06F8/65 ,  G06F8/60 ,  G06N20/00 ,  G06F16/906 ,  G06F8/61 ,  G06F9/50

Abstract: Techniques are described herein for scalable clustering of target resources by parameter set. In some embodiments, a plurality of parameter sets of varying length are received, where a parameter set identifies attributes of a target resource. A plurality of signature vectors are generated based on the plurality of parameter sets such that the signature vectors have equal lengths. A signature vector may map to one or more parameter sets of the plurality of parameter sets. A plurality of clusters are generated based on the similarity between signature vectors. Operations may be performed on a target resource based on one or more nodes in the plurality of clusters.

公开(公告)号：US10331802B2

公开(公告)日：2019-06-25

申请号：US15057065

申请日：2016-02-29

Applicant: Oracle International Corporation

Inventor： Dustin Garvey ,  Uri Shaft ,  Lik Wong ,  Amit Ganesh

IPC: G06F17/30 ,  G06F17/18 ,  G06F21/55 ,  G06Q10/04 ,  G06N99/00 ,  G06Q10/06

Abstract: Techniques are described for characterizing and summarizing seasonal patterns detected within a time series. A set of time series data is analyzed to identify a plurality of instances of a season, where each instance corresponds to a respective sub-period within the season. A first set of instances from the plurality of instances are associated with a particular class of seasonal pattern. After classifying the first set of instances, a second set of instances may remain unclassified or otherwise may not be associated with the particular class of seasonal pattern. Based on the first and second set of instances, a summary may be generated that identifies one or more stretches of time that are associated with the particular class of seasonal pattern. The one or more stretches of time may span at least one sub-period corresponding to at least one instance in the second set of instances.

公开(公告)号：US20170249649A1

公开(公告)日：2017-08-31

申请号：US15266987

申请日：2016-09-15

Applicant: Oracle International Corporation

Inventor： Dustin Garvey ,  Sampanna Shahaji Salunke ,  Uri Shaft

IPC: G06Q30/02

CPC classification number: G06T11/206 ,  G06F17/18 ,  G06F21/55 ,  G06K9/00536 ,  G06K9/628 ,  G06N20/00 ,  G06Q10/04 ,  G06Q10/06 ,  G06Q10/0631 ,  G06Q10/06315 ,  G06Q10/1093 ,  G06Q30/0202 ,  G06T11/001

Abstract: Systems and methods for trending patterns within a set of time-series data are described. In one or more embodiments, a set of one or more groups of data points that are associated with a particular seasonal pattern are generated within volatile and/or non-volatile storage. A set of pairwise slopes is determined for data point pairs within the set of one or more groups of data points. Based, at least in part on the plurality of pairwise slopes, a representative trend rate for the particular seasonal pattern is determined. A set of forecasted values is then generated within volatile or non-volatile storage based, at least in part, on the representative trend rate for the particular seasonal pattern.

公开(公告)号：US08892536B2

公开(公告)日：2014-11-18

申请号：US13627967

申请日：2012-09-26

Applicant: Oracle International Corporation

Inventor： Uri Shaft ,  Amirali Valiani ,  Peter Belknap

IPC: G06F7/02 ,  G06F17/30

CPC classification number: G06F17/30289

Abstract: A method for resolving a hang in a database system includes receiving a symbolic graph having a plurality of nodes, where each node represents a database session involved in the hang during a specified time interval. The blocking time associated with each node in the symbolic graph is recursively determined. The node that has the longest blocking time is output to a display for review by the database administrator. Alternatively, the database session represented by the node having the longest blocking time may be automatically eliminated.

Abstract translation: 一种用于解决数据库系统中的挂起的方法包括：接收具有多个节点的符号图，其中每个节点在指定的时间间隔内表示涉及挂起的数据库会话。 递归地确定与符号图中的每个节点相关联的阻塞时间。 具有最长阻塞时间的节点被输出到显示器以供数据库管理员查看。 或者，可以自动消除由具有最长阻塞时间的节点表示的数据库会话。

公开(公告)号：US11860729B2

公开(公告)日：2024-01-02

申请号：US17705760

申请日：2022-03-28

Applicant: Oracle International Corporation

Inventor： Eric Sutton ,  Dustin Garvey ,  Sampanna Shahaji Salunke ,  Uri Shaft

IPC: G06F11/00 ,  G06F11/07 ,  G06N5/04 ,  G06F16/21 ,  G06N20/00 ,  G06N3/08 ,  G06N3/006 ,  G06N5/048 ,  G06N20/10

CPC classification number: G06F11/0793 ,  G06F11/079 ,  G06F11/0727 ,  G06F16/217 ,  G06N5/04 ,  G06N20/00 ,  G06N3/006 ,  G06N3/08 ,  G06N5/048 ,  G06N20/10

Abstract: Techniques for predictive system remediation are disclosed. Based on attributes associated with applications of one or more system-selected remedial actions to one or more problematic system behaviors in a system (e.g., a database system), the system determines a predicted effectiveness of one or more future applications of a remedial action to a particular problematic system behavior, as of one or more future times. The system determines that the predicted effectiveness of the one or more future applications of the remedial action is positive but does not satisfy a performance criterion. Responsive to determining that the predicted effectiveness is positive but does not satisfy the performance criterion, the system generates a notification corresponding to the predicted effectiveness not satisfying the performance criterion. The system applies the remedial action to the particular problematic system behavior, despite already determining that the predicted effectiveness does not satisfy the one or more performance criteria.

公开(公告)号：US11670020B2

公开(公告)日：2023-06-06

申请号：US17039112

申请日：2020-09-30

Applicant: Oracle International Corporation

Inventor： Dustin Garvey ,  Uri Shaft ,  Edwina Ming-Yue Lu ,  Sampanna Shahaji Salunke ,  Lik Wong

IPC: G06Q30/0202 ,  G06Q10/04 ,  G06Q10/0631 ,  G06T11/20 ,  G06N20/00 ,  G06F17/18 ,  G06F21/55 ,  G06Q10/06 ,  G06F11/34 ,  G06F18/2431 ,  G06Q10/1093 ,  G06T11/00 ,  H04L41/0896 ,  G06F9/50

CPC classification number: G06T11/206 ,  G06F11/3452 ,  G06F17/18 ,  G06F18/2431 ,  G06F21/55 ,  G06N20/00 ,  G06Q10/04 ,  G06Q10/06 ,  G06Q10/0631 ,  G06Q10/1093 ,  G06Q30/0202 ,  G06T11/001 ,  G06F9/505 ,  G06F2218/12 ,  G06Q10/06315 ,  H04L41/0896

Abstract: Techniques are described for generating seasonal forecasts. According to an embodiment, a set of time-series data is associated with one or more classes, which may include a first class that represent a dense pattern that repeats over multiple instances of a season in the set of time-series data and a second class that represent another pattern that repeats over multiple instances of the season in the set of time-series data. A particular class of data is associated with at least two sub-classes of data, where a first sub-class represents high data points from the first class, and a second sub-class represents another set of data points from the first class. A trend rate is determined for a particular sub-class. Based at least in part on the trend rate, a forecast is generated.