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    DATA DRIVEN METHODS AND SYSTEMS FOR WHAT IF ANALYSIS
    12.
    发明申请
    DATA DRIVEN METHODS AND SYSTEMS FOR WHAT IF ANALYSIS 有权

    公开(公告)号：US20210073680A1

    公开(公告)日：2021-03-11

    申请号：US17028166

    申请日：2020-09-22

    Applicant: Oracle International Corporation

    Inventor： Dustin Garvey ,  Sampanna Shahaji Salunke ,  Uri Shaft ,  Amit Ganesh ,  Sumathi Gopalakrishnan

    IPC: G06N20/00 ,  G06F9/46

    Abstract: Techniques are described for applying what-f analytics to simulate performance of computing resources in cloud and other computing environments. In one or more embodiments, a plurality of time-series datasets are received including time-series datasets representing a plurality of demands on a resource and datasets representing performance metrics for a resource. Based on the datasets at least one demand propagation model and at least one resource prediction model are trained. Responsive to receiving an adjustment to a first set of one or more values associated with a first demand: (a) a second adjustment is generated for a second set of one or more values associated with a second demand; and (b) a third adjustment is generated for a third set of one or more values that is associated with the resource performance metric.

    Database Performance Analysis Based on a Random Archive
    13.
    发明申请
    Database Performance Analysis Based on a Random Archive 审中-公开

    公开(公告)号：US20200004860A1

    公开(公告)日：2020-01-02

    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: G06F17/30

    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.

    Scalable, multi-dimensional search for optimal configuration
    14.
    发明授权
    Scalable, multi-dimensional search for optimal configuration 有权

    公开(公告)号：US10466936B2

    公开(公告)日：2019-11-05

    申请号：US14865476

    申请日：2015-09-25

    Applicant: Oracle International Corporation

    Inventor： John Raitto ,  Uri Shaft

    IPC: G06F3/06 ,  G06F16/28

    Abstract: According to an embodiment, storage configurations are identified for storing items, such as database tables, partitions, or any other types of objects or data structures, within a desired storage area, such as an in-memory data store or any other limited storage resource. Each of the storage configurations is assigned to a particular item of the items. Each of the storage configurations associates the assigned particular item with one or more storage configuration options. Storage recommendations are generated for at least a set of the storage configurations. A different storage recommendation exists for each storage configuration in the set of the storage configurations. The storage recommendation associates the storage configuration with a range of possible storage sizes for a particular storage area of a system. Based on the storage recommendations, recommended system configurations a generated for different possible storage sizes of the particular storage area.

    SYSTEM FOR DETECTING AND CHARACTERIZING SEASONS
    16.
    发明申请
    SYSTEM FOR DETECTING AND CHARACTERIZING SEASONS 审中-公开

    公开(公告)号：US20170249376A1

    公开(公告)日：2017-08-31

    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

    CPC classification number: G06F16/285 ,  G06F16/2477 ,  G06F17/18 ,  G06F21/55 ,  G06N20/00 ,  G06Q10/04 ,  G06Q10/06315 ,  G06Q30/0201 ,  G06Q30/0202

    Abstract: Techniques are described for characterizing and summarizing seasonal patterns detected within a time series. According to an embodiment, 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.

    Systems And Methods For Detecting Long Term Seasons
    18.
    发明申请
    Systems And Methods For Detecting Long Term Seasons 有权

    公开(公告)号：US20240403719A1

    公开(公告)日：2024-12-05

    申请号：US18732481

    申请日：2024-06-03

    Applicant: Oracle International Corporation

    Inventor： Dustin Garvey ,  Sampanna Salunke ,  Uri Shaft ,  Sumathi Gopalakrishnan

    IPC: G06N20/00 ,  G06N5/02

    Abstract: Techniques for machine-learning of long-term seasonal patterns are disclosed. In some embodiments, a network service receives a set of time-series data that tracks metric values of at least one computing resource over time. Responsive to receiving the time-series data, the network service detects a subset of metric values that are outliers and associated with a plurality of timestamps. The network service maps the plurality of timestamps to one or more encodings of at least one encoding space that defines a plurality of encodings for different seasonal patterns. Based on the mapped encodings, the network service generates a representation of a seasonal pattern. Based on the representation of the seasonal pattern, the network service may perform one or more operations in association with the at least one computing resource.

    Unsupervised method for classifying seasonal patterns
    19.
    发明授权
    Unsupervised method for classifying seasonal patterns 有权

    公开(公告)号：US11836162B2

    公开(公告)日：2023-12-05

    申请号：US16862496

    申请日：2020-04-29

    Applicant: Oracle International Corporation

    Inventor： Dustin Garvey ,  Uri Shaft ,  Lik Wong

    IPC: G06F16/28 ,  G06N20/00

    CPC classification number: G06F16/285 ,  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.

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